Note: Descriptions are shown in the official language in which they were submitted.
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WEARABLE DEVICE AND PLATFORM FOR SENSORY INPUT
FIELD
The present invention relates generally to electrical and electronic hardware,
computer
software, wired and wireless network communications, and computing devices.
More
specifically, techniques for a wearable device and platform for sensory input
are described.
BACKGROUND
With the advent of greater computing capabilities in smaller personal and/or
portable form
factors and an increasing number of applications (i.e., computer and Internet
software or
programs) for different uses, consumers (i.e., users) have access to large
amounts of personal data.
Information and data are often readily available, but poorly captured using
conventional data
capture devices. Conventional devices typically lack capabilities that can
capture, analyze,
communicate, or use data in a contextually-meaningful, comprehensive, and
efficient manner.
Further, conventional solutions are often limited to specific individual
purposes or uses,
demanding that users invest in multiple devices in order to perform different
activities (e.g,, a
sports watch for tracking time and distance, a UPS receiver for monitoring a
hike or run, a
cyclometer for gathering cycling data, and others). Although a wide range of
data and
information is available, conventional devices and applications fail to
provide effective solutions
that comprehensively capture data for a given user across numerous disparate
activities.
Some conventional solutions combine a small number of discrete functions.
Functionality
for data capture, processing, storage, or communication in conventional
devices such as a watch
or timer with a heart rate monitor or global positioning system ("UPS")
receiver are available
conventionally, but are expensive to manufacture and purchase, Other
conventional solutions for
combining personal data capture facilities often present numerous design and
manufacturing
problems such as size restrictions, specialized materials requirements,
lowered tolerances for
defects such as pits or holes in coverings for water-resistant or waterproof
devices, unreliability,
higher failure rates, increased manufacturing time, and expense. Subsequently,
conventional
devices such as fitness watches, heart rate monitors, GPS-enabled fitness
monitors, health
monitors (e.g., diabetic blood sugar testing units), digital voice recorders,
pedometers, altimeters,
and other conventional personal data capture devices are generally
manufactured for conditions
that occur in a single or small groupings of activities.
Generally, if the number of activities performed by conventional personal data
capture
devices increases, there is a corresponding rise in design and manufacturing
requirements that
results in significant consumer expense, which eventually becomes prohibitive
to both investment
and commercialization, Further, conventional manufacturing techniques are
often limited and
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ineffective at meeting increased requirements to protect sensitive hardware,
circuitry, and other
components that are susceptible to damage, but which are required to perform
various personal
data capture activities. As a conventional example, sensitive electronic
components such as
printed circuit board assemblies ("PCBA"), sensors, and computer memory
(hereafter "memory")
can be significantly damaged or destroyed during manufacturing processes where
overmoldings
or layering of protective material occurs using techniques such as injection
molding, cold
molding, and others. Damaged or destroyed items subsequently raises the cost
of goods sold and
can deter not only investment and commercialization, but also innovation in
data capture and
analysis technologies, which are highly compelling fields of opportunity.
Thus, what is needed is a solution for data capture devices without the
limitations of
conventional techniques.
BRIEF DESCRIPTION OF THE DRAWINGS
Various embodiments or examples ("examples") are disclosed in the following
detailed
description and the accompanying drawings:
FIG. 1 illustrates an exemplary data-capable strapband system;
FIG. 2A illustrates an exemplary wearable device and platform for sensory
input;
FIG. 2B illustrates an alternative exemplary wearable device and platform for
sensory
input;
FIG. 3 illustrates sensors for use with an exemplary data-capable strapband;
FIG. 4 illustrates an application architecture for an exemplary data-capable
strapband;
FIG. 5A illustrates representative data types for use with an exemplary data-
capable
strapband;
FIG. 5B illustrates representative data types for use with an exemplary data-
capable
strapband in fitness-related activities;
FIG. 5C illustrates representative data types for use with an exemplary data-
capable
strapband in sleep management activities;
FIG. 5D illustrates representative data types for use with an exemplary data-
capable
strapband in medical-related activities;
FIG. 5E illustrates representative data types for use with an exemplary data-
capable
strapband in social media/networking-related activities;
FIG. 6 illustrates a transition between modes of operation of a strapband in
accordance
with various embodiments;
FIG. 7A illustrates a perspective view of an exemplary data-capable strapband;
FIG. 7B illustrates a side view of an exemplary data-capable strapband;
FIG. 7C illustrates another side view of an exemplary data-capable strapband;
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FIG. 7D illustrates a top view of an exemplary data-capable strapband;
FIG, 7E illustrates a bottom view of an exemplary data-capable strapband;
FIG. 7F illustrates a front view of an exemplary data-capable strapband;
FIG. 70 illustrates a rear view of an exemplary data-capable strapband;
FIG. 8A illustrates a perspective view of an exemplary data-capable strapband;
FIG. 8B illustrates a side view of an exemplary data-capable strapband;
FIG. 8C illustrates another side view of an exemplary data-capable strapband;
FIG. 8D illustrates a top view of an exemplary data-capable strapband;
FIG, 8E illustrates a bottom view of an exemplary data-capable strapband;
FIG. 8F illustrates a front view of an exemplary data-capable strapband;
FIG, 80 illustrates a rear view of an exemplary data-capable strapband;
FIG. 9A illustrates a perspective view of an exemplary data-capable strapband;
FIG. 9B illustrates a side view of an exemplary data-capable strapband;
FIG. 9C illustrates another side view of an exemplary data-capable strapband;
FIG. 9D illustrates a top view of an exemplary data-capable strapband;
FIG. 9E illustrates a bottom view of an exemplary data-capable strapband;
FIG. 9F illustrates a front view of an exemplary data-capable strapband;
FIG, 90 illustrates a rear view of an exemplary data-capable strapband;
FIG. 10 illustrates an exemplary computer system suitable for use with a data-
capable
strapband;
FIG. 11 depicts a variety of inputs in a specific example of a strapband, such
as a data-
capable strapband, according to various embodiments;
FIGs. 12A to 12F depict a variety of motion signatures as input into a
strapband, such as a
data-capable strapband, according to various embodiments;
FIG. 13 depicts an inference engine of a strapband configured to detect an
activity and/or a
mode based on monitored motion, according to various embodiments;
FIG. 14 depicts a representative implementation of one or more strapbands and
equivalent
devices, as wearable devices, to form unique motion profiles, according to
various embodiments;
FIG. 15 depicts an example of a motion capture manager configured to capture
motion and
portions thereof, according to various embodiments;
FIG. 16 depicts an example of a motion analyzer configured to evaluate motion-
centric
events, according to various embodiments;
FIG, 17 illustrates action and event processing during a mode of operation in
accordance
with various embodiments;
FIG. 18A illustrates an exemplary wearable device for sensory user interface;
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FIG, 18B illustrates an alternative exemplary wearable device for sensory user
interface;
FIG, 18C illustrates an exemplary switch rod to be used with an exemplary
wearable
device;
FIG. 18D illustrates an exemplary switch for use with an exemplary wearable
device; and
FIG. 18E illustrates an exemplary sensory user interface.
DETAILED DESCRIPTION
Various embodiments or examples may be implemented in numerous ways, including
as a
system, a process, an apparatus, a user interface, or a series of program
instructions on a computer
readable medium such as a computer readable storage medium or a computer
network where the
program instructions are sent over optical, electronic, or wireless
communication links. In
general, operations of disclosed processes may be performed in an arbitrary
order, unless
otherwise provided in the claims.
A detailed description of one or more examples is provided below along with
accompanying figures. The detailed description is provided in connection with
such examples,
but is not limited to any particular example. The scope is limited only by the
claims and
numerous alternatives, modifications, and equivalents are encompassed.
Numerous specific
details are set forth in the following description in order to provide a
thorough understanding.
These details are provided for the purpose of example and the described
techniques may be
practiced according to the claims without some or all of these specific
details. For clarity,
technical material that is known in the technical fields related to the
examples has not been
described in detail to avoid unnecessarily obscuring the description.
FIG. 1 illustrates an exemplary data-capable strapband system. Here, system
100 includes
network 102, strapbands (hereafter "bands") 104-112, server 114, mobile
computing device 115,
mobile communications device 118, computer 120, laptop 122, and distributed
sensor 124.
Although used interchangeably, "strapband" and "band" may be used to refer to
the same or
substantially similar data-capable device that may be worn as a strap or band
around an arm, leg,
ankle, or other bodily appendage or feature. In other examples, bands 104-112
may be attached
directly or indirectly to other items, organic or inorganic, animate, or
static. In still other
examples, bands 104-112 may be used differently.
As described above, bands 104-112 may be implemented as wearable personal data
or data
capture devices (e.g., data-capable devices) that are worn by a user around a
wrist, ankle, arm, ear,
or other appendage, or attached to the body or affixed to clothing. One or
more facilities, sensing
elements, or sensors, both active and passive, may be implemented as part of
bands 104-112 in
order to capture various types of data from different sources. Temperature,
environmental,
temporal, motion, electronic, electrical, chemical, or other types of sensors
(including those
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described below in connection with FIG. 3) may be used in order to gather
varying amounts of
data, which may be configurable by a user, locally (e.g., using user interface
facilities such as
buttons, switches, motion-activated/detected command structures (e.g.,
accelerometer-gathered
data from user-initiated motion of bands 104-112), and others) or remotely
(e.g., entering rules or
parameters in a website or graphical user interface ("GUI") that may be used
to modify control
systems or signals in firmware, circuitry, hardware, and software implemented
(i.e., installed) on
bands 104-112). In some examples, a user interface may be any type of human-
computing
interface (e.g., graphical, visual, audible, haptic, or any other type of
interface that communicates
information to a user (i.e., wearer of bands 104-112) using, for example,
noise, light, vibration, or
other sources of energy and data generation (e.g., pulsing vibrations to
represent various types of
signals or meanings, blinking lights, and the like, without limitation))
implemented locally (i.e.,
on or coupled to one or more of bands 104-112) or remotely (i.e., on a device
other than bands
104-112), In other examples, a wearable device such as bands 104-112 may also
be implemented
as a user interface configured to receive and provide input to or from a user
(i.e., wearer), Bands
104-112 may also be implemented as data-capable devices that are configured
for data
communication using various types of communications infrastructure and media,
as described in
greater detail below. Bands 104-112 may also be wearable, personal, non-
intrusive, lightweight
devices that are configured to gather large amounts of personally relevant
data that can be used to
improve user health, fitness levels, medical conditions, athletic performance,
sleeping physiology,
and physiological conditions, or used as a sensory-based user interface ("UI")
to signal social-
related notifications specifying the state of the user through vibration,
heat, lights or other sensory
based notifications. For example, a social-related notification signal
indicating a user is on-line
can be transmitted to a recipient, who in turn, receives the notification as,
for instance, a vibration.
Using data gathered by bands 104-112, applications may be used to perform
various
analyses and evaluations that can generate information as to a person's
physical (e.g., healthy,
sick, weakened, or other states, or activity level), emotional, or mental
state (e.g., an elevated
body temperature or heart rate may indicate stress, a lowered heart rate and
skin temperature, or
reduced movement (excessive sleeping), may indicate physiological depression
caused by
exertion or other factors, chemical data gathered from evaluating outgassing
from the skin's
surface may be analyzed to determine whether a person's diet is balanced or if
various nutrients
are lacking, salinity detectors may be evaluated to determine if high, lower,
or proper blood sugar
levels are present for diabetes management, and others). Generally, bands 104-
112 may be
configured to gather from sensors locally and remotely. =
As an example, band 104 may capture (i.e,, record, store, communicate (i.e.,
send or
receive), process, or the like) data from various sources (i.e., sensors that
are organic (i.e.,
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installed, integrated, or otherwise implemented with band 104) or distributed
(e.g., microphones
on mobile computing device 115, mobile communications device 118, computer
120, laptop 122,
distributed sensor 124, global positioning system ("GPS") satellites (in low,
mid, or high earth
orbit), or others, without limitation)) and exchange data with one or more of
bands 106-112,
server 114, mobile computing device 115, mobile communications device 118,
computer 120,
laptop 122, and distributed sensor 124. As shown here, a local sensor may be
one that is
incorporated, integrated, or otherwise implemented with bands 104-112. A
remote or distributed
sensor (e.g., mobile computing device 115, mobile communications device 118,
computer 120,
laptop 122, or, generally, distributed sensor 124) may be sensors that can be
accessed, controlled,
or otherwise used by bands 104-112. For example, band 112 may be configured to
control
devices that are also controlled by a given user (e.g., mobile computing
device 115, mobile
communications device 118, computer 120, laptop 122, and distributed sensor
124). For example,
a microphone in mobile communications device 118 may be used to detect, for
example, ambient
audio data that is used to help identify a person's location, or an ear clip
(e.g., a headset as
described below) affixed to an ear may be used to record pulse or blood oxygen
saturation levels.
Additionally, a sensor implemented with a screen on mobile computing device
115 may be used
to read a user's temperature or obtain a biometric signature while a user is
interacting with data.
A further example may include using data that is observed on computer 120 or
laptop 122 that
provides information as to a user's online behavior and the type of content
that she is viewing,
which may be used by bands 104-112. Regardless of the type or location of
sensor used, data
may be transferred to bands 104-112 by using, for example, an analog audio
jack, digital adapter
(e.g., USB, mini-USB), or other, without limitation, plug, or other type of
connector that may be
used to physically couple bands 104-112 to another device or system for
transferring data and, in
some examples, to provide power to recharge a battery (not shown).
Alternatively, a wireless data
communication interface or facility (e.g., a wireless radio that is configured
to communicate data
from bands 104-112 using one or more data communication protocols (e.g., IEEE
802.11a/b/g/n
(WiFi), WiMax, ANTTm, ZigBee , Bluetooth , Near Field Communications ("NFC"),
and
others)) may be used to receive or transfer data. Further, bands 104-112 may
be configured to
analyze, evaluate, modify, or otherwise use data gathered, either directly or
indirectly,
In some examples, bands 104-112 may be configured to share data with each
other or with
an intermediary facility, such as a database, website, web service, or the
like, which may be
implemented by server 114. In some embodiments, server 114 can be operated by
a third party
providing, for example, social media-related services. Bands 104-112 and other
related devices
may exchange data with each other directly, or bands 104-112 may exchange data
via a third party
server, such as a third party like Facebook , to provide social-media related
services. Examples
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of third party servers include servers for social networking services,
including, but not limited to,
services such as Facebook , Yahoo! IMTm, GTalkTm, MSN MessengerTM, Twitter
and other
private or public social networks. The exchanged data may include personal 20
physiological data
and data derived from sensory-based user interfaces ("UI"). Server 114, in
some examples, may
be implemented using one or more processor-based computing devices or
networks, including
computing clouds, storage area networks ("SAN"), or the like. As shown, bands
104-112 may be
used as a personal data or area network (e.g,, "PDN" or "PAN") in which data
relevant to a given
user or band (e.g,, one or more of bands 104-112) may be shared. As shown
here, bands 104 and
112 may be configured to exchange data with each other over network 102 or
indirectly using
server 114. Users of bands 104 and 112 may direct a web browser hosted on a
computer (e.g.,
computer 120, laptop 122, or the like) in order to access, view, modify, or
perform other
operations with data captured by bands 104 and 112. For example, two runners
using bands 104
and 112 may be geographically remote (e.g., users are not geographically in
close proximity
locally such that bands being used by each user are in direct data
communication), but wish to
share data regarding their race times (pre, post, or in-race), personal
records (i.e., "PR"), target
split times, results, performance characteristics (e.g., target heart rate,
target V02 max, and
others), and other information. If both runners (i.e., bands 104 and 112) are
engaged in a race on
the same day, data can be gathered for comparative analysis and other uses.
Further, data can be
shared in substantially real-time (taking into account any latencies incurred
by data transfer rates,
network topologies, or other data network factors) as well as uploaded after a
given activity or
event has been performed. In other words, data can be captured by the user as
it is worn and
configured to transfer data using, for example, a wireless network connection
(e.g., a wireless
network interface card, wireless local area network ("LAN") card, cell phone,
or the like, Data
may also be shared in a temporally asynchronous manner in which a wired data
connection (e.g.,
an analog audio plug (and associated software or firmware) configured to
transfer digitally
encoded data to encoded audio data that may be transferred between bands 104-
112 and a plug
configured to receive, encode/decode, and process data exchanged) may be used
to transfer data
from one or more bands 104-112 to various destinations (e.g., another of bands
104-112, server
114, mobile computing device 115, mobile communications device 118, computer
120, laptop
122, and distributed sensor 124). Bands 104-112 may be implemented with
various types of
wired and/or wireless communication facilities and are not intended to be
limited to any specific
technology. For example, data may be transferred from bands 104-112 using an
analog audio
plug (e.g., TRRS, TRS, or others). In other examples, wireless communication
facilities using
various types of data communication protocols (e.g., WiFi, Bluetooth , ZigBee
, ANTTm, and
others) may be implemented as part of bands 104-112, which may include
circuitry, firmware,
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hardware, radios, antennas, processors, microprocessors, memories, or other
electrical, electronic,
mechanical, or physical elements configured to enable data communication
capabilities of various
types and characteristics.
As data-capable devices, bands 104-112 may be configured to collect data from
a wide
range of sources, including onboard (not shown) and distributed sensors (e.g.,
server 114, mobile
computing device 115, mobile communications device 118, computer 120, laptop
122, and
distributed sensor 124) or other bands, Some or all data captured may be
personal, sensitive, or
confidential and various techniques for providing secure storage and access
may be implemented.
For example, various types of security protocols and algorithms may be used to
encode data
stored or accessed by bands 104-112. Examples of security protocols and
algorithms include
authentication, encryption, encoding, private and public key infrastructure,
passwords,
checksums, hash codes and hash functions (e.g., SHA, SHA-1, MD-5, and the
like), or others may
be used to prevent undesired access to data captured by bands 104-112. In
other examples, data
security for bands 104-112 may be implemented differently.
Bands 104-112 may be used as personal wearable, data capture devices that,
when worn,
are configured to identify a specific, individual user. By evaluating captured
data such as motion
data from an accelerometer, biometric data such as heart rate, skin galvanic
response, and other
biometric data, and using analysis techniques, both long and short-term (e.g.,
software packages
or modules of any type, without limitation), a user may have a unique pattern
of behavior or
motion and/or biometric responses that can be used as a signature for
identification. For example,
bands 104-112 may gather data regarding an individual person's gait or other
unique biometric,
physiological or behavioral characteristics. Using, for example, distributed
sensor 124, a
biometric signature (e.g., fingerprint, retinal or iris vascular pattern, or
others) may be gathered
and transmitted to bands 104-112 that, when combined with other data,
determines that a given
user has been properly identified and, as such, authenticated. When bands 104-
112 are worn, a
user may be identified and authenticated to enable a variety of other
functions such as accessing
or modifying data, enabling wired or wireless data transmission facilities
(i.e., allowing the
transfer of data from bands 104-112), modifying functionality or functions of
bands 104-112,
authenticating financial transactions using stored data and information (e.g.,
credit card, PIN, card
security numbers, and the like), running applications that allow for various
operations to be
performed (e.g., controlling physical security and access by transmitting a
security code to a
reader that, when authenticated, unlocks a door by turning off current to an
electromagnetic lock,
and others), and others. Different functions and operations beyond those
described may be
performed using bands 104-112, which can act as secure, personal, wearable,
data-capable
devices. The number, type, function, configuration, specifications, structure,
or other features of
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system 100 and the above-described elements may be varied and are not limited
to the examples
provided.
FIG. 2A illustrates an exemplary wearable device and platform for sensory
input. Here,
band (i.e., wearable device) 200 includes bus 202, processor 204, memory 206,
vibration source
208, accelerometer 210, sensor 212, battery 214, and communications facility
216. In some
examples, the quantity, type, function, structure, and configuration of band
200 and the elements
(e.g., bus 202, processor 204, memory 206, vibration source 208, accelerometer
210, sensor 212,
battery 214, and communications facility 216) shown may be varied and are not
limited to the
examples provided. As shown, processor 204 may be implemented as logic to
provide control
functions and signals to memory 206, vibration source 208, accelerometer 210,
sensor 212,
battery 214, and communications facility 216. Processor 204 may be implemented
using any type
of processor or microprocessor suitable for packaging within bands 104-112
(FIG, 1), Various
types of microprocessors may be used to provide data processing capabilities
for band 200 and are
not limited to any specific type or capability. For example, a MSP430F5528-
type microprocessor
manufactured by Texas Instruments of Dallas, Texas may be configured for data
communication
using audio tones and enabling the use of an audio plug-and-jack system (e.g.,
TRRS, TRS, or
others) for transferring data captured by band 200. Further, different
processors may be desired if
other functionality (e.g., the type and number of sensors (e.g., sensor 212))
are varied. Data
processed by processor 204 may be stored using, for example, memory 206.
In some examples, memory 206 may be implemented using various types of data
storage
technologies and standards, including, without limitation, read-only memory
("ROM"), random
access memory ("RAM"), dynamic random access memory ("DRAM"), static random
access
memory ("SRAM"), static/dynamic random access memory ("SDRAM"), magnetic
random
access memory ("MRAM"), solid state, two and three-dimensional memories, Flash
, and others,
Memory 206 may also be implemented using one or more partitions that are
configured for
multiple types of data storage technologies to allow for non-modifiable (i.e.,
by a user) software
to be installed (e.g., firmware installed on ROM) while also providing for
storage of captured data
and applications using, for example, RAM. Once captured and/or stored in
memory 206, data
may be subjected to various operations performed by other elements of band
200.
Vibration source 208, in some examples, may be implemented as a motor or other
mechanical structure that functions to provide vibratory energy that is
communicated through
band 200. As an example, an application stored on memory 206 may be configured
to monitor a
clock signal from processor 204 in order to provide timekeeping functions to
band 200. If an
alarm is set for a desired time, vibration source 208 may be used to vibrate
when the desired time
occurs. As another example, vibration source 208 may be coupled to a framework
(not shown) or
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other structure that is used to translate or communicate vibratory energy
throughout the physical
structure of band 200. In other examples, vibration source 208 may be
implemented differently.
Power may be stored in battery 214, which may be implemented as a battery,
battery
module, power management module, or the like, Power may also be gathered from
local power
sources such as solar panels, thermo-electric generators, and kinetic energy
generators, among
others that are alternatives power sources to external power for a battery.
These additional
sources can either power the system directly or can charge a battery, which,
in turn, is used to
power the system (e.g., of a strapband). In other words, battery 214 may
include a rechargeable,
expendable, replaceable, or other type of battery, but also circuitry,
hardware, or software that
may be used in connection with in lieu of processor 204 in order to provide
power management,
charge/recharging, sleep, or other functions. Further, battery 214 may be
implemented using
various types of battery technologies, including Lithium Ion ("LI"), Nickel
Metal Hydride
("NiMH"), or others, without limitation. Power drawn as electrical current may
be distributed
from battery via bus 202, the latter of which may be implemented as deposited
or formed circuitry
or using other forms of circuits or cabling, including flexible circuitry.
Electrical current
distributed from battery 204 and managed by processor 204 may be used by one
or more of
memory 206, vibration source 208, accelerometer 210, sensor 212, or
communications facility
216.
As shown, various sensors may be used as input sources for data captured by
band 200.
For example, accelerometer 210 may be used to detect a motion or other
condition and convert it
to data as measured across one, two, or three axes of motion. In addition to
accelerometer 210,
other sensors (i.e., sensor 212) may be implemented to provide temperature,
environmental,
physical, chemical, electrical, or other types of sensory inputs. As presented
here, sensor 212 may
include one or multiple sensors and is not intended to be limiting as to the
quantity or type of
sensor implemented. Sensory input captured by band 200 using accelerometer 210
and sensor
212 or data requested from another source (i.e., outside of band 200) may also
be converted to
data and exchanged, transferred, or otherwise communicated using
communications facility 216.
As used herein, "facility" refers to any, some, or all of the features and
structures that are used to
implement a given set of functions. For example, communications facility 216
may include a
wireless radio, control circuit or logic, antenna, transceiver, receiver,
transmitter, resistors, diodes,
transistors, or other elements that are used to transmit and receive data from
band 200. In some
examples, communications facility 216 may be implemented to provide a "wired"
data
communication capability such as an analog or digital attachment, plug, jack,
or the like to allow
for data to be transferred. In other examples, communications facility 216 may
be implemented to
provide a wireless data communication capability to transmit digitally encoded
data across one or
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more frequencies using various types of data communication protocols, without
limitation, In still
other examples, band 200 and the above-described elements may be varied in
function, structure,
configuration, or implementation and are not limited to those shown and
described.
FIG. 2B illustrates an alternative exemplary wearable device and platform for
sensory
input. Here, band (i.e., wearable device) 220 includes bus 202, processor 204,
memory 206,
vibration source 208, accelerometer 210, sensor 212, battery 214,
communications facility 216,
switch 222, and light-emitting diode (hereafter "LED") 224. Like-numbered and
named elements
may be implemented similarly in function and structure to those described in
prior examples.
Further, the quantity, type, function, structure, and configuration of band
200 and the elements
(e.g., bus 202, processor 204, memory 206, vibration source 208, accelerometer
210, sensor 212,
battery 214, and communications facility 216) shown may be varied and are not
limited to the
examples provided.
In some examples, band 200 may be implemented as an alternative structure to
band 200
(FIG, 2A) described above. For example, sensor 212 may be configured to sense,
detect, gather,
or otherwise receive input (i.e., sensed physical, chemical, biological,
physiological, or
psychological quantities) that, once received, may be converted into data and
transferred to
processor 204 using bus 202. As an example, temperature, heart rate,
respiration rate, galvanic
skin response (i.e., skin conductance response), muscle stiffness/fatigue, and
other types of
conditions or parameters may be measured using sensor 212, which may be
implemented using
one or multiple sensors, Further, sensor 212 is generally coupled (directly or
indirectly) to band
220. As used herein, "coupled" may refer to a sensor being locally implemented
on band 220 or
remotely on, for example, another device that is in data communication with
it.
Sensor 212 may be configured, in some examples, to sense various types of
environmental
(e.g., ambient air temperature, barometric pressure, location (e.g., using GPS
or other satellite
constellations for calculating Cartesian or other coordinates on the earth's
surface, micro-cell
network triangulation, or others), physical, physiological, psychological, or
activity-based
conditions in order to determine a state of a user of wearable device 220
(i.e., band 220). In other
examples, applications or firmware may be downloaded that, when installed, may
be configured
to change sensor 212 in terms of function, Sensory input to sensor 212 may be
used for various
purposes such as measuring caloric burn rate, providing active (e.g.,
generating an alert such as
vibration, audible, or visual indicator) or inactive (e.g,, providing
information, content,
promotions, advertisements, or the like on a website, mobile website, or other
location that is
accessible using an account that is associated with a user and band 220)
feedback, measuring
fatigue (e.g,, by calculating skin conductance response (hereafter "SCR")
using sensor 212 or
accelerometer 210) or other physical states, determining a mood of a user, and
others, without
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limitation. As used herein, feedback may be provided using a mechanism (i.e.,
feedback
mechanism) that is configured to provide an alert or other indicator to a
user. Various types of
feedback mechanisms may be used, including a vibratory source, motor, light
source (e.g.,
pulsating, blinking, or steady illumination), light emitting diode (e.g., LED
224), audible, audio,
visual, haptic, or others, without limitation. Feedback mechanisms may provide
sensory output of
the types indicated above via band 200 or, in other examples, using other
devices that may be in
data communication with it. For example, a driver may receive a vibratory
alert from vibration
source (e.g., motor) 208 when sensor 212 detects skin tautness (using, for
example, accelerometer
to detect muscle stiffness) that indicates she is falling asleep and, in
connection with a GPS-
sensed signal, wearable device 220 determines that a vehicle is approaching a
divider,
intersection, obstacle, or is accelerating/decelerating rapidly, and the like.
Further, an audible
indicator may be generated and sent to an ear-worn communication device such
as a Bluetooth
(or other data communication protocol, near or far field) headset. Other types
of devices that have
a data connection with wearable device 220 may also be used to provide sensory
output to a user,
such as using a mobile communications or computing device having a graphical
user interface to
display data or information associated with sensory input received by sensor
212.
In some examples, sensory output may be an audible tone, visual indication,
vibration, or
other indicator that can be provided by another device that is in data
communication with band
220. In other examples, sensory output may be a media file such as a song that
is played when
sensor 212 detects a given parameter. For example, if a user is running and
sensor 212 detects a
heart rate that is lower than the recorded heart rate as measured against 65
previous runs,
processor 204 may be configured to generate a control signal to an audio
device that begins
playing an upbeat or high tempo song to the user in order to increase her
heart rate and activity- .
based performance. As another example, sensor 212 and/or accelerometer 210 may
sense various
inputs that can be measured against a calculated "lifeline" (e.g., LIFELINETM)
that is an abstract
representation of a user's health or wellness. If sensory input to sensor 212
(or accelerometer 210
or any other sensor implemented with band 220) is received, it may be compared
to the user's
lifeline or abstract representation (hereafter "representation") in order to
determine whether
feedback, if any, should be provided in order to modify the user's behavior. A
user may input a
range of tolerance (i.e., a range within which an alert is not generated) or
processor 204 may
determine a range of tolerance to be stored in memory 206 with regard to
various sensory input.
For example, if sensor 212 is configured to measure internal bodily
temperature, a user may set a
0.1 degree Fahrenheit range of tolerance to allow her body temperature to
fluctuate between 98.5
and 98.7 degrees Fahrenheit before an alert is generated (e.g., to avoid heat
stress, heat
exhaustion, heat stroke, or the like). Sensor 212 may also be implemented as
multiple sensors that
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are disposed (i.e., positioned) on opposite sides of band 220 such that, when
worn on a wrist or
other bodily appendage, allows for the measurement of skin conductivity in
order to determine
skin conductance response. Skin conductivity may be used to measure various
types of
parameters and conditions such as cognitive effort, arousal, lying, stress,
physical fatigue due to
poor sleep quality, emotional responses to various stimuli, and others.
Activity-based feedback may be given along with state-based feedback. In some
examples, band 220 may be configured to provide feedback to a user in order to
help him achieve
a desired level of fitness, athletic performance, health, or wellness. in
addition to feedback, band
220 may also be configured to provide indicators of use to a wearer during,
before, or after a
given activity or state.
As used herein, various types of indicators (e.g,, audible, visual,
mechanical, or the like)
may also be used in order to provide a sensory user interface. In other words,
band 220 may be
configured with switch 222 that can be implemented using various types of
structures as
indicators of device state, function, operation, mode, or other conditions or
characteristics.
Examples of indicators include "wheel" or rotating structures such as dials or
buttons that, when
turned to a given position, indicate a particular function, mode, or state of
band 220. Other
structures may include single or multiple-position switches that, when turned
to a given position,
are also configured for the user to visually recognize a function, mode, or
state of band 220. For
example, a 4-position switch or button may indicate "on," "off," standby,"
"active," "inactive," or
other mode. A 2-position switch or button may also indicate other modes of
operation such as
"on" and "off." As yet another example, a single switch or button may be
provided such that,
when the switch or button is depressed, band 220 changes mode or function
without, alternatively,
providing a visual indication. In other examples, different types of buttons,
switches, or other
user interfaces may be provided and are not limited to the examples shown.
FIG. 3 illustrates sensors for use with an exemplary data-capable strapband.
Sensor 212
may be implemented using various types of sensors, some of which are shown.
Like-numbered
and named elements may describe the same or substantially similar element as
those shown in
other descriptions. Here, sensor 212 (FIG. 2) may be implemented as
accelerometer 302,
altimeter/barometer 304, light/infrared ("IR") sensor 306, pulse/heart rate
("HR") monitor 308,
audio sensor (e.g., microphone, transducer, or others) 310, pedometer 312,
velocimeter 314, UPS
receiver 316, location-based service sensor (e.g., sensor for determining
location within a cellular
or micro-cellular network, which may or may not use UPS or other satellite
constellations for
fixing a position) 318, motion detection sensor 320, environmental sensor 322,
chemical sensor
324, electrical sensor 326, or mechanical sensor 328.
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As shown, accelerometer 302 may be used to capture data associated with motion
detection along 1, 2, or 3-axes of measurement, without limitation to any
specific type of
specification of sensor. Accelerometer 302 may also be implemented to measure
various types of
user motion and may be configured based on the type of sensor, firmware,
software, hardware, or
circuitry used. As another example, altimeter/barometer 304 may be used to
measure
environment pressure, atmospheric or otherwise, and is not limited to any
specification or type of
pressure-reading device. In some examples, altimeter/barometer 304 may be an
altimeter, a
barometer, or a combination thereof. For example, altimeter/barometer 304 may
be implemented
as an altimeter for measuring above ground level ("AGL") pressure in band 200,
which has been
configured for use by naval or military aviators. As another example,
altimeter/barometer 304
may be implemented as a barometer for reading atmospheric pressure for marine-
based
applications. In other examples, altimeter/barometer 304 may be implemented
differently.
Other types of sensors that may be used to measure light or photonic
conditions include
light/IR sensor 306, motion detection sensor 320, and environmental sensor
322, the latter of
which may include any type of sensor for capturing data associated with
environmental conditions
beyond light. Further, motion detection sensor 320 may be configured to detect
motion using a
variety of techniques and technologies, including, but not limited to
comparative or differential
light analysis (e.g., comparing foreground and background lighting), sound
monitoring, or others.
Audio sensor 310 may be implemented using any type of device configured to
record or capture
sound.
In some examples, pedometer 312 may be implemented using devices to measure
various
types of data associated with pedestrian-oriented activities such as running
or walking.
Footstrikes, stride length, stride length or interval, time, and other data
may be measured.
Velocimeter 314 may be implemented, in some examples, to measure velocity
(e.g., speed and
directional vectors) without limitation to any particular activity. Further,
additional sensors that
may be used as sensor 212 include those configured to identify or obtain
location-based data, For
example, UPS receiver 316 may be used to obtain coordinates of the geographic
location of band
200 using, for example, various types of signals transmitted by civilian
and/or military satellite
constellations in low, medium, or high earth orbit (e.g., "LEO," "MEO," or
"GEO"). In other
examples, differential UPS algorithms may also be implemented with UPS
receiver 316, which
may be used to generate more precise or accurate coordinates. Still further,
location-based
services sensor 318 may be implemented to obtain location-based data
including, but not limited
to location, nearby services or items of interest, and the like. As an
example, location-based
services sensor 318 may be configured to detect an electronic signal, encoded
or otherwise, that
provides information regarding a physical locale as band 200 passes. The
electronic signal may
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include, in some examples, encoded data regarding the location and information
associated
therewith. Electrical sensor 326 and mechanical sensor 328 may be configured
to include other
types (e.g., haptic, kinetic, piezoelectric, piezomechanical, pressure, touch,
thermal, and others) of
sensors for data input to band 200, without limitation. Other types of sensors
apart from those
shown may also be used, including magnetic flux sensors such as solid-state
compasses and the
like. The sensors can also include gyroscopic sensors. While the present
illustration provides
numerous examples of types of sensors that may be used with band 200 (FIG, 2),
others not
shown or described may be implemented with or as a substitute for any sensor
shown or
described.
FIG. 4 illustrates an application architecture for an exemplary data-capable
strapband.
Here, application architecture 400 includes bus 402, logic module 404,
communications module
406, security module 408, interface module 410, data management 412, audio
module 414, motor
controller 416, service management module 418, sensor input evaluation module
420, and power
management module 422. In some examples, application architecture 400 and the
above-listed
elements (e.g., bus 402, logic module 404, communications module 406, security
module 408,
interface module 410, data management 412, audio module 414, motor controller
416, service
management module 418, sensor input evaluation module 420, and power
management module
422) may be implemented as software using various computer programming and
formatting
languages such as Java, C++, C, and others, As shown here, logic module 404
may be firmware
or application software that is installed in memory 206 (FIG. 2) and executed
by processor 204
(FIG. 2). Included with logic module 404 may be program instructions or code
(e.g., source,
object, binary executables, or others) that, when initiated, called, or
instantiated, perform various
functions.
For example, logic module 404 may be configured to send control signals to
communications module 406 in order to transfer, transmit, or receive data
stored in memory 206,
the latter of which may be managed by a database management system ("DBMS") or
utility in
data management module 412. As another example, security module 408 may be
controlled by
logic module 404 to provide encoding, decoding, encryption, authentication, or
other functions to
band 200 (FIG. 2). Alternatively, security module 408 may also be implemented
as an application
that, using data captured from various sensors and stored in memory 206 (and
accessed by data
management module 412) may be used to provide identification functions that
enable band 200 to
passively identify a user or wearer of band 200. Still further, various types
of security software
and applications may be used and are not limited to those shown and described.
Interface module 410, in some examples, may be used to manage user interface
controls
such as switches, buttons, or other types of controls that enable a user to
manage various functions
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of band 200. For example, a 4-position switch may be turned to a given
position that is
interpreted by interface module 410 to determine the proper signal or feedback
to send to logic
module 404 in order to generate a particular result. In other examples, a
button (not shown) may
be depressed that allows a user to trigger or initiate certain actions by
sending another signal to
logic module 404. Still further, interface module 410 may be used to interpret
data from, for
example, accelerometer 210 (FIG. 2) to identify specific movement or motion
that initiates or
triggers a given response. In other examples, interface module 410 may be used
to manage
different types of displays (e.g., light-emitting diodes (LEDs),
interferometric modulator display
(IMOD), electrophoretic ink (E Ink), organic light-emitting diode (OLED),
etc.). In other
examples, interface module 410 may be implemented differently in function;
structure, or
configuration and is not limited to those shown and described.
As shown, audio module 414 may be configured to manage encoded or unencoded
data
gathered from various types of audio sensors. In some examples, audio module
414 may include
one or more codecs that are used to encode or decode various types of audio
waveforms. For
example, analog audio input may be encoded by audio module 414 and, once
encoded, sent as a
signal or collection of data packets, messages, segments, frames, or the like
to logic module 404
for transmission via communications module 406. In other examples, audio
module 414 may be
implemented differently in function, structure, configuration, or
implementation and is not limited
to those shown and described. Other elements that may be used by band 200
include motor
controller 416, which may be firmware or an application to control a motor or
other vibratory
energy source (e.g,, vibration source 208 (FIG: 2)). Power used for band 200
may be drawn from
battery 214 (FIG. 2) and managed by power management module 422, which may be
firmware or
an application used to manage, with or without user input, how power is
consumer, conserved, or
otherwise used by band 200 and the above-described elements, including one or
more sensors
(e.g., sensor 212 (FIG. 2), sensors 302-328 (FIG. 3)). With regard to data
captured, sensor input
evaluation module 420 may be a software engine or module that is used to
evaluate and analyze
data received from one or more inputs (e.g., sensors 302-328) to band 200.
When received, data
may be analyzed by sensor input evaluation module 420, which may include
custom or "off-the-
shelf' analytics packages that are configured to provide application-specific
analysis of data to
determine trends, patterns, and other useful information. In other examples,
sensor input module
420 may also include firmware or software that enables the generation of
various types and
formats of reports for presenting data and any analysis performed thereupon.
Another element of application architecture 400 that may be included is
service
management module 418. In some examples, service management module 418 may be
firmware,
software, or an application that is configured to manage various aspects and
operations associated
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with executing software-related instructions for band 200, For example,
libraries or classes that
are used by software or applications on band 200 ma)' be served from an online
or networked
source. Service management module 418 may be implemented to manage how and
when these
services are invoked in order to ensure that desired applications are executed
properly within
application architecture 400. As discrete sets, collections, or groupings of
functions, services used
by band 200 for various purposes ranging from communications to operating
systems to call or
document libraries may be managed by service management module 418.
Alternatively, service
management module 418 may be implemented differently and is not limited to the
examples
provided herein. Further, application architecture 400 is an example of a
software/system/application-level architecture that may be used to implement
various software-
related aspects of band 200 and may be varied in the quantity, type,
configuration, function,
structure, or type of programming or formatting languages used, without
limitation to any given
example.
FIG. 5A illustrates representative data types for use with an exemplary data-
capable
strapband. Here, wearable device 502 may capture various types of data,
including, but not
limited to sensor data 504, manually-entered data 506, application data 508,
location data 510,
network data 512, system/operating data 514, and user data 516. Various types
of data may be
captured from sensors, such as those described above in connection with FIG.
3. Manually-
entered data, in some examples, may be data or inputs received directly and
locally by band 200
(FIG, 2). In other examples, manually-entered data may also be provided
through a third-party
website that stores the data in a database and may be synchronized from server
114 (FIG. 1) with
one or more of bands 104-112. Other types of data that may be captured
including application
data 508 and system/operating data 514, which may be associated with firmware,
software, or
hardware installed or implemented on band 200. Further, location data 510 may
be used by
wearable device 502, as described above. User data 516, in some examples, may
be data that
inClude profile data, preferences, rules, or other information that has been
previously entered by a
given user of wearable device 502. Further, network data 512 may be data is
captured by
wearable device with regard to routing tables, data paths, network or access
availability (e.g.,
wireless network access availability), and the like. Other types of data may
be captured by
wearable device 502 and are not limited to the examples shown and described,
Additional
context-specific examples of types of data captured by bands 104-112 (FIG, 1)
are provided
below.
FIG. 5B illustrates representative data types for use with an exemplary data-
capable
strapband in fitness-related activities. Here, band 519 may be configured to
capture types (i.e.,
categories) of data such as heart rate/pulse monitoring data 520, blood oxygen
saturation data 522,
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skin temperature data 524, salinity/emission/outgassing data 526, location/GPS
data 528,
environmental data 530, and accelerometer data 532. As an example, a runner
may use or wear
band 519 to obtain data associated with his physiological condition (i.e.,
heart rate/pulse
monitoring data 520, skin temperature, salinity/emission/outgassing data 526,
among others),
athletic efficiency (i.e., blood oxygen saturation data 522), and performance
(i.e,, location/GPS
data 528 (e.g., distance or laps run), environmental data 530 (e.g., ambient
temperature, humidity,
pressure, and the like), accelerometer 532 (e.g., biomechanical information,
including gait, stride,
stride length, among others)). Other or different types of data may be
captured by band 519, but
the above-described examples are illustrative of some types of data that may
be captured by band
519. Further, data captured may be uploaded to a website or online/networked
destination for
storage and other uses. For example, fitness-related data may be used by
applications that are
downloaded from a "fitness marketplace" where athletes may find, purchase, or
download
applications for various uses. Some applications may be activity-specific and
thus may be used to
modify or alter the data capture capabilities of band 519 accordingly. For
example, a fitness
marketplace may be a website accessible by various types of mobile and non-
mobile clients to
locate applications for different exercise or fitness categories such as
running, swimming, tennis,
golf; baseball, football, fencing, and many others. When downloaded, a fitness
marketplace may
also be used with user-specific accounts to manage the retrieved applications
as well as usage
with band 519, or to use the data to provide services such as online personal
coaching or targeted
advertisements. More, fewer, or different types of data may be captured for
fitness-related
activities.
FIG. 5C illustrates representative data types for use with an exemplary data-
capable
strapband in sleep management activities. Here, band 539 may be used for sleep
management
purposes to track various types of data, including heart rate monitoring data
540, motion sensor
data 542, accelerometer data 544, skin resistivity data 546, user input data
548, clock data 550,
and audio data 552. In some examples, heart rate monitor data 540 may be
captured to evaluate
rest, waking, or various states of sleep. Motion sensor data 542 and
accelerometer data 544 may
be used to determine whether a user of band 539 is experiencing a restful or
fitful sleep. For
example, some motion sensor data 542 may be captured by a light sensor that
measures ambient
or differential light patterns in order to determine whether a user is
sleeping on her front, side, or
back, Accelerometer data 544 may also be captured to determine whether a user
is experiencing
gentle or violent disruptions when sleeping, such as those often found in
afflictions of sleep apnea
or other sleep disorders. Further, skin resistivity data 546 may be captured
to determine whether a
user is ill (e.g., running a temperature, sweating, experiencing chills,
clammy skin, and others).
Still further, user input data may include data input by a user as to how and
whether band 539
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should trigger vibration source 208 (FIG, 2) to wake a user at a given time or
whether to use a
series of increasing or decreasing vibrations to trigger a waking state. Clock
data (550) may be
used to measure the duration of sleep or a finite period of time in which a
user is at rest. Audio
data may also be captured to determine whether a user is snoring and, if so,
the frequencies and
amplitude therein may suggest physical conditions that a user may be
interested in knowing (e.g.,
snoring, breathing interruptions, talking in one's sleep, and the like). More,
fewer, or different
types of data may be captured for sleep management-related activities.
FIG. 5D illustrates representative data types for use with an exemplary data-
capable
strapband in medical-related activities. Here, band 539 may also be configured
for medical
purposes and related-types of data such as heart rate monitoring data 560,
respiratory monitoring
data 562, body temperature data 564, blood sugar data 566, chemical
protein/analysis data 568,
patient medical records data 570, and healthcare professional (e.g., doctor,
physician, registered
nurse, physician's assistant, dentist, orthopedist, surgeon, and others) data
572. In some
examples, data may be captured by band 539 directly from wear by a user, For
example, band
539 may be able to sample and analyze sweat through a salinity or moisture
detector to identify
whether any particular chemicals, proteins, hormones, or other organic or
inorganic compounds
are present, which can be analyzed by band 539 or communicated to server 114
to perform further
analysis. If sent to server 114, further analyses may be performed by a
hospital or other medical
facility using data captured by band 539. In other examples, more, fewer, or
different types of
data may be captured for medical-related activities.
FIG. 5E illustrates representative data types for use with an exemplary data-
capable
strapband in social media/networking-related activities. Examples of social
media/networking-
related activities include related to Internet-based Social Networking 15
Services ("SNS"), such
as Facebook , Twitter , etc. Here, band 519, shown with an audio data plug,
may be configured
to capture data for use with various types of social media and networking-
related services,
websites, and activities. Accelerometer data 580, manual data 582, other
user/friends data 584,
location data 586, network data 588, clock/timer data 590, and environmental
data 592 are
examples of data that may be gathered and shared by, for example, uploading
data from band 519
using, for example, an audio plug such as those described herein, As another
example,
accelerometer data 580 may be captured and shared with other users to share
motion, activity, or
other movement-oriented data. Manual data 582 may be data that a given user
also wishes to
share with other users. Likewise, other user/friends data 584 may be from
other bands (not
shown) that can be shared or aggregated with data captured by band 519.
Location data 586 for
band 519 may also be shared with other users, In other examples, a user may
also enter manual
data 582 to prevent other users or friends from receiving updated location
data from band 519.
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Additionally, network data 588 and clock/timer data may be captured and shared
with other users
to indicate, for example, activities or events that a given user (i.e.,
wearing band 519) was
engaged at certain locations. Further, if a user of band 519 has friends who
are not geographically
located in close or near proximity (e.g., the user of band 519 is located in
San Francisco and her
friend is located in Rome), environmental data can be captured by band 519
(e.g., weather,
temperature, humidity, sunny or overcast (as interpreted from data captured by
a light sensor and
combined with captured data for humidity and temperature), among others). In
other examples,
more, fewer, or different types of data may be captured for medical-related
activities,
FIG. 6 illustrates a transition between modes of operation for a strapband in
accordance
with various embodiments. A strapband can transition between modes by either
entering a mode
at 602 or exiting a mode at 660. The flow to enter a mode begins at 602 and
flows downward,
whereas the flow to exit the mode begins at 660 and flows upward. A mode can
be entered and
exited explicitly 603 or entered and exited implicitly 605, In particular, a
user can indicate
explicitly whether to enter or exit a mode of operation by using inputs 620.
Examples of inputs
620 include a switch with one or more positions that are each associated with
a selectable mode,
and a display I/O 624 that can be touch-sensitive for entering commands
explicitly to enter or exit
a mode. Note that entry of a second mode of operation can extinguish
implicitly the first mode of
operation. Further, a user can explicitly indicate whether to enter or exit a
mode of operation by
using motion signatures 610. That is, the motion of the strapband can
facilitate transitions
between modes of operation. A motion signature is a set of motions or patterns
of motion that the
strapband can detect using the logic of the strapband, whereby the logic can
infer a mode from the
motion signature. Examples of motion signatures are discussed below in FIG.
11. A set of
motions can be predetermined, and then can be associated with a command to
enter or exit a
mode. Thus, motion can select a mode of operation. In some embodiments, modes
of operation
include a "normal" mode, an "active mode," a "sleep mode" or "resting mode,"),
among other
types of modes. A normal mode includes usual or normative amount of
activities, whereas, an
"active mode" typically includes relatively large amounts of activity. Active
mode can include
activities, such as running and swimming, for example. A "sleep mode" or
"resting mode"
typically includes a relatively low amount of activity that is indicative of
sleeping or resting can
be indicative of the user sleeping.
A mode can be entered and exited implicitly 605. In particular, a strapband
and its logic
can determine whether to enter or exit a mode of operation by inferring either
an activity or a
mode at 630. An inferred mode of operation can be determined as a function of
user
characteristics 632, such as determined by user-relevant sensors (e.g., heart
rate, body
temperature, etc.). An inferred mode of operation can be determined using
motion matching 634
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(e.g., motion is analyzed and a type of activity is determined). Further, an
inferred mode of
operation can be determined by examining environmental factors 636 (e.g.,
ambient temperature,
time, ambient light, etc.). To illustrate, consider that: (1.) user
characteristics 632 specify that the
user's heart rate is at a resting rate and the body temperature falls
(indicative of resting or
sleeping), (2.) motion matching 634 determines that the user has a relatively
low level of activity,
and (3.) environment factors 636 indicate that the time is 3:00 am and the
ambient light is
negligible. In view of the foregoing, an inference engine or other logic of
the strapband likely can
infer that the user is sleeping and then operate to transition the strapband
into sleep mode. In this
mode, power may be reduced, Note that while a mode may transition either
explicitly or
implicitly, it need not exit the same way.
FIG. 7A illustrates a perspective view of an exemplary data-capable strapband
configured
to receive overmolding. Here, band 700 includes framework 702, covering 704,
flexible circuit
706, covering 708, motor 710, coverings 714-724, plug 726, accessory 728,
control housing 734,
control 736, and flexible circuits 737-738. In some examples, band 700 is
shown with various
elements (i.e., covering 704, flexible circuit 706, covering 708, motor 710,
coverings 714-724,
plug 726, accessory 728, control housing 734, control 736, and flexible
circuits 737-738) coupled
to framework 702. Coverings 708, 714-724 and control housing 734 may be
configured to protect
various types of elements, which may be electrical, electronic, mechanical,
structural, or of
another type, without limitation. For example, covering 708 may be used to
protect a battery and
power management module from protective material formed around band 700 during
an injection
molding operation. As another example, housing 704 may be used to protect a
printed circuit
board assembly ("PCBA") from similar damage. Further, control housing 734 may
be used to
protect various types of user interfaces (e.g., switches, buttons (e.g.,
control 736), lights, light-
emitting diodes, or other control features and functionality) from damage. In
other examples, the
elements shown may be varied in quantity, type, manufacturer, specification,
function, structure,
or other aspects in order to provide data capture, communication, analysis,
usage, and other
capabilities to band 700, which may be worn by a user around a wrist, arm,
leg, ankle, neck or
other protrusion or aperture, without restriction. Band 700, in some examples,
illustrates an initial
unlayered device that may be protected using the techniques for protective
overmolding as
described above. Alternatively, the number, type, function, configuration,
ornamental
appearance, or other aspects shown may be varied without limitation.
FIG. 7B illustrates a side view of an exemplary data-capable strapband. Here,
band 740
includes framework 702, covering 704, flexible circuit 706, covering 708,
motor 710, battery 712,
coverings 714-724, plug 726, accessory 728, button/switch/LED/LCD Display 730-
732, control
housing 734, control 736, and flexible circuits 737-738 and is shown as a side
view of band 700.
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In other examples, the number, type, function, configuration, ornamental
appearance, or other
aspects shown may be varied without limitation.
FIG. 7C illustrates another side view of an exemplary data-capable strapband.
Here, band
750 includes framework 702, covering 704, flexible circuit 706, covering 708,
motor 710, battery
712, coverings 714-724, accessory 728, button/switch/LED/LCD Display 730-732,
control
housing 734, control 736, and flexible circuits 737-738 and is shown as an
opposite side view of
band 740. In some examples, button/switch/LED/LCD Display 730-732 may be
implemented
using different types of switches, including multiple position switches that
may be manually
turned to indicate a given function or command. Further, underlighting
provided by light emitting
diodes ("LED") or other types of low power lights or lighting systems may be
used to provide a
visual status for band 750. In other examples, the number, type, function,
configuration,
ornamental appearance, or other aspects shown may be varied without
limitation.
FIG. 7D illustrates a top view of an exemplary data-capable strapband. Here,
band 760
includes framework 702, coverings 714-716 and 722-724, plug 726, accessory
728, control
housing 734, control 736, flexible circuits 737-738, and PCBA 762. In other
examples, the
number, type, function, configuration, ornamental appearance, or other aspects
shown may be
varied without limitation,
FIG. 7E illustrates a bottom view of an exemplary data-capable strapband.
Here, band 770
includes framework 702, covering 704, flexible circuit 706, covering 708,
motor 710, coverings
714-720, plug 726, accessory 728, control housing 734, control 736, and PCBA
772. In some
examples, PCBA 772 may be implemented as any type of electrical or electronic
circuit board
element or component, without restriction. In other examples, the number,
type, function,
configuration, ornamental appearance, or other aspects shown may be varied
without limitation.
FIG. 7F illustrates a front view of an exemplary data-capable strapband. Here,
band 780
includes framework 702, flexible circuit 706, covering 708, motor 710,
coverings 714-718 and
722, accessory 728, button/switch/LED/LCD Display 730, control housing 734,
control 736, and
flexible circuit 737. In some examples, button/switch/LED/LCD Display 730 may
be
implemented using various types of displays including liquid crystal (LCD),
thin film, active
matrix, and others, without limitation. In other examples, the number, type,
function,
configuration, ornamental appearance, or other aspects shown may be varied
without limitation.
FIG, 7G illustrates a rear view of an exemplary data-capable strapband. Here,
band 790
includes framework 702, covering 708, motor 710, coverings 714-722, analog
audio plug 726,
accessory 728, control 736, and flexible circuit 737, In some examples,
control 736 may be a
button configured for depression in order to activate or initiate other
functionality of band 790. In
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other examples, the number, type, function, configuration, ornamental
appearance, or other
aspects shown may be varied without limitation.
FIG. 8A illustrates a perspective of an exemplary data-capable strapband
having a first
molding. Here, an alternative band (i.e., band 800) includes molding 802,
analog audio TRRS-
type plug (hereafter "plug") 804, plug housing 806, button 808, framework 810,
control housing
812, and indicator light 814. In some examples, a first protective overmolding
(i.e., molding 802)
has been applied over band 700 (FIG. 7) and the above-described elements
(e.g., covering 704,
flexible circuit 706, covering 708, motor 710, coverings 714-724, plug 726,
accessory 728,
control housing 734, control 736, and flexible circuit 738) leaving some
elements partially
exposed (e.g., plug 804, plug housing 806, button 808, framework 810, control
housing 812, and
indicator light 814). However, internal PCBAs, flexible connectors, circuitry,
and other sensitive
elements have been protectively covered with a first or inner molding that can
be configured to
further protect band 800 from subsequent moldings formed over band 800 using
the above-
described techniques. In other examples, the type, configuration, location,
shape, design, layout,
or other aspects of band 800 may be varied and are not limited to those shown
and described, For
example, TRRS plug 804 may be removed if a wireless communication facility is
instead attached
to framework 810, thus having a transceiver, logic, and antenna instead being
protected by
molding 802. As another example, button 808 may be removed and replaced by
another control
mechanism (e.g,, an accelerometer that provides motion data to a processor
that, using firmware
and/or an application, can identify and resolve different types of motion that
band 800 is
undergoing), thus enabling molding 802 to be extended more fully, if not
completely, over band
800. In other examples, the number, type, function, configuration, ornamental
appearance, or
other aspects shown may be varied without limitation.
FIG. 8B illustrates a side view of an exemplary data-capable strapband. Here,
band
820 includes molding 802, plug 804, plug housing 806, button 808, control
housing 812, and
indicator lights 814 and 822. In other examples, the number, type, function,
configuration,
ornamental appearance, or other aspects shown may be varied without
limitation,
FIG, 8C illustrates another side view of an exemplary data-capable strapband.
Here,
band 825 includes molding 802, plug 804, button 808, framework 810, control
housing 812, and
indicator lights 814 and 822. The view shown is an opposite view of that
presented in FIG, 8B.
In other examples, the number, type, function, configuration, ornamental
appearance, or other
aspects shown may be varied without limitation.
FIG. 8D illustrates a top view of an exemplary data-capable strapband. Here,
band
830 includes molding 802, plug 804, plug housing 806, button 808, control
housing 812, and
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indicator lights 814 and 822, In other examples, the number, type, function,
configuration,
ornamental appearance, or other aspects shown may be varied without
limitation.
FIG. 8E illustrates a bottom view of an exemplary data-capable strapband.
Here, band
840 includes molding 802, plug 804, plug housing 806, button 808, control
housing 812, and
indicator lights 814 and 822. In other examples, the number, type, function,
configuration,
ornamental appearance, or other aspects shown may be varied without
limitation.
FIG, 8F illustrates a front view of an exemplary data-capable strapband. Here,
band
850 includes molding 802, plug 804, plug housing 806, button 808, control
housing 812, and
indicator light 814. In other examples, the number, type, function,
configuration, ornamental
appearance, or other aspects shown may be varied without limitation.
FIG. 8G illustrates a rear view of an exemplary data-capable strapband. Here,
band 860
includes molding 802 and button 808. In other examples, the number, type,
function,
configuration, ornamental appearance, or other aspects shown may be varied
without limitation.
FIG. 9A illustrates a perspective view of an exemplary data-capable strapband
having a
second molding. Here, band 900 includes molding 902, plug 904, and button 906.
As shown
another overmolding or protective material has been formed by injection
molding, for example,
molding 902 over band 900. As another molding or covering layer, molding 902
may also be
configured to receive surface designs, raised textures, or patterns, which may
be used to add to the
commercial appeal of band 900. In some examples, band 900 may be illustrative
of a finished
data-capable strapband (i.e., band 700 (FIG. 7), 800 (FIG. 8) or 900) that may
be configured to
provide a wide range of electrical, electronic, mechanical, structural,
photonic, or other
capabilities.
Here, band 900 may be configured to perform data communication with one or
more other
data-capable devices (e.g., other bands, computers, networked computers,
clients, servers, peers,
and the like) using wired or wireless features. For example, plug 900 may be
used, in connection
with firmware and software that allow for the transmission of audio tones to
send or receive
encoded data, which may be performed using a variety of encoded waveforms and
protocols,
without limitation. In other examples, plug 904 may be removed and instead
replaced with a
wireless communication facility that is protected by molding 902. If using a
wireless
communication facility and protocol, band 900 may communicate with other data-
capable devices
such as cell phones, smart phones, computers (e.g., desktop, laptop, notebook,
tablet, and the
like), computing networks and clouds, and other types of data-capable devices,
without limitation,
In still other examples, band 900 and the elements described above in
connection with FIGs. 1-9,
may be varied in type, configuration, function, structure, or other aspects,
without limitation to
any of the examples shown and described.
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FIG, 9B illustrates a side view of an exemplary data-capable strapband. Here,
band 910
includes molding 902, plug 904, and button 906, In other examples, the number,
type, function,
configuration, ornamental appearance, or other aspects shown may be varied
without limitation.
FIG. 9C illustrates another side view of an exemplary data-capable strapband.
Here, band
920 includes molding 902 and button 906. In other examples, the number, type,
function,
configuration, ornamental appearance, or other aspects shown may be varied
without limitation.
FIG. 9D illustrates a top view of an exemplary data-capable strapband. Here,
band 930
includes molding 902, plug 904, button 906, and textures 932-934. In some
examples, textures
932-934 may be applied to the external surface of molding 902. As an example,
textured surfaces
may be molded into the exterior surface of molding 902 to aid with handling or
to provide
ornamental or aesthetic designs. The type, shape, and repetitive nature of
textures 932-934 are
not limiting and designs may be either two or three-dimensional relative to
the planar surface of
molding 902. In other examples, the number, type, function, configuration,
ornamental
appearance, or other aspects shown may be varied without limitation.
FIG. 9E illustrates a bottom view of an exemplary data-capable strapband.
Here, band 940
includes molding 902 and textures 932-934, as described above. In other
examples, the number,
type, function, configuration, ornamental appearance, or other aspects shown
may be varied
without limitation,
FIG. 9F illustrates a front view of an exemplary data-capable strapband. Here,
band 950
includes molding 902, plug 904, and textures 932-934. In other examples, the
number, type,
function, configuration, ornamental appearance, or other aspects shown may be
varied without
FIG. 9G illustrates a rear view of an exemplary data-capable strapband. Here,
band 960
includes molding 902, button 906, and textures 932-934. In other examples, the
number, type,
function, configuration, ornamental appearance, or other aspects shown may be
varied without
limitation.
FIG. 10 illustrates an exemplary computer system suitable for use with a data-
capable
strapband. In some examples, computer system 1000 may be used to implement
computer
programs, applications, methods, processes, or other software to perform the
above-described
techniques. Computer system 1000 includes a bus 1002 or other communication
mechanism for
communicating information, which interconnects subsystems and devices, such as
processor
1004, system memory 1006 (e.g., RAM), storage device 1008 (e.g., ROM), disk
drive 1010 (e.g.,
magnetic or optical), communication interface 1012 (e.g., modem or Ethernet
card), display 1014
(e.g., CRT or LCD), input device 1016 (e.g., keyboard), and cursor control
1018 (e.g., mouse or
trackball).
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According to some examples, computer system 1000 performs specific operations
by
processor 1004 executing one or more sequences of one or more instructions
stored in system
memory 1006. Such instructions may be read into system memory 1006 from
another computer
readable medium, such as static storage device 1008 or disk drive 1010. In
some examples, hard-
wired circuitry may be used in place of or in combination with software
instructions for
implementation.
The term "computer readable medium" refers to any tangible medium that
participates in
providing instructions to processor 1004 for execution. Such a medium may take
many forms,
including but not limited to, non-volatile media and volatile media. Non-
volatile media includes,
for example, optical or magnetic disks, such as disk drive 1010, Volatile
media includes dynamic
memory, such as system memory 1006.
Common forms of computer readable media includes, for example, floppy disk,
flexible
disk, hard disk, magnetic tape, any other magnetic medium, CD-ROM, any other
optical medium,
punch cards, paper tape, any other physical medium with patterns of holes,
RAM, PROM,
EPROM, FLASH-EPROM, any other memory chip or cartridge, or any other medium
from which
a computer can read.
Instructions may further be transmitted or received using a transmission
medium. The
term "transmission medium" may include any tangible or intangible medium that
is capable of
storing, encoding or carrying instructions for execution by the machine, and
includes digital or
analog communications signals or other intangible medium to facilitate
communication of such
instructions. Transmission media includes coaxial cables, copper wire, and
fiber optics, including
wires that comprise bus 1002 for transmitting a computer data signal.
In some examples, execution of the sequences of instructions may be performed
by a
single computer system 1000. According to some examples, two or more computer
systems 1000
coupled by communication link 1020 (e.g., LAN, PSTN, or wireless network) may
perform the
sequence of instructions in coordination with one another. Computer system
1000 may transmit
and receive messages, data, and instructions, including program, i.e.,
application code, through
communication link 1020 and communication interface 1012. Received program
code may be
executed by processor 1004 as it is received, and/or stored in disk drive
1010, or other non-
volatile storage for later execution.
FIG. 11 depicts a variety of inputs in a specific example of a strapband, such
as a data-
capable strapband, according to various embodiments, In diagram 1100,
strapband 1102 can
include one or more of the following: a switch 1104, a display I/O 1120, and a
multi-pole or
multi-position switch 1101. Switch 1104 can rotate in direction 1107 to select
a mode, or switch
1104 can be a push button operable by pushing in direction 1105, whereby
subsequent pressing of
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the button cycles through different modes of operation. Or, different
sequences of short and long
durations during which the button is activated. Display I/O 1120 can be a
touch-sensitive
graphical user interface. The multi-pole switch 1101, in some examples, can be
a four-position
switch, each position being associated with a mode (e.g., a sleep mode, an
active mode, a normal
mode, etc.). Additionally, commands can be entered via graphical user
interface 1112 via
wireless (or wired) communication device 1110. Further, any number of visual
outputs (e.g.,
LEDs as indicator lights), audio outputs, and/or mechanical (e.g., vibration)
outputs can be
implemented to inform the user of an event, a mode, or any other status of
interest relating to the
functionality of the strapband.
FIGs, 12A to 12F depict a variety of motion signatures as input into a
strapband, such as a
data-capable strapband, according to various embodiments. In FIG. 12A, diagram
1200 depicts a
user's arm (e.g., as a locomotive member or appendage) with a strapband 1202
attached to user
wrist 1203, Strapband 1202 can envelop or substantially surround user wrist
1203 as well. FIGs,
12B to 12D illustrate different "motion signatures" defined by various ranges
of motion and/or
motion patterns (as well as number of motions), whereby each of the motion
signatures identifies
a mode of operation. FIG. 12B depicts up-and-down motion, FIG, 12C depicts
rotation about the
wrist, and FIG, 12D depicts side-to-side motion. FIG, 12E depicts an ability
detect a change in
mode as a function of the motion and deceleration (e.g,, when a user claps
hands or makes contact
with a surface 1220 to get strapband to change modes), whereas, FIG. 12F
depicts an ability to
detect "no motion" initially and experience an abrupt acceleration of the
strapband (e.g., user taps
strapband with finger 1230 to change modes). Note that motion signatures can
be motion patterns
that are predetermined, with the user selecting or linking a specific motion
signature to invoke a
specific mode. Note, too, a user can define unique motion signatures. In some
embodiments, any
number of detect motions can be used to define a motion signature. Thus,
different numbers of
the same motion can activate different modes. For example, two up-and-down
motions in FIG.
12B can activate one mode, whereas four up-and-down motions can activate
another mode.
Further, any combination of motions (e.g,, two up-and-down motions of FIG. 12B
and two taps of
FIG. 12E) can be used as an input, regardless whether a mode of operation or
otherwise.
FIG. 13 depicts an inference engine of a strapband configured to detect an
activity and/or a
mode based on monitored motion, according to various embodiments. In some
embodiments,
inference engine 1304 of a strapband can be configured to detect an activity
or mode, or a state of
a strapband, as a function of at least data derived from one or more sources
of data, such as any
number of sensors. Examples of data obtained by the sensors include, but are
not limited to, data
describing motion, location, user characteristics (e.g., heart rate, body
temperature, etc.),
environmental characteristics (e.g., time, degree of ambient light, altitude,
magnetic flux (e.g.,
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magnetic field of the earth), or any other source of magnetic flux), GPS-
generated position data,
proximity to other strapband wearers, etc.), and data derived or sensed by any
source of relevant
information. Further, inference engine 1304 is configured to analyze sets of
data from a variety of
inputs and sources of information to identify an activity, mode and/or state
of a strapband. In one
example, a set of sensor data can include GPS-derived data, data representing
magnetic flux, data
representing rotation (e.g., as derived by a gyroscope), and any other data
that can be relevant to
inference engine 1304 in its operation. The inference engine can use
positional data along with
motion-related information to identify an activity or mode, among other
purposes.
According to some embodiments, inference engine 1304 can be configured to
analyze
real-time sensor data, such as user-related data 1301 derived in real-time
from sensors and/or
environmental-related data 1303 derived in real-time from sensors. In
particular, inference engine
1304 can compare any of the data derived in real-time (or from storage)
against other types of
data (regardless of whether the data is real-time or archived), The data can
originate from
different sensors, and can obtained in real-time or from memory as user data
1352. Therefore,
inference engine 1304 can be configured to compare data (or sets of data)
against each other,
thereby matching sensor data, as well as other data, to determine an activity
or mode.
Diagram 1300 depicts an example of an inference engine 1304 that is configured
to
determine an activity in which the user is engaged, as a function of motion
and, in some
embodiments, as a function of sensor data, such as user-related data 1301
derived from sensors
and/or environmental-related data 1303 derived from sensors, Examples of
activities that
inference engine 1304 evaluates include sitting, sleeping, working, running,
walking, playing
soccer or baseball, swimming, resting, socializing, touring, visiting various
locations, shopping at
a store, and the like. These activities are associated with different motions
of the user, and, in
particular, different motions of one or more locomotive members (e.g,, motion
of a user's arm or
wrist) that are inherent in the different activities. For example, a user's
wrist motion during
running is more "pendulum-like" in it motion pattern, whereas, the wrist
motion during swimming
(e.g., freestyle strokes) is more "circular-like" in its motion pattern.
Diagram 1300 also depicts a
motion matcher 1320, which is configured to detect and analyze motion to
determine the activity
(or the most probable activity) in which the user is engaged. To further
refine the determination
of the activity, inference engine 1304 includes a user characterizer 1310 and
an environmental
detector 1311 to detect sensor data for purposes of comparing subsets of
sensor data (e.g,, one or
more types of data) against other subsets of data, Upon determining a match
between sensor data,
inference engine 1304 can use the matched sensor data, as well as motion-
related data, to identify
a specific activity or mode. User characterizer 1310 is configured to accept
user-related data 1301
from relevant sensors. Examples of user-related data 1301 include heart rate,
body temperature,
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or any other personally-related information with which inference engine 1304
can determine, for
example, whether a user is sleeping or not. Further, environmental detector
1311 is configured to
accept environmental-related data 1303 from relevant sensors. Examples of
environmental-
related data 1303 include time, ambient temperature, degree of brightness
(e.g., whether in the
dark or in sunlight), location data (e.g., GPS data, or derived from wireless
networks), or any
other environmental-related information with which inference engine 1304 can
determine whether
a user is engaged in a particular activity.
A strapband can operate in different modes of operation. One mode of operation
is an
"active mode," Active mode can be associated with activities that involve
relatively high degrees
of motion at relatively high rates of change. Thus, a strapband enters the
active mode to
sufficiently capture and monitor data with such activities, with power
consumption as being less
critical. In this mode, a controller, such as mode controller 1302, operates
at a higher sample rate
to capture the motion of the strapband at, for example, higher rates of speed.
Certain safety or
health-related monitoring can be implemented in active mode, or, in response
to engaging in a
specific activity. For example, a controller of strapband can monitor a user's
heart rate against
normal and abnormal heart rates to alert the user to any issues during, for
example, a strenuous
activity. In some embodiments, strapband can be configured as set forth in
FIG. 5B and user
characterizer 1310 can process user-related information from sensors described
in relation FIG.
5B, Another mode of operation is a "sleep mode." Sleep mode can be associated
with activities
that involve relatively low degrees of motion at relatively low rates of
change. Thus, a strapband
enters the sleep mode to sufficiently capture and monitor data with such
activities, while
preserving power. In some embodiments, strapband can be configured as set
forth in FIG, 5C and
user characterizer 1310 can process user-related information from sensors
described in relation
FIG. 5C. Yet another mode is "normal mode," in which the strapband operates in
accordance
with typical user activities, such as during work, travel, movement around the
house, bathing, etc.
A strapband can operate in any number different modes, including a health
monitoring mode,
which can implement, for example, the features set forth in FIG. 5D, Another
mode of operation
is a "social mode" of operation in which the user interacts with other users
of similar strapbands
or communication devices, and, thus, a strapband can implement, for example,
the features set
forth in FIG. 5E. Any of these modes can be entered or exited either
explicitly or implicitly.
Diagram 1300 also depicts a motion matcher 1320, which is configured to detect
and
analyze motion to determine the activity (or the most probable activity) in
which the user is
engaged. In various embodiments, motion matcher 1320 can form part of
inference engine 1304
(not shown), or can have a structure and/or function separate therefrom (as
shown). Regardless,
the structures and/or functions of inference engine 1304, including user
characterizer 1310 and an
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environmental detector 1311, and motion matcher 1320 cooperate to determine an
activity in
which the user is engaged and transmit data indicating the activity (and other
related information)
to a controller (e.g., a mode controller 1302) that is configured to control
operation of a mode,
such as an "active mode," of the strapband.
Motion matcher 1320 of FIG. 13 includes a motion/activity deduction engine
1324, a
motion capture manager 1322 and a motion analyzer 1326. Motion matcher 1320
can receive
motion-related data 1303 from relevant sensors, including those sensors that
relate to space or
position and to time. Examples of such sensors include accelerometers, motion
detectors,
velocimeters, altimeters, barometers, etc. Motion capture manager 1322 is
configured to capture
portions of motion, and to aggregate those portions of motion to form an
aggregated motion
pattern or profile. Further, motion capture manager 1322 is configured to
store motion patterns as
profiles 1344 in database 1340 for real-time or future analysis. Motion pro-
files 1344 include sets
of data relating to instances of motion or aggregated portions of motion
(e.g,, as a function of time
and space, such as expressed in X, Y, Z coordinate systems).
For example, motion capture manager 1322 can be configured to capture motion
relating
to the activity of walking and motion relating to running, each motion being
associated with a
specific profile 1344. To illustrate, consider that motion profiles 1344 of
walking and running
share some portions of motion in common. For example, the user's wrist motion
during running
and walking share a "pendulum-like" pattern over time, but differ in sampled
positions of the
strapband. During walking, the wrist and strapband is generally at waist-level
as the user walks
with arms relaxed (e.g., swinging of the arms during walking can result in a
longer arc-like
motion pattern over distance and time), whereas during running, a user
typically raises the wrists
and changes the orientation of the strapband (e.g., swinging of the arms
during running can result
in a shorter arc-like motion pattern). Motion/activity deduction engine 1324
is configured to
access profiles 1344 and deduce, for example, in real-time whether the
activity is walking or
running.
Motion/activity deduction engine 1324 is configured to analyze a portion of
motion and
deduce the activity (e.g., as an aggregate of the portions of motion) in which
the user is engaged
and provide that information to the inference engine 1304, which, in turn,
compares user
characteristics and environmental characteristics against the deduced activity
to confirm or reject
the determination, For example, if motion/activity deduction engine 1324
deduces that monitored
rnotion indicates that the user is sleeping, then the heart rate of the user,
as a user characteristic,
can be used to compare against thresholds in user data 1352 of database 1350
to confirm that the
user's heart rate is consistent with a sleeping user. User data 1352 can also
include past location
data, whereby historic location data can be used to determine whether a
location is frequented by
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a user (e.g., as a means of identifying the user). Further, inference engine
1304 can evaluate
environmental characteristics, such as whether there is ambient light (e.g.,
darkness implies
condition,s for resting), the time of day (e.g., a person's sleeping times
typically can be between
12 midnight and 6 am), or other related information.
In operation, motion/activity deduction engine 1324 can be configured to store
motion-
related data to form motion profiles 1344 in real-time (or near real-time). In
some embodiments,
the motion-related data can be compared against motion reference data 1346 to
determine "a
match" of motions. Motion reference data 1346, which includes reference motion
profiles and
patterns, can be derived by motion data captured for the user during previous
activities, whereby
the previous activities and motion thereof serve as a reference against which
to compare, Or,
motion reference data 1346 can include ideal or statistically-relevant motion
patterns against
which motion/activity deduction engine 1324 determines a match by determining
which reference
profile data 1346 "best fits" the real-time motion data. Motion/activity
deduction engine 1324 can
operate to determine a motion pattern, and, thus, determine an activity. Note
that motion
reference profile data 1346, in some embodiments, serves as a "motion
fingerprint" for a user and
can be unique and personal to a specific user. Therefore, motion reference
profile data 1346 can
be used by a controller to determine whether subsequent use of a strapband is
by the authorized
user or whether the current user's real-time motion data is a mismatch against
motion reference
profile data 1346. If there is mismatch, a controller can activate a security
protocol responsive to
the unauthorized use to preserve information or generate an alert to be
communicated external to
the strapband.
Motion analyzer 1326 is configured to analyze motion, for example, in real-
time, among
other things. For example, if the user is swinging a baseball bat or golf club
(e.g., when the
strapband is located on the wrist) or the user is kicking a soccer ball (e.g.,
when the strapband is
located on the ankle), motion analyzer 1326 evaluates the captured motion to
detect, for example,
a deceleration in motion (e.g., as a motion-centric event), which can be
indicative of an impulse
event, such as striking an object, like a golf ball. Motion-related
characteristics, such as space and
time, as well as other environment and user characteristics can be captured
relating to the motion-
centric event, A motion-centric event, for example, is an event that can
relate to changes in
position during motion, as well as changes in time or velocity. In some
embodiments, inference
engine 1304 stores user characteristic data and environmental data in database
1350 as user data
1352 for archival purposes, reporting purposes, or any other purpose.
Similarly inference engine
1304 and/or motion matcher 1320 can store motion-related data as motion data
1342 for real-time
and/or future use. According to some embodiments, stored data can be accessed
by a user or any
entity (e.g.; a third party) to adjust the data of databases 1340 and 1350 to,
for example, optimize
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motion profile data or sensor data to ensure more accurate results. A user can
access motion
profile data in database 1350. Or, a user can adjust the functionality of
inference engine 1304 to
ensure more accurate or precise determinations. For example, if inference
engine 1304 detects a
user's walking motion as a running motion, the user can modify the behavior of
the logic in the
strapband to increase the accuracy and optimize the operation of the
strapband.
FIG. 14 depicts a representative implementation of one or more strapbands and
equivalent
devices, as wearable devices, to form unique motion profiles, according to
various embodiments.
In diagram 1400, strapbands and an equivalent device are disposed on
locomotive members of the
user, whereby the locomotive members facilitate motion relative to and about a
center point 1430
(e.g., a reference point for a position, such as a center of mass). A headset
1410 is configured to
communicate with strapbands 1411, 1412, 1413 and 1414 and is disposed on a
body portion 1402
(e.g., the head), which is subject to motion relative to center point 1430.
Strapbands 1411 and
1412 are disposed on locomotive portions 1404 of the user (e.g., the arms or
wrists), whereas
strapbands 1413 and 1414 are disposed on locomotive portion 1406 of the user
(e.g., the legs or
ankles). As shown, headset 1410 is disposed at distance 1420 from center point
1430, strapbands
1411 and 1412 are disposed at distance 1422 from center point 1430, and
strapbands 1413 and
1414 are disposed at distance 1424 from center point 1430. A great number of
users have
different values of distances 1420, 1422, and 1424. Further, different wrist-
to-elbow and elbow-
to-shoulder lengths for different users affect the relative motion of
strapbands 1411 and 1412
about center point 1430, and similarly, different hip-to-knee and knee-to-
ankle lengths for
different users affect the relative motion of strapbands 1413 and 1414 about
center point 1430.
Moreover, a great number of users have unique gaits and styles of motion. The
above-described
factors, as well as other factors, facilitate the determination of a unique
motion profile for a user
per activity (or in combination of a number of activities). The uniqueness of
the motion patterns
in which a user performs an activity enables the use of motion profile data to
provide a "motion
fingerprint." A "motion fingerprint" is unique to a user and can be compared
against detected
motion profiles to determine, for example, whether a use of the strapband by a
subsequent wearer
is unauthorized. In some cases, unauthorized users do not typically share
common motion
profiles. Note that while four are shown, fewer than four can be used to
establish a "motion
fingerprint," or more can be shown (e.g., a strapband can be disposed in a
pocket or otherwise
carried by the user). For example, a user can place a single strapbands at
different portions of the
body to capture motion patterns for those body parts in a serial fashion.
Then, each of the
motions patterns can be combined to form a "motion fingerprint." In some
cases, a single
strapband 1411 is sufficient to establish a "motion fingerprint." Note, too,
that one or more of
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strapbands 1411, 1412, 1413 and 1414 can be configured to operate with
multiple users, including
non-human users, such as pets,
FIG. 15 depicts an example of a motion capture manager configured to capture
motion and
portions therefore, according to various embodiments. Diagram 1500 depicts an
example of a
motion matcher 1560 and/or a motion capture manager 1561, one or both of which
are configured
to capture motion of an activity or state of a user and generate one or more
motion profiles, such
as motion profile 1502 and motion profile 1552, Database 1570 is configured to
store motion
profiles 1502 and 1552. Note that motion profiles 1502 and 1552 are shown as
graphical
representation of motion data for purposes of discussion, and can be stored in
any suitable data
structure or arrangement. Note, too, that motion profiles 1502 and 1552 can
represent real-time
motion data with which a motion matcher 1560 uses to determine modes and
activities.
To illustrate operation of motion capture manager 1561, consider that motion
profile 1502
represents motion data captured for a running or walking activity. The data of
motion profile
1502 indicates the user is traversing along the Y-axis with motions
describable in X, Y, Z
coordinates or any other coordinate system. The rate at which motion is
captured along the Y-
axis is based on the sampling rate and includes a time component. For a
strapband disposed on a
wrist of a user, motion capture manager 1561 captures portions of motion, such
as repeated
motion segments A-to-B and B-to-C. In particular, motion capture manager 1561
is configured to
detect motion for an arm 1501a in the +Y direction from the beginning of the
forward swinging
arm (e.g., point A) to the end of the forward swinging arm (e.g., point B).
Further, motion capture
manager 1561 is configured to detect motion for arm 1501b in the -Y direction
from the
beginning of the backward swinging arm (e.g., point B) to the end of the
backward swinging arm
(e.g., point C). Note that point C is at a greater distance along the Y-axis
than point A as the
center point or center mass of the user has advanced in the +Y direction,
Motion capture manager
1561 continues to monitor and capture motion until, for example, motion
capture manager 1561
detects no significant motion (i.e., below a threshold) or an activity or mode
is ended.
Note that in some embodiments, a motion profile can be captured by motion
capture
manager 1561 in a "normal mode" of operation and sampled at a first sampling
rate ("sample rate
1") 1532 between samples of data 1520, which is a relatively slow sampling
rate that is
configured to operate with normal activities. Samples of data 1520 represent
not only motion data
(e.g., data regarding X, Y, and Z coordinates, time, accelerations,
velocities, etc.), but can also
represent or link to user related information captured at those sample times.
Motion matcher 1560
analyzes the motion, and, if the motion relates to an activity associated with
an "active mode,"
motion matcher 1560 signals to the controller, such as a mode controller, to
change modes (e.g.,
from normal to active mode). During active mode, the sampling rate increases
to a second
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sampling rate ("sample rate 2") 1534 between samples of data 1520 (e.g., as
well as between a
sample of data 1520 and a sample of data 1540). An increased sampling rate can
facilitate, for
example, a more accurate set of captured motion data. To illustrate the above,
consider that a user
is sitting or stretching prior to a work out. The user's activities likely are
occurring in a normal
mode of operation. But once motion data of profile 1502 is detected, a
motion/activity deduction
engine can deduce the activity of running, and then can infer the mode ought
to be the active
mode. The logic of the strapband then can place the strapband into the active
mode. Therefore,
the strapband can change modes of operation implicitly (i.e., explicit actions
to change modes
need not be necessary). In some cases, a mode controller can identify an
activity as a "running"
activity, and then invoke activity-specific functions, such as an indication
(e.g., a vibratory
indication) to the user every one-quarter mile or 15 minute duration during
the activity.
FIG. 15 also depicts another motion profile 1552. Consider that motion profile
1552
represents motion data captured for swimming activity (e.g., using a freestyle
stroke). Similar to
profile 1502, the motion pattern data of motion profile 1552 indicates the
user is traversing along
the Y-axis. The rate at which motion is captured along the Y-axis is based on
the sampling rate of
samples 1520 and 1540, for example. For a strapband disposed on a wrist of a
user, motion
capture manager 1561 captures the portions of motion, such as motion segments
A-to-B and B-to-
C. In particular, motion capture manager 1561 is configured to detect motion
for an arm 1551a in
the +Y direction from the beginning of a forward arc (e.g., point A) to the
end of the forward are
(e.g., point B). Further, motion capture manager 1561 is configured to detect
motion for arm
1551b in the -Y direction from the beginning of reverse arc (e.g., point B) to
the end of the
reverse arc (e.g., point C). Motion capture manager 1561 continues to monitor
and capture
motion until, for example, motion capture manager 1561 detects no significant
motion (i.e., below
a threshold) or an activity or mode is ended.
In operation, a mode controller can determine that the motion data of profile
1552 is
associated with an active mode, similar with the above-described running
activity, and can place
the strapband into the active mode, if it is not already in that mode.
Further, motion matcher 1560
can analyze the motion pattern data of profile 1552 against, for example, the
motion data of
profile 1502 and conclude that the activity associated with the data being
captured for profile
1552 does not relate to a running activity. Motion matcher 1560 then can
analyze profile 1552 of
the real-time generated motion data, and, if it determines a match with
reference motion data for
the activity of swimming, motion matcher 1560 can generate an indication that
the user is
performing "swimming" as an activity. Thus, the strapband and its logic can
implicitly determine
an activity that a user is performing (i.e., explicit actions to specify an
activity need not be
necessary). Therefore, a mode controller then can invoke swimming-specific
functions, such as
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an application to generate an indication (e.g., a vibratory indication) to the
user at completion of
every lap, or can count a number of strokes. While not shown, motion matcher
1560 and/or a
motion capture manager 1561 can be configured to implicitly determine modes of
operation, such
as a sleeping mode of operation (e.g., the mode controller, in part, can
analyze motion patterns
against a motion profile that includes sleep-related motion data. Motion
matcher 1560 and/or a
motion capture manager 1561 also can be configured to an activity out of a
number of possible
activities.
FIG. 16 depicts an example of a motion analyzer configured to evaluate motion-
centric
events, according to various embodiments. Diagram 1600 depicts an example of a
motion
matcher 1660 and/or a motion analyzer 1666 for capturing motion of an activity
or state of a user
and generating one or more motion profiles, such as a motion profile 1602. To
illustrate, consider
that motion profile 1602 represents motion data captured for an activity of
swinging a baseball bat
1604. The motion pattern data of motion profile 1602 indicates the user begins
the swing at
position 1604a in the -Y direction. The user moves the strapband and the bat
to position 1604b,
and then swings the bat toward the -Y direction when contact is made with the
baseball at position
1604c. Note that the set of data samples 1630 includes data samples 1630a and
1630b at
relatively close proximity to each other in profile 1602, This indicates a
deceleration (e.g., a
slight, but detectable deceleration) in the bat when it hits the baseball.
Thus, motion analyzer
1666 can analyze motion to determine motion-centric events, such as striking a
baseball, striking
a golf ball, or kicking a soccer ball. Data regarding the motion-centric
events can be stored in
database 1670 for additional analysis or archiving purposes, for example.
FIG. 17 illustrates action and event processing during a mode of operation in
accordance
with various embodiments. At 1702, the strapband enters a mode of operation.
During a certain
mode, a controller (e.g., a mode controller) can be configured to monitor user
characteristics at
1704 relevant to the mode, as well as relevant motion at 1706 and
environmental factors at 1708.
The logic of the strapband can operate to detect user and mode-related events
at 1710, as well as
motion-centric events at 1712. Optionally, upon detection of an event, the
logic of the strapband
can perform an action at 1714 or inhibit an action at 1716, and continue to
loop at 1718 during the
activity or mode.
To illustrate action and event processing of a strapband, consider the
following examples.
First, consider a person is performing an activity of running or jogging, and
enters an active mode
at 1702. The logic of the strapband analyzes user characteristics at 1704,
such as sleep patterns,
and determines that the person has been getting less than a normal amount of
sleep for the last few
days, and that the person's heart rate indicates the user is undergoing
strenuous exercise as
confirmed by detected motion in 1706. Further, the logic determines a large
number of wireless
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signals, indicating a populated area, such as along a busy street. Next, the
logic detects an
incoming call to the user's headset at 1710. Given the state of the user, the
logic suppresses the
call at 1716 to ensure that the user is not distracted and thus not
endangered.
As a second example, consider a person is performing an activity of sleeping
and has
entered a sleep mode at 1702. The logic of the strapband analyzes user
characteristics at 1704,
such as heart rate, body temperature, and other user characteristics relevant
to the determination
whether the person is in REM sleep. Further, the person's motion has decreased
sufficiently to
match that typical of periods of deep or REM sleep as confirmed by detected
motion (or lack
thereof) at 1706. Environmental factors indicate a relatively dark room at
1708. Upon
determination that the user is in REM sleep, as an event, at 1710, the logic
of the strapband
inhibits an alarm at 1716 set to wake the user until REM sleep is over. This
process loops at 1718
until the user is out of REM sleep, when the alarm can be performed
subsequently at 1714. In one
example, the alarm is implemented as a vibration generated by the strapband.
Note that the
strapband can inhibit the alarm features of a mobile phone, as the strapband
can communicate an
alarm disable signal to the mobile phone.
In at least some examples, the structures and/or functions of any of the above-
described
features can be implemented in software, hardware, firmware, circuitry, or a
combination thereof.
Note that the structures and constituent elements above, as well as their
functionality, may be
aggregated with one or more other structures or elements. Alternatively, the
elements and their
functionality may be subdivided into constituent sub-elements, if any. As
software, the above-
described techniques may be implemented using various types of programming or
formatting
languages, frameworks, syntax, applications, protocols, objects, or
techniques. As hardware
and/or firmware, the above-described techniques may be implemented using
various types of
programming or integrated circuit design languages, including hardware
description languages,
such as any register transfer language ("RTL") configured to design field-
programmable gate
arrays ("FPGAs"), application-specific integrated circuits ("ASICs"), or any
other type of
integrated circuit. These can be varied and are not limited to the examples or
descriptions
provided.
FIG, 18A illustrates an exemplary wearable device for sensory user interface.
Here, a
cross-sectional view of wearable device 1800 includes housing 1802, switch
1804, switch rod
1806, switch seal 1808, pivot arm 1810, spring 1812, printed circuit board
(hereafter "PCB")
1814, support 1816, light pipes 1818-1820, and light windows 1822-1824. In
some examples,
wearable device 1800 may be implemented as part of band 900 (FIG. 9A),
providing a user
interface for a user to interact, manage, or otherwise manipulate controls for
a data-capable
strapband. As shown, when switch 1804 is depressed and stopped by switch seal
1808, switch rod
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1806 may be configured to mechanically engage pivot arm 1810 and cause
electrical contact with
one or more elements on PCB 1814. In an alternative example, pivot arm 1810
may cause light to
be selectively reflected back, depending on the position of pivot arm 1810, to
PCB 1814, which
may comprise an optical transmitter/receiver to detect the reflection and to
report back different
rotational positions of pivot arm 1810. In another alternative example, pivot
arm 1810 may
comprise magnets, which may be brought into, and out of, proximity with one or
more magnetic
field sensor on PCB 1814 indicating different rotational positions of switch
1804, In other
examples, switch 1804 may be configured to rotate and cause electrical contact
with other
elements on PCB 1814, Spring 1812 is configured to return switch rod 1806 and
button 1804 to a
recoiled position to await another user input (e.g., depression of switch
1804), In some examples,
light sources (e.g., LED 224 (FIG. 2A)) may be mounted on PCB 1814 and, using
light pipes
1818 and 1820 provide illuminated displays through light windows 1822 and
1824. Further, light
windows 1822 and 1824 may be implemented as rotating switches that are
translucent,
transparent, or opaque and, when rotated, emit light from different features
that visually indicate
when a different function, mode, or operation is present. In other examples,
wearable device 1800
may be implemented differently and is not limited to those provided.
FIG. 18B illustrates an alternative exemplary wearable device for sensory user
interface,
Here, a cross-sectional view of an alternative wearable device 1830 includes
switch rod 1806,
pivot arm 1810, spring 1812, light pipes 1818-1820, switch seal 1832, and
detents 1834. In some
examples, switch seal 1832 may be configured differently than as shown in FIG.
18A, providing a
flush surface against which switch 1804 (FIG. 18A) may be depressed until
stopped by detents
1834. Further, switch seal 1832 may be formed using material that is
waterproof, water-resistant,
or otherwise able to prevent the intrusion of undesired materials, chemicals,
or liquids into the
interior cavity of wearable device 1830. In other examples, wearable device
1830 may be
configured, designed, formed, fabricated, function, or otherwise implemented
differently and is
not limited to the features, functions, and structures shown,
FIG. 18C illustrates an exemplary switch rod to be used with an exemplary
wearable
device. Here, a perspective view of switch rod 1806, which may be configured
to act as a shaft or
piston that, when depressed using switch 1804 (FIG, l 8A), engages pivot arm
1810 (FIG. 18A)
and moves into electrical contact one or more components on PCB 1814. Limits
on the rotation
or movement of switch rod 1806 may be provided by various types of mechanical
structures and
are not limited to any examples shown and described.
FIG. 18D illustrates an exemplary switch for use with an exemplary wearable
device.
Here, a distal end of wearable device 1840 is shown including housing 1802,
switch 1804, and
concentric seal 1842, As an alternative design, concentric seal 1842 may be
implemented to
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provide greater connectivity between switch 1804 and detents 1834 (not shown;
FIG. 18B). As
shown, a concentric well in concentric seal 1842 may be configured to receive
switch 1804 and,
when depressed, engage switch rod 1806 (not shown; FIG, 18A). In other
examples, wearable
device 1840 and the above-described elements may be varied in function,
structure, design,
implementation, or other aspects and are not limited to those shown.
FIG. 18E illustrates an exemplary sensory user interface, Here, wearable
device 1850
includes housing 1802, switch 1804, and light windows 1822-1824. In some
examples, light
windows 1822-1824 may be implemented using various designs, shapes, or
features in order to
permit light to emanate from, for example, LEDs mounted on PCB 1814, Further,
light windows
1822-1824 may also be implemented as rotating switches that, when turned to a
given orientation,
provide a visual indication of a function, mode, activity, state, or operation
being performed. In
other examples, wearable device 1850 and the above-described elements may be
implemented
differently in design, function, or structure, and are not limited to those
shown,
Although the foregoing examples have been described in some detail for
purposes of
clarity of understanding, the above-described inventive techniques are not
limited to the details
provided. There are many alternative ways of implementing the above-described
invention
techniques. The disclosed examples are illustrative and not restrictive,
38
