Note: Descriptions are shown in the official language in which they were submitted.
CA 02817145 2013-05-06
WO 2012/171032 PCT/US2012/041958
DETERMINATIVE PROCESSES FOR WEARABLE DEVICES
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
determinative processes for wearable devices 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
GPS 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 nurribcr 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 ("GPS") receiver arc available
conventionally, but arc
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.
Further, processing capabilities such as complex software for increasing
demands for creative and
customized software that can analyze and present sensory data and smaller
packaging has led to
significantly increased costs and processing challenges. Further, complex
software or processing
capabilities typically requires significant power availability and results in
high power, low life uses of
expensive devices. 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.
Thus, what is nccdcd is a solution for improving the capabilities of data
capture devices without
the limitations of conventional techniques.
BRIEF DESCRIPTION OF THE DRAWINGS
Various embodiments or examples ("examples") arc disclosed in the following
detailed
description and the accompanying drawings:
FIG. 1 illustrates an exemplary data-capable strapband system;
CA 02817145 2013-05-06
WO 2012/171032 PCT/US2012/041958
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 usc 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 an exemplary recommendation system;
FIG. 7 illustrates an exemplary system for feature extraction from body-worn
accelerometers;
FIG. 8 illustrates an exemplary determinative process for wearable devices;
FIG. 9 illustrates another exemplary determinative process for wearable
devices; and
FIG. 10 illustrates an exemplary computer system suitable for use with a data-
capable strapband.
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 arc 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
2
CA 02817145 2013-05-06
WO 2012/171032 PCT/US2012/041958
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 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 ("Ur) 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.
3
CA 02817145 2013-05-06
WO 2012/171032 PCT/US2012/041958
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 arc
organic (i.e., 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 1.15, 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 car
clip (e.g., a headset as described below) affixed to an car 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- I 12 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 802.1 la/b/g/n (WiFi), WiMax, ANTrm, ZigBece, Bluctooth , 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, wcbsite, 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 of third party servers
include servers for social
networking services, including, but not limited to, services such as Facebook
, Yahoo! .IM1, GTalkTm,
MSN MesscngerTM, Twiner 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,
4
CA 02817145 2013-05-06
WO 2012/171032 PCT/US2012/041958
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 arc 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)
arc 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 arc 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,
IRS, or others). In other
examples, wireless communication facilities using various types of data
communication protocols (e.g.,
WiFi, BluctoothO, ZigBecO, ANTrm, and others) may be implemented as part of
bands 104-112, which
may include circuitry, firmware, 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
5
CA 02817145 2013-05-06
WO 2012/171032 PCT/US2012/041958
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, arc
configured to identify a specific, individual user. By evaluating captured
data such as motion data from an
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,
6
CA 02817145 2013-05-06
WO 2012/171032 PCT/US2012/041958
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 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
7
CA 02817145 2013-05-06
WO 2012/171032 PCT/US2012/041958
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 arc 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 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 arc 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, light source 224, and
recommendation engine 226. 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, communications facility 216,
switch 222, light source 224,
and recommendation engine 226) 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, polar, or other coordinates on the carth'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
8
CA 02817145 2013-05-06
WO 2012/171032 PCT/US2012/041958
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
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) (e.g.,
light source 224, which may be
implemented as any type of illumination, fluorescing, phosphorescing, or other
light-generating mechanism
such as light emitting diode (hereafter "LED"), incandescent, fluorescent, or
other type of light), 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 car-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 numine 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.,
LIFELLNETM) that is an abstract representation of a user's health or wellness.
Li 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 ranee 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 are disposed (i.e., positioned) on
opposite sides of band 220 such that,
9
CA 02817145 2013-05-06
WO 2012/171032 PCT/US2012/041958
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 alone 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 usc to a wearer during, before, or after a given
activity or state. Feedback may also be
generated by recommendation engine 226.
In some examples, recommendation engine 226 may be implemented using software,
hardware,
circuitry, or a combination thereof. Any type of computer programming,
formatting, or scripting language
may be used to implement recommendation engine and the techniques described.
For example,
recommendation engine 226 may be configured to generate content associated
with a given state or activity
as a result of sensory input received by sensor 212 and/or accelerometer and
processed by processor 204..
As shown, recommendation engine 226 may receive various types of data
transformed from sensory input
by sensor 212. Requests or calls may be sent to memory 206, which may be
implemented as either local or
remote storage that includes one or more data storm facilities, such as those
described herein. Content to
be delivered by recommendation engine 226 may take various forms, including
text, graphical, visual,
audible, audio, multi-media, applications, algorithms, or other formats that
may be delivered using various
types of user interfaces, such as those described herein. In some examples,
content may be retrieved from
"marketplaces" where users may select various types of algorithms, templates,
or other collective
applications that may be configured for use with band 220. For example, a
"marketplace framework" may
be used to offer applications, algorithms, programs, or other types of data or
information for sell, lease, or
free to users of wearable devices. Marketplaces may be implemented using any
type of structure that
provides for the sale, purchase, lease, or license of content such as that
described above. Based on various
types of activities or states (e.g., physiological, psychological, or
otherwise) models that provide
applications that, when installed and executed, enable a user to perform
certain functions with feedback
from band 200, may also be downloaded from a marketplace. In other examples,
marketplaces of various
types and purposes may be implemented.
. Recommendation engine 226 may also be implemented to evaluate data
associated with various
types of sensory input in order to determine the type of content to be
generated and delivered, either to a
wearable device (e.g., band 220) or to another device that may or may not be
coupled to, but in data
communication (i.e., using various types of data communication protocols and
networks) with band 220.
Recommendation engine 226 is described in greater detail below in connection
with FIG. 6.
Referring back to FIG. 2B and 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
CA 02817145 2013-05-06
WO 2012/171032 PCT/US2012/041958
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 arc not limited to the examples shown.
FIG. .3 illustrates sensors for use with an exemplary data-capable sn-apband.
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, GPS 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 GPS 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.
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,
11
CA 02817145 2013-05-06
WO 2012/171032 PCT/US2012/041958
stride length or interval, time, and other data may be measured. Velocimcter
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, GPS 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 GPS algorithms may also be implemented with GPS
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 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, piczomechanical,
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
CA 02817145 2013-05-06
WO 2012/171032
PCT/US2012/041958
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
arc 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 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),
interfcromctric modulator display (IMOD),
elecn-ophoretic 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. Insome examples, audio module 414 may
include one or more cgdecs
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,
30 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.
35 Another
clement 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 with executing software-
related instructions for band 200. For example, libraries or classes that are
used by software or applications
13
CA 02817145 2013-05-06
WO 2012/171032 PCT/US2012/041958
on band 200 may be served from an online or networked source. Service
management module 418 may be
implemented to manage how and when these services arc 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. I) 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 arc 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,
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/cmission/outgassing data 526, among others), athletic efficiency
(i.e., blood oxygen level 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., biomcchanical 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
14
CA 02817145 2013-05-06
WO 2012/171032 PCT/US2012/041958
band 519. Further, data captured may be uploaded to a wcbsite or
online/networked destination for storage
and other uses. For example, fitness-related data may be used by applications
that arc 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 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
CA 02817145 2013-05-06
WO 2012/171032 PCT/US2012/041958
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, wcbsites, 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. 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 an exemplary recommendation system. Here, recommendation
system 600
includes recommendation engine 602, user interface module (hereafter "Ul
module") 604, logic 606, point
module 608, application programming interface (hereafter "API") 610, valuator
612, databases 614-616,
network 618, and data types 620-634. In some examples, data types 620-634 may
be of various types of
data converted or transformed (i.e., "transformed") from sensory input
received by, for example, sensor 212
(FIG. 2B), including psychological data 620, physiological data 622,
biological data 624, activity data 626,
state data 628, mood data 630, sleep data 632, medical data 634, among others,
without limitation. In some
examples, data types 620-634 may be transformed from input received from a
variety of sensors, including
one or more of the sensors described in connection with FIG. 3. For example,
input from an accelerometer
(i.e., accelerometer 302), an HR monitor (i.e., HR monitor 308), an audio
sensor (i.e., audio sensor 310), a
location-based service sensor (i.e., location-based service sensor 318), and
other sensors, may be
transformed into sleep data 632. In another example, input from a chemical
sensor (i.e., chemical sensor
324), an HR monitor (i.e., HR monitor 308), an IR sensor (i.e., IR sensor
306), and other sensors., may be
transformed into mood data 630. In still other examples, input from different
groups of sensors may be
16
CA 02817145 2013-05-06
WO 2012/171032 PCT/US2012/041958
transformed into other data types. As shown recommendation engine 602 may be
configured to receive data
types 620-634 using UI module 604. In some examples, Ul module 604 may be
configured to provide
various interfaces (e.g., a form, a field, a download/upload interface, a drag-
and-drop interface, or the like)
and to receive user input in a variety of formats, including typing (i.e.,
into a field), uploading data (e.g.,
from an external drive, a camera, a portable USB-drive, a CD-ROM, a DVD, a
portable computing device, a
smartphone, a portable communication device, a wearable device, or other
device), a mouse click (i.e.. in a
form), another type of selection (i.e., using a drag-and-drop interface), or
other formats. Logic 606 may be
configured to perform various types of functions and operations using user and
system-specified rules. For
example, logic 606 may generate a control signal configured to initiate the
transformation of sensory input
received by sensor 212 into data configured to be sent to recommendation
engine 602. In another example,
logic 606 may be configured to generate different control signals according to
different rules. For example,
logic 606, which may be implemented separately or as a part of processor 204
(FIGs. 2A-2B) may indicate
that valuator 612 should quantitatively calculate, algorithmically or
otherwise, a value for the received data
and assign a point value by point module 608. In some examples, an assigned
point value may be used to
compare an account associated with a wearable device (e.g., band 200 (FIG. 2A)
or band 220 (FIG. 2B))
with another account (i.e., wearable device) or against a set of data or
parameters specified by a user (e.g., a
fitness, health, athletic, or wellness-oriented goal). For example, a database
(e.g., database 614-616) may
store information in, with, or otherwise associated with, an account (e.g.,
associated with a wearable device,
band or user), the information including information (e.g., data, points, or
other values) associated with, for
example, a fitness goal, a health issue, a medical condition, an activity, a
promotion, an award or award
program, or the like. Point module 608 may also be configured to cooperatively
process data in order to
present to a user a display or other rendering that illustrates progress,
status, or state. For example, point
module 608 may be configured to present a "lifeline," other graph or graphic,
or other abstract
representation of a given user's health, wellness, or other characteristic.
Further, point module 608 may be
generated by recommendation engine 602 in order to provide a user interface or
other mechanism by which
a user of a wearable device can view various types of qualitative and
quantitative information associated
with data provided from various types of sensors such as those described
herein. =
As shown, recommendation engine 602 may be configured to present content on or
at a user
interface using API 610. in some examples, content may be recommendations that
are presented relative to
data types evaluated by recommendation engine 602. In some examples,
recommendations may be
presented in various types of forms and formats such as vibration, noise,
light, or other sensory notification. =
In other examples, recommendations also may be textual, graphical, visual,
audible, or other types of
content that may be perceived by a user of a wearable device. For example, if
recommendation engine 602
detects, using mood data type 630, that a user is depressed (i.e., lowered
heart rate or pulse, skin tautness is
lessened, biological, physiological, psychological, or other factors indicate
a depressed state),
recommendation engine 602 may be configured to request content from database
614 (which may be in
local data communication with recommendation engine 602) or database 616
(which may be remotely in
data communication with recommendation engine 602 over network 618 (e.g., LAN,
WAN, MAN, cloud,
17
CA 02817145 2013-05-06
WO 2012/171032
PCT/US2012/041958
SAN, and others). Such content may be a recommendation, and may include a
discounted promotion to a
day spa, a vibration or other sensory notification intended to stimulate a
user to improve or heighten her
mood (i.e., psychological state). In other examples, a recommendation, or
other content generated by
recommendation engine 602, may be related to an activity or state. In other
examples, recommendation
engine 602 may be used to generate other types of recommendations, including
advertisements, promotions,
awards, offers, editorial (e.g., newscasts, podcasts, video logs (i.e.,
vlogs), web logs (i.e., blogs), text, video,
multimedia, or other types of content retrieved from database 614 and/or 616.
In some examples, a
recommendation generated by recommendation engine 602 may be associated with a
health condition,
medical condition, fitness eoal, award, promotion, or the like. In still othei
examples, recommendation =
system 600 and the above-described elements may be varied and are not limited
to those shown and
described.
FIG. 7 illustrates an exemplary system for feature extraction from body-worn
accelerometers.
Here, system 700 includes coordinate transformers 702-706 and temporal scalar
708. In some examples,
banks of coordinate transformers (e.g., coordinate transformers 702-706) may
be implemented and are not
limited to the quantity, type, or functions shown. Various types of motions
associated with bodily limbs and
appendages may be measured, at a fixed angular rate (i.e., fixed co), using
coordinate transformers 702-706.
As shown, coordinate transformers 702-706 may be configured to receive motion
signals that are
algorithmically processed to identify one or more motion sub-signals. In some
examples, each of coordinate
transformers 702-706 may be associated with a particular angular rate. When
introduced to temporal scalar
708, the rate of information production for lower angular rates may be
reduced, which may lead to a near-
constant critical distance, which in turn may be used to generate various
types of vectors (e.g., temporal, =
spatial, and others) for purposes of determining motion calculations that may
be used to identify various
types of motion. Such vectors can provide both magnitude and directional
components of motion for other
algorithmic processing functions (e.g., vector analysis, Fourier
transformations, and others) to determine
various aspects associated with motion, such as velocity, speed, rate of
change, axis, and others, and for
analyses of data transformed or otherwise derived from sensory input to, for
example, sensor 212 (FIG. 2A).
Using motion sub-signals and banks (i.e., logical groupings) of coordinate
transformers,
transformation processes or functions may be performed on input (i.e., motion
signals that have been
quantitatively reduced to vectors or other measurable quantities or types) in
order to facilitate the production
of data that may be used to process other functions associated with wearable
devices such as band 200. As
an example, a body may be evaluated as a linked set of rigid "beams" (i.e.,
limbs or other bodily parts,
taking into account quantitative variables for moments and inertia) that are
connected or coupled by
rotational joints. By measuring the length of a "beams," different angular
rate dynamics can occur and may
be determined, or otherwise processed, using sysfem 700. Measurements of
angular rate dynamics may
allow for the extraction of data from body-worn accelerometers in an efficient
manner resulting from a
reduction in the use of space for electrical, electronic, and logic-based
components for performing these
calculations or otherwise manipulating motion signals. Further, system 700 may
be used to reduce power
18
CA 02817145 2013-05-06
WO 2012/171032 PCT/US2012/041958
consumption, memory accesses and operations, and the number of operations
performed over a given length
of time (e.g., 1VIIPS).
In other examples, different techniques may be used to advantageously improve
the processing
capabilities of system 700 and, for example, band 200. For example, different
sensors coupled to or in data
communication with band 200 may monitor or sense the same or substantially
similar sensory input.
Generally, signals from different sensors (e.g., sensor 212 (FIG. 2A)) may
illustrate some degree of
correlation, but noise measurements may be uncorrelated. For example, an
accelerometer may show noise
resulting from the movement of a structure to which it is attached (e.g., a
wearable device), but a
microphone may show acoustic noise emanating from a 'given environment. By
using one- or multiple
sensors in combination with the described techniques, it may be possible to
reject noise and accentuate a
signal generated from multiple domains (e.g., different sensors having
different sample rates, frequency
responses, ranges, or the like). In still other examples, system 700 and the
above-described elements may
be varied and are not limited to those provided.
FIG. 8 illustrates an exemplary determinative process for wearable devices.
Here, process 800
begins by receiving data associated with an event (802). In some examples, a
wearable device (e.g., bands
104-112 (FIG. 1), wearable device 220 (FIG. 2B), and the like) may be
configured to gather, or capture, the
data associated with the event. In other examples, data may comprise, or
otherwise be associated with,
sensory input detected by a sensor, for example, coupled to a wearable device.
In some examples, an event
may be a part of, or otherwise associated with, an activity (e.g., running,
walking, sleeping, working,
swimming, cycling, or the like). In other examples, an event may be a part of,
or otherwise associated with,
a biological state, a physiological state, a psychological state, or the like.
Once received, data may be
evaluated to determine a state associated with a user of a wearable device
(804). In some examples, data
may be received and evaluated using a recommendation engine (e.g.,
recommendation engine 602). In other -
examples, data may be received and evaluated using a different engine or unit
in communication with a
recommendation engine. In some examples, a state may be determinative of a
user's mood, emotional or
physical state or status, biological condition, medical condition, athletic
form, or the like. In some
examples, evaluating data may include determining various types of information
using the data. For
example, data may be used to determine a type of activity associated with an
event, a level of activity
associated with an event, a value associated with an event, or other
information. Once evaluated, data may
then be used to generate a recommendation, as described above in connection
with FIGs. 2A and 6 (806). In
some examples, a recommendation may be generated by a recommendation engine
(e.g., recommendation
engine 602) implemented on a wearable device. In other examples, a
recommendation engine (e.g.,
recommendation engine 602) for generating a recommendation may be implemented
on another device in
data communication with a wearable device. In some examples, a state that is
determined also may be
compared to one or more other states (i.e., stored in a memory or database
accessible by a recommendation
engine) to identify another recommendation associated with the event. In some
examples, a wearable
device may include a user interface configured to display graphics, or
otherwise provide notifications or
prompts (e.g., through sounds, vibrations, or other sensory communication
methods), associated with a
19
CA 02817145 2013-05-06
WO 2012/171032 PCT/US2012/041958
recommendation. In other examples, the above-described process may be varied
in function, order, process,
implementation, or other aspects and is not limited to those provided.
FIG. 9 illustrates another exemplary determinative process for wearable
devices. Here, a motion
may be evaluated to determine one or more motion signals (902). In some
examples, motion and motion
signals may be associated with movement of a limb or appendage. In some
examples, motion may be
detected by a sensor on a wearable device, and the wearable device may include
circuitry configured to
generate one or more motion signals. Once determined, motion signals may be
further isolated into motion
sub-signals (904) that, when evaluated may be used to determine spatial and
temporal vectors associated
with each motion sub-signal (906). In some examples, motions signals may be
isolated into motion sub-
signals using one or more coordinate transformers (e.g., coordinate
transformers 702-706). In some
examples, a motion signal may be processed according to one or more algorithms
configured to identify one
or more motion sub-signals. Using spatial and temporal vectors associated with
each motion sub-signal, a
data structure (or set of data structures) may be generated that may be used,
for example, to develop a model
or pattern associated with an activity or a state, from which recommendations
or other content, indicators, or
information, such as those described herein, may be generated (908). In some
examples, data structure may
be generated using vectors, or other data, output from a temporal scalar
(e.g., temporal scalar 708), which
may be configured to process motion signals or sub-signals to generate various
types of vectors that may be
used to identify and determine motion or types thereof. In other examples,
process 900 may be varied in
function, order, process, implementation, or other aspects and is not limited
to those provided.
FIG. 10 illustrates an exemplary computer system suitable for use with
determinative processes
for wearable devices. 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, LCD,
LED, OLED, elnk, or
reflective), input device 1016 (e.g., keyboard), and cursor control 1018
(e.g., mouse or trackball).
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.
CA 02817145 2013-05-06
WO 2012/171032
PCT/US2012/041958
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
1.000 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.
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.
21
