SMART WEARABLE HEALTH MONITOR SYSTEM

SYSTEME DE CONTROLE DE SANTE INTELLIGENT A PORTER

English Abstract

A smart wearable health monitoring system is disclosed that creates a
medical model of a target individual in a species based on a laser doppler
blood
vessel imaging scan and a plurality of sensors.

Claims

CLAIMS
What is claimed is:
1. A method comprising:
concurrently recording input data from a plurality of medical sensors that are

medically attached to a target individual of a species wherein the plurality
of medical
sensors comprise a first photoplethysmography device, a laser doppler blood
vessel
imaging device, a pulse rate sensor, a blood pressure sensor, a peripheral
capillary
oxygen saturation sensor, and a respiration rate sensor, wherein the recording
of the
input data lasts for at least 5 minutes;
parsing the input data to determine temporal correlations between input data
received from the first photoplethysmography device and input data received
from
one or more of the laser doppler blood vessel imaging device, the pulse rate
sensor,
the blood pressure sensor, the peripheral capillary oxygen saturation sensor,
and the
respiration rate sensor, wherein the temporal correlations correlate input
data from the
first photoplethysmography device to input data from the pulse rate sensor,
the blood
pressure sensor, the peripheral capillary oxygen saturation sensor and the
respiration
rate sensor;
loading the temporal correlations to a second photoplethysmography device;
after the recording, reading live data from the second photoplethysmography
device that is attached to the individual; and
determining medical data of the individual comprising a pulse rate of the
mammal, a blood pressure of the species, a peripheral capillary oxygen
saturation of
the individual, and a respiration rate of the individual according to temporal

correlations between the live data from the second photoplethysmography device
and
recorded input data; and
storing historical records of the medical data of the individual on a memory
device.
Date Recue/Date Received 2020-09-30

2.The method of claim 1 further comprising wirelessly transmitting the
historical
records to a remote computing device.
3.The method of claim 1, further comprising receiving one or more medical
threshold
values.
4.The method of claim 3, further comprising transmitting an alert to a remote
computing device in response to data in the historical records exceeding one
or more
of the medical threshold values.
5.The method of claim 1, wherein determining temporal correlations comprises
constructing a detailed micro blood vessel four dimensional image by fusing
data
from the photoplethysmography device and the recorded input data, and training
a
machine learning model on the input data to generate a medical model of the
individual.
Date Recue/Date Received 2020-09-30

Description

SMART WEARABLE HEALTH MONITOR SYSTEM
TECHNICAL FIELD OF THE INVENTION
[0001] The utility model relates to a smart wearable health monitoring device,
belonging to the field of Internet of Things technologies.
Date Recue/Date Received 2020-09-30

BRIEF DESCRIPTION OF THE DRAWINGS
[0002] The present invention is illustrated and described herein with
reference to the
various drawings, in which like reference numbers denote the various
components
and/or steps, as appropriate. The drawings illustrate example embodiments of
the
present disclosure and cannot be considered as limiting its scope.
[0003] FIG. 1 is a schematic diagram of the utility model, according to some
example embodiments.
[0004] FIG. 2 is a schematic diagram of the power module, according to some
example embodiments.
[0005] FIG. 3 is a flowchart of the machine learning model, according to some
example embodiments.
Date Recue/Date Received 2020-09-30

DETAILED DESCRIPTION
[0006] The measurement of vital signs is critical to the treatment and
management of
many medical conditions for a variety of target individuals or populations. A
smart
wearable health monitoring system capable of accurately and frequently
measuring
vital signs including body temperature, blood pressure, peripheral capillary
oxygen
saturation (Sp02), pulse rate, and respiration rate is described. The
invention will
utilize machine learning techniques to infer vital health signals more
accurately.
[0007] In various embodiments, the invention utilizes a Laser Doppler Blood
Vessel
Imaging (LDBVI) device to reconstruct an accurate 4-dimensional representation
of
the micro blood vessels in the targeted area. In combination with a portable
photoplethysmography (PPG) device (used to measure pulse oximetry in clinical
settings for pulse and oxygen saturation measurements) to gather data from
various
sensors and a customized deep learning model, the invention will generate a
personalized algorithm to better infer vital health signs in real time.
[0008] In various embodiments, the invention will first attach a custom LDBVI
device to a targeted surface area on the measured individual. Additional
sensors
including a digital blood pressure gauge and respiration sensors will be used
at this
stage. The data will be stored on a remote computing device to reconstruct a
detailed
4D micro blood vessel image and fused with other sensor readings. Using a
custom
data visualization platform and automated machine learning platform, the
invention
can quickly analyze the health-related data from the measured individual and
generate
a personalized baseline profile. By attaching a custom PPG wearable device to
the
measured individual, the invention can infer the vital health signals in real
time
through a custom algorithm.
[0009] In various embodiments, the invention will utilize machine learning
techniques to obtain more accurate vital health signals. A custom quantized
machine
learning model will run on the PPG device and process the sensor data in real
time to
infer measurements including pulse rate, blood pressure, 5p02, and respiration
rate.
The invention will utilize a Deep Neural Network (DNN) to generate a
correlation
function that converts PPG data in real time to identify key features
including systolic
blood pressure (SBP), diastolic blood pressure (DBP), 5p02, and respiration
rate. The
Date Recue/Date Received 2020-09-30

invention will utilize a Recurrent Neural Network (RNN) model to extract more
detailed vital signs from the 4D micro blood vessel time-series data captured
with the
LDBVI device to reconstruct patient's hemodynamics system. The invention will
use
this data to generate a specific baseline vital health signal data for each
measured
individual.
[0010] In various embodiments, the invention will track fluctuations to the
vital
health signal data through the PPG device. The invention will utilize machine
learning models to infer if variations from the baseline health signal data
are
significant in both measured individuals and populations.
[0011] Detailed Description (General Embodiment)
[0012] The utility model relates to a smart wearable health monitoring system,

comprising: a heart rate and blood oxygen sensor 106, a temperature sensor
107, an
accelerometer and piezo sensor 108, a microcontroller 102, a display screen
103, a
wireless module 104, a power module 101, and a user device 105, wherein the
various sensors feed the data to the microcontroller, then displays the data
on the
display screen, and sends the data to the user device by means of a wireless
module,
and the power module is configured to supply power to the microcontroller.
[0013] The power module comprises of: a battery 210, a power management
circuit
211, a charging port, and a charging station 212, where the battery is
connected to a
power management circuit which feeds power to the microcontroller 202, and the

battery is charged by a charging port which receives power from an external
charging
station.
EMBODIMENTS
[0014] Embodiment 1 refers to a smart wearable health monitoring system which
relates to measured individuals in a population.
[0015] Embodiment 2 refers to a smart wearable health monitoring system which
relates to marine animals.
[0016] Embodiment 3 relates to a smart wearable health monitoring system which

relates to a specific marine animal (key target species are: marine mammals,
fish
(salmon, etc.), lobster).
Date Recue/Date Received 2020-09-30

Representative Drawing