The sensor patch is connected to a processor (circuit) that includes a Bluetooth module and is powered by a battery. The Bluetooth module allows the sensor patch to be linked to a phone to record data. Credit: Guren Matsumura, et al. Device. October 21, 2024
Edge computing
on a smartphone has been used to analyze data collected by a multimodal
flexible wearable sensor patch and detect arrhythmia, coughs and falls.
Wearable sensors are devices that can be worn on the
body and measure the state of the body. They are part of the Internet of Things
(IoT) and show great promise for monitoring health. These sensors generate
large amounts of data, and that data must be processed to be understood.
The field of computing dealing with processing these
data on the sensor or a device that the sensor is connected to—rather than at a remote server on the cloud—is called edge computing. Edge computing is a key element in wearable sensor technology.
A research team from Japan, led by Professor Kuniharu
Takei at Hokkaido University and Associate Professor Kohei Nakajima at The
University of Tokyo, have fabricated a flexible multimodal wearable sensor patch and
developed edge computing software that is capable of detecting arrhythmia,
coughs and falls in volunteers.
The sensor, which uses a smartphone as the edge
computing device, was described in a paper published in the journal Device.
"Our goal in this study was to design a
multimodal sensor patch that could process and interpret data using edge
computing, and detect early stages of disease during daily life," explains
Takei.
A demonstration of how the newly developed smart
sensor patch is paired to a phone to detect changes in various parameters, as
well as conditions such as arrhythmia, coughs and falls. Credit: Guren
Matsumura, et al. Device. October 21, 2024
The team fabricated sensors that monitor cardiac activity via
electrocardiogram (ECG), respiration, skin temperature, and humidity caused by
perspiration. After confirming their suitability for long-term use, the sensors
were integrated onto a flexible film (sensor patch) that adheres to human skin.
The sensor patch also included a Bluetooth module to connect to a smartphone.
The team first tested the capability of the sensor patch to detect
physiological changes in three volunteers, who wore it on their chests. The
sensor patch was used to monitor vital signs in the
volunteers under wet-bulb globe temperatures (used to determine likelihood of
heat stress) of 22°C and over 29°C.
"Although our test group was small, we could observe their vital signs change during time-series monitoring at high temperatures. This observation may eventually lead to the identifying symptoms of early-stage heat stress," Takei explains.
The smart sensor patch is fabricated on a supporting
film so that it may be peeled off and stuck onto the skin. Credit: Guren
Matsumura, et al. Device. October 21, 2024
The team
developed a machine learning program to process the recorded data to detect
other symptoms such as heart arrhythmia, coughing and falls. "In addition
to performing the analysis on a computer," Nakajima says, "we also
designed an edge computing application for smartphones that could perform the
same analysis. We achieved prediction accuracy of over 80%."
"The significant advance of this study is the
integration of multimodal flexible sensors, real-time machine learning data
analyses, and remote vital monitoring using a smartphone," Takei
concludes.
"One drawback of our system is that training could not be carried out on the smartphone, and had to be done on the computer; however, this can be solved by simplifying the data processing." This study advances the concept of a patched-based, edge-computing system for telemedicine or telediagnosis.
Source: Smart sensor patch detects health symptoms through edge computing
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