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A Wearable Multisensor Patch for Breathing Pattern Recognition

delete2023-05-15
delete9
PRE
AI
P
Partha Sarati Das
H
Hasnet Eftakher Uddin Ahmed
F
Fatemeh Motaghedi
N
Nicholas J. Lester
M
Mohammad Al Janaideh
S
Syed Anees
T
Tricia Breen Carmichael
A
Anthony R. Bain
S
Simon Rondeau‐Gagné *
M
Mohammed Jalal Ahamed *
DOI:10.1109/JSEN.2023.3264942delete
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Abstract

Abstract

En 中文
In this article, a multisensor patch is presented for the purpose of detecting and recognizing the signals produced by human breathing in response to a variety of different body movements. We show that a multisensor patch consisting of an accelerometer and a pressure sensor can simultaneously measure breathing-related inertial motion and muscle stretch with a high degree of accuracy when it is attached close to the diaphragm. To construct the multisensor patch, we relied on commercially available off-the-shelf (COTS) electronic components that were relatively inexpensive. Different breathing motions were analyzed based on the accelerometer and the pressure sensor, including inhale, exhale, normal breathing, and breath hold conditions. The breathing frequency from the accelerometer and the flexible capacitive pressure sensors was found to be 0.2 Hz, and the normal breathing rate (BR) from the accelerometer and the pressure sensor was 11 breaths/min. We demonstrate that this new functional device and related approaches allow the identification of breathing patterns that are less cumbersome and tenably more reliable than conventional measures. The proposed multisensor patch holds great potential as a sensing technology in medical applications for early detection of respiratory changes, one of the most predictive and earliest vital signs for worsening health. The presented methodology can be adapted for mass production of reasonably priced noninvasive breathing pattern detection and off-line analysis.
Keywords:
Sensors
Accelerometers
Pressure sensors
Monitoring
Wearable sensors
Biomedical monitoring
Mechanical sensors
Accelerometer
breathing pattern recognition
pressure sensor
wearable

Journal

IEEE Sensors Journal cover
IEEE Sensors Journal
IF:
4.5
Papers:
2.2W
Citations:
7.3W

Organization

U
university of windsor
Scholars:
4.4K
Papers: 4.5K
Citations: 3
M
Memorial University Newfoundland
Scholars:
8.0K
Papers: 7.8K
Citations: 64
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