A Wearable Multisensor Patch for Breathing Pattern Recognition

加速度计 呼吸 压力传感器 计算机科学 呼吸频率 陀螺仪 可穿戴计算机 声学 人工智能 生物医学工程 工程类 医学 物理 嵌入式系统 心率 麻醉 航空航天工程 放射科 操作系统 血压 机械工程
作者
Partha Sarati Das,Hasnet Eftakher Uddin Ahmed,Fatemeh Motaghedi,Nicholas J. Lester,Abdelrahman Khalil,Mohammad Al Janaideh,Syed Anees,Tricia Breen Carmichael,Anthony R. Bain,Simon Rondeau‐Gagné,Mohammed Jalal Ahamed
出处
期刊:IEEE Sensors Journal [IEEE Sensors Council]
卷期号:23 (10): 10924-10934 被引量:12
标识
DOI:10.1109/jsen.2023.3264942
摘要

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.
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