Abstract
Breathing pattern and heart rate can be major indicators of a person's physical condition, and an easy way to measure the vital signs can be useful in health monitoring. In this paper, we propose a new method for identifying the changes in breathing and heart rate pattern of a person using commercial WiFi devices. The amplitude of signal waves can represent the periodic up-and-down chest movements caused by breathing and heartbeat, and prominent changes of the signal pattern can be detected by using the Dynamic Time Warping algorithm. We verified the feasibility of the proposed method in real testbeds and evaluated the method through various experiments with 10 participants. The proposed method achieves 94% accuracy in identifying a subjects physical status. This low-cost method will be useful for monitoring our health in everyday life.
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