Jeng, P.; Wang, L.; Hu, C.; Wu, D. A Wrist Sensor Sleep Posture Monitoring System: An
Automatic Labeling Approach. Preprints2019, 2019070060. https://doi.org/10.20944/preprints201907.0060.v1
APA Style
Jeng, P., Wang, L., Hu, C., & Wu, D. (2019). A Wrist Sensor Sleep Posture Monitoring System: An
Automatic Labeling Approach. Preprints. https://doi.org/10.20944/preprints201907.0060.v1
Chicago/Turabian Style
Jeng, P., Chaur-Jong Hu and Dean Wu. 2019 "A Wrist Sensor Sleep Posture Monitoring System: An
Automatic Labeling Approach" Preprints. https://doi.org/10.20944/preprints201907.0060.v1
Abstract
Sleep postures monitoring systems in the hospital aim at transforming sensing signals into quantitative data to characterize the sleep behaviors of the patient. However, a home-care sleep posture monitoring system needs to be user friendly. In this paper, we present iSleePost - a user-friendly home-care intelligent sleep posture monitoring system. We address the labor-intensive labeling issue of traditional machine learning approaches in the training phase. Our proposed mobile health (mHealth) system leverages the communications and computation capabilities of mobile phones for provisioning a continuous sleep posture monitoring service. Our experiments show that iSleePost can achieve 90 percent accuracy in recognizing sleep postures. More importantly, iSleePost demonstrates that an easily-wear wrist sensor can accurately quantify sleep postures.
Engineering, Electrical and Electronic Engineering
Copyright:
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