標題: IoT-Based Wireless Polysomnography Intelligent System for Sleep Monitoring
作者: Lin, Chin-Teng
Prasad, Mukesh
Chung, Chia-Hsin
Puthal, Deepak
El-Sayed, Hesham
Sankar, Sharmi
Wang, Yu-Kai
Singh, Jagendra
Sangaiah, Arun Kumar
資訊工程學系
Department of Computer Science
關鍵字: Polysomnography (PSG);JAVA;Internet of Things;wireless;sleep monitoring
公開日期: 1-一月-2018
摘要: Polysomnography (PSG) is considered the gold standard in the diagnosis of obstructive sleep apnea (OSA). The diagnosis of OSA requires an overnight sleep experiment in a laboratory. However, due to limitations in relation to the number of labs and beds available, patients often need to wait a long time before being diagnosed and eventually treated. In addition, the unfamiliar environment and restricted mobility when a patient is being tested with a polysomnogram may disturb their sleep, resulting in an incomplete or corrupted test. Therefore, it is posed that a PSG conducted in the patient's home would be more reliable and convenient. The Internet of Things (IoT) plays a vital role in the e-Health system. In this paper, we implement an IoT-based wireless polysomnography system for sleep monitoring, which utilizes a battery-powered, miniature, wireless, portable, and multipurpose recorder. A Java-based PSG recording program in the personal computer is designed to save several bio-signals and transfer them into the European data format. These PSG records can be used to determine a patient's sleep stages and diagnose OSA. This system is portable, lightweight, and has low power-consumption. To demonstrate the feasibility of the proposed PSG system, a comparison was made between the standard PSG-Alice 5 Diagnostic Sleep System and the proposed system. Several healthy volunteer patients participated in the PSG experiment and were monitored by both the standard PSG-Alice 5 Diagnostic Sleep System and the proposed system simultaneously, under the supervision of specialists at the Sleep Laboratory in Taipei Veteran General Hospital. A comparison of the results of the time-domain waveform and sleep stage of the two systems shows that the proposed system is reliable and can be applied in practice. The proposed system can facilitate the long-term tracing and research of personal sleep monitoring at home.
URI: http://dx.doi.org/10.1109/ACCESS.2017.2765702
http://hdl.handle.net/11536/144563
ISSN: 2169-3536
DOI: 10.1109/ACCESS.2017.2765702
期刊: IEEE ACCESS
Volume: 6
起始頁: 405
結束頁: 414
顯示於類別:期刊論文