Internet-Based Unobtrusive Tele-Monitoring System for Sleep and Respiration

被引:6
|
作者
Choi, Ahyoung [1 ]
Noh, Sangwoo [2 ]
Shin, Hangsik [3 ]
机构
[1] Gachon Univ, Dept Software, Seongnam 13120, South Korea
[2] Samsung Elect Co Ltd, S LSI Div, Hwaseong 18448, South Korea
[3] Chonnam Natl Univ, Dept Biomed Engn, Yeosu 59626, South Korea
关键词
Cloud computing; Remote monitoring; Servers; Biomedical monitoring; Medical services; Logic gates; biomedical telemetry; health information management; Internet of Things; remote monitoring; PATIENT; IMPLEMENTATION; TECHNOLOGIES; HOME;
D O I
10.1109/ACCESS.2020.2989336
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This research is about new advances in the application of remote bio-signal monitoring technology. An unobtrusive IoT bio-signal measurement system is attached to a bed using a very thin strip sensor, then the user & x2019;s sleep efficiency and respiration rate can be measured with accuracy similar to that of an existing FDA-approved sleep tracker. In particular, in this study, we propose a ubiquitous central monitoring system that links an existing, personal use, unobtrusive measurement system to cloud-based systems via WiFi transmission. The proposed monitoring system simultaneously collects, stores, and displays the data from multiple devices using a web server as well as PC and mobile platforms such as personal smart devices. In this study, we implemented a system for the real-time transmission and display of data from multiple unobtrusive systems and validated that there were no problems associated with sending and receiving data at distances of 300 km with around a one-second delay. In addition, we evaluated the tele-monitoring system & x2019;s data processing time, CPU usage, and memory usage as the number of users was increased. Each user transmits an average of 810 bytes of data including information such as user id, time stamp, data for each channel, respiration rate and sleep status. We observed that the average data processing time was 0.15 seconds, average CPU usage was 5.01 & x0025;, average memory usage was 0.1 & x0025; assuming 10 users connected simultaneously. These results are expected to be useful in guiding future similar personal, public, and clinical applications of this technology.
引用
收藏
页码:76700 / 76707
页数:8
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