模式识别(心理学)
睡眠(系统调用)
人工智能
朴素贝叶斯分类器
睡眠呼吸暂停
计算机科学
医学
语音识别
生物医学工程
模拟
计算机视觉
心脏病学
支持向量机
操作系统
作者
Mengxing Liu,Liping Qin,Shuming Ye
出处
期刊:PubMed
日期:2019-07-30
卷期号:43 (4): 243-247
被引量:5
标识
DOI:10.3969/j.issn.1671-7104.2019.04.003
摘要
Sleep posture recognition is the core index of diagnosis and treatment of positional sleep apnea syndrome. In order to detect body postures noninvasively, we developed a portable approach for sleep posture recognition using BCG signals with their morphological difference. A type of piezo-electric polymer film sensor was applied to the mattress to acquire BCG, the discrete wavelet transform with cubic B-spline was used to extract characteristic parameters and a naive Bayes learning phase was adapted to predict body postures. Eleven healthy subjects participated in the sleep simulation experiments. The results indicate that the mean error obtained from heart rates was 0.04±1.3 beats/min (±1.96 SD). The final recognition accuracy of four basic sleep postures exceeded 97%, and the average value was 97.9%. This measuring system is comfortable and accurate, which can be streamlined for daily sleep monitoring application.
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