A Mattress System of Recognizing Sleep Postures Based on BCG Signal.
10.3969/j.issn.1671-7104.2019.04.003
- Author:
Mengxing LIU
1
;
Liping QIN
2
;
Shuming YE
1
Author Information
1. College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, 310027.
2. Zhejiang Institute for the Control of Medical Device, Hangzhou, 310018.
- Publication Type:Journal Article
- Keywords:
BCG;
Bayesian classification;
sleep apnea;
sleep posture;
wavelet transform
- MeSH:
Bayes Theorem;
Beds;
Humans;
Polysomnography;
instrumentation;
Posture;
Sleep;
Sleep Apnea Syndromes;
diagnosis
- From:
Chinese Journal of Medical Instrumentation
2019;43(4):243-247
- CountryChina
- Language:Chinese
-
Abstract:
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.
