A Mattress System of Recognizing Sleep Postures Based on BCG Signal / 中国医疗器械杂志
Chinese Journal of Medical Instrumentation
;
(6): 243-247, 2019.
Article
Dans Chinois
| WPRIM
| ID: wpr-772516
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.
Texte intégral:
Disponible
Indice:
WPRIM (Pacifique occidental)
Sujet Principal:
Posture
/
Sommeil
/
Syndromes d'apnées du sommeil
/
Lits
/
Théorème de Bayes
/
Polysomnographie
/
Diagnostic
Type d'étude:
Etude diagnostique
/
Étude pronostique
Limites du sujet:
Humains
langue:
Chinois
Texte intégral:
Chinese Journal of Medical Instrumentation
Année:
2019
Type:
Article
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