Identification of Sleep Stages Based on Body Movement Signals from RFMS

doi:10.12068/j.issn.1005-3026.2016.08.004

Abstract

Abstract: To reduce the burden of the traditional sleep monitoring system on human body， a non-contact sleep monitoring system based on microwave technique was developed， and a sleep stages recognition algorithm was proposed based on body movement signals from radio frequency motion sensors (RFMSs).The RFMS signals were processed by wavelet transform， then， the energy of signals was calculated by integral algorithm. Finally， the sleep stages such as wakefulness， light sleep， moderate sleep， deep sleep were recognized by discriminant analysis and threshold processing. The RFMS signals from 8 normal subjects， whose sleep were monitored for 46 days， were acquired， with their video information， TANITA sleep information， pulse wave， and respiration signals gathered synchronously. Compared with videos， the staging results of this system match 90% in wakefulness stage. In comparison with the results of TANITA， the results of the RFMS match 70% in other sleep stages.The results match 80% in comparison with the change modes of respiratory rate and heart rate at different sleep stages.

Key words: non-contact, sleep monitoring, sleep stage, body movement, RF

CLC Number:

TP274.1

XU Li-sheng， BO Hong-rui， ZHAO Jin-ye， DOU Yuan-zhu. Identification of Sleep Stages Based on Body Movement Signals from RFMS[J]. Journal of Northeastern University Natural Science, 2016, 37(8): 1079-1083.

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