A Novel Method to Identify Obstructive Sleep Apnea Events via Mandible sEMG
It is important to identify OSA events accurately for estimating the severity of OSA. Polysomnography examination was complex and not friendly for sleep. This paper proposed a novel method to identify OSA events. Three-channel mandible sEMG and breathing waveform were recorded simultaneously, and FastICA algorithm was applied for decomposing the sEMG signals into three independent components, then to determinate the independent component which has maximum Pearson correlation coefficient with breathing waveform as genioglossus muscle EMG. When the genioglossus muscle EMG value drops to 10% of the maximum value of the individual’s maximum respiratory effort for more than 10 s, it is considered that an OSA event occurs once. Twenty-one OSA patients participated a controlled experiment, which demonstrates that there is no significant difference between the proposed method and Polysomnography examination (P = 0.1726). The proposed method to identify OSA events via mandible sEMG and breathing waveform was proved to be effective non-invasive, and more patient-friendly.
KeywordsObstructive sleep apnea Genioglossus muscle Breathing waveform Independent component analysis Electromyography
The authors acknowledge the support of Medicine Science Program for Young Scholars of PLA (Grant: 16QNP058) and Presidential Foundation of General Hospital of Jinan Military Command (Grant: 2015GL01).
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