著者

岡田 志麻 北川 将嗣 山本 康平 橘 素子 前野 蔵人

出版者

公益社団法人 日本生体医工学会

雑誌

生体医工学 (ISSN:1347443X)

巻号頁・発行日

vol.54, no.3, pp.139-144, 2016-06-10 (Released:2016-11-23)

参考文献数

16

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Sleep is essential for the maintenance of human life. Polysomnography (PSG) is a common method for the evaluation of sleep quality. However, the test requires attachment of many electrodes to the subject, and the constraint may cause great stress. Therefore, it is important to find a new method to free the subject from being burdened by electrodes;that is, to measure in an unconstraint and noncontact manner. In this study, we propose a new sleep measurement system using microwave sensing. The sensor detects body movements and respiratory movements in a noncontact manner. In this study, we analyzed sleep stage using PSG and simultaneously measured body movements and respiratory movements using a radio-frequency sensor. The mean and standard deviation of the number of body movements decreased, and the movements also became micro-movements when the degree of awakening decreased. The mean respiratory frequency did not change markedly in various sleep stages and showed little dispersion. The mean and standard deviation of the respiratory amplitude decreased as was observed for body movement, and the respiratory amplitude was stable when the degree of awakening decreased. We used the linear discriminant function to classify the sleep stages into:Wake, REM, Light and Deep sleep. The mean agreement rate was approximately 78% for four stages in total. Our results show that the sleep stages can be successfully estimated by body and respiratory movements during sleep.

著者

山本 康平 橘 素子 前野 蔵人 北川 正嗣 岡田 志麻

出版者

一般社団法人 人工知能学会

雑誌

人工知能学会全国大会論文集 第29回 (2015)

巻号頁・発行日

pp.1C22, 2015 (Released:2018-07-30)

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近年、加速度センサデバイスの普及により、簡便に睡眠深度を推定することが可能となってきている。しかし、これらのデバイスは利用者が意識的に装着や操作を行う必要がある。本報告では、マイクロ波を用いることで遠隔から非接触にて微細な呼吸動作を含む体動を計測し、それらからの特徴抽出と機械学習モデルを組み合わせることで、人体への装着や操作が不要な睡眠深度の推定技術を提案する。