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。

著者

岡田 志麻 藤原 義久 松浦 英文 安田 昌司 水貝 浩二郎 牧川 方昭 飯田 健夫

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.41, no.4, pp.493-497, 2003-12-10 (Released:2011-09-05)

参考文献数

6

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Sleep is very important to keep our physical condition healthy. Many studies have been devoted to clarify the mechanism of sleep and to monitor the sleep all night. In this study, we paid attention to heart activity during sleep and have developed a nonrestraint monitoring method of heart activity using an acceleration sensor set inside the coverlet. This method is easy for the use of sleep monitoring at home in daily life. An acceleration sensor was set inside the coverlet as it opposing to subject's left chest. Subjects were asked to lie in supine position and the coverlet with an acceleration sensor was put on the subject. Mechanical vibration from heart activity expected to be carried to the acceleration sensor through the coverlet. As a result, periodic vibration was measured successfully and this vibration was proved to be in high correlation with the R wave of ECG in six subjects. The same results were obtained even in case of lying in right and left lateral decubitus position.

著者

眞田 慎 岡田 志麻

出版者

公益社団法人 日本生体医工学会

雑誌

生体医工学

巻号頁・発行日

vol.55, no.3, pp.224-224, 2017

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<p>現在の日本において,聴覚・言語障害者が360,000人であるのに対して手話通訳士は3,406人となっており,聴覚障害者に比べて手話通訳士の人数が少なくなっている.この状況は,聴覚障害者と健聴者間の円滑なコミュニケーションを困難にし,聴覚障害者の積極的な社会参加を妨げる要因の一つとなっている.この問題を解決する手段として,本研究ではKinect v2を用いた手話通訳士を介さないリアルタイム手話通訳システムの開発を行った.また,手話動作の認識において動作者の表情が重要なパラメータとなることから,本システムでは腕の動きと手の形,表情の3つの状態を認識し,それぞれArms Motions,Hand States,Facial Expressionsパラメータとして動作データの取得を行う.さらに,取得した各パラメータデータの組み合わせから手話動作を特定し,通訳結果をモニター上にテキストで表示する.本研究では,各パラメータ認識手法の検証実験と通訳システムの実証実験を行った.検証実験の結果において,Arms Motionsで100%,Hand Statesで86%,Facial Expressionsで88%の認識精度が得られた.また,実証実験の結果において,3つのパラメータ認識手法を組み合わせた手話通訳システムを用いた手話単語の通訳に成功した.以上により,本システムの手話通訳における有効性が示された.</p>

著者

岡田 志麻 藤原 義久 松浦 英文 安田 昌司 水貝 浩二郎 牧川 方昭 飯田 健夫

出版者

社団法人日本生体医工学会

雑誌

生体医工学 : 日本エム・イー学会誌 (ISSN:1347443X)

巻号頁・発行日

vol.41, no.4, pp.493-497, 2003-12-10

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Sleep is very important to keep our physical condition healthy. Many studies have been devoted to clarify the mechanism of sleep and to monitor the sleep all night. In this study, we paid attention to heart activity during sleep and have developed a nonrestraint monitoring method of heart activity using an acceleration sensor set inside the coverlet. This method is easy for the use of sleep monitoring at home in daily life. An acceleration sensor was set inside the coverlet as it opposing to subject's left chest. Subjects were asked to lie in supine position and the coverlet with an acceleration sensor was put on the subject. Mechanical vibration from heart activity expected to be carried to the acceleration sensor through the coverlet. As a result, periodic vibration was measured successfully and this vibration was proved to be in high correlation with the R wave of ECG in six subjects. The same results were obtained even in case of lying in right and left lateral decubitus position.