三次元ビジョンセンサを用いた人物検出と呼吸推定

カテゴリ: 論文誌(論文単位)

グループ名: 【C】電子・情報・システム部門

発行日: 2018/07/01

タイトル(英語): Person Detection and Breath Estimation Using 3D Vision Sensor

著者名: 磯本　佳助（鳥取大学大学院持続性社会創生科学研究科），櫛田　大輔（鳥取大学大学院工学研究科(クロス情報科学研究センター)）

著者名(英語): Keisuke Isomoto (Graduate School of Sustainability Science, Tottori Univerisy), Daisuke Kushida (Graduate School of Engineering (Cross-Informatics Research Center), Tottori Univerisy)

キーワード: 睡眠時無呼吸症候群，非接触・非拘束，Kinect，FFT，背景差分法　　sleep apnea syndrome，non-contact/unconstrained，Kinect，FFT，background subtraction method

要約(英語): Sleep apnea syndrome (SAS: Sleep Apnea Syndrome) is well-known as a disease that falls into intermittent apnea when sleeping. The estimated number of patients with SAS is known to be about 2% (2-3 million) of the Japanese population, many patients are not aware because of the disease occurring during sleep. This paper proposes a method of extracting breathing frequency necessary for SAS diagnosis using time series data of distance information on 2D image obtained from 3D vision sensor. At this time, in order to accurately estimate the breathing frequency, the position of the subject is detected from the distance information, and the frequency analysis of the distance information is performed only for the position of the detected subject. By verification using healthy subjects, the authors confirmed that the proposed method can correctly acquire the position of the subject and can estimate the breathing frequency of the subject.

本誌: 電気学会論文誌C（電子・情報・システム部門誌） Vol.138 No.7 （2018）特集：平成29年電子・情報・システム部門大会

本誌掲載ページ: 927-933 p

原稿種別: 論文／日本語

電子版へのリンク: https://www.jstage.jst.go.jp/article/ieejeiss/138/7/138_927/_article/-char/ja/