Finding Nursing Interval from Mobile Sensors Attached to Nurses

• Item type: SIG Technical Reports(1)
• 公開日: 2013-03-07
• タイトル: Finding Nursing Interval from Mobile Sensors Attached to Nurses
• タイトル / 言語: en
• タイトル: Finding Nursing Interval from Mobile Sensors Attached to Nurses
• 言語: eng
• キーワード / 主題Scheme: Other
• キーワード / 主題: 位置推定・経路推定
• 資源タイプ / 資源タイプ識別子: http://purl.org/coar/resource_type/c_18gh
• 資源タイプ: technical report
• 著者所属: Kyushu Institute of Technology
• 著者所属: Kyushu Institute of Technology
• 著者所属: Kyushu University Hospital
• 著者所属: Kyushu University Hospital
• 著者所属(英): en
• 著者所属(英): Kyushu Institute of Technology
• 著者所属(英): en
• 著者所属(英): Kyushu Institute of Technology
• 著者所属(英): en
• 著者所属(英): Kyushu University Hospital
• 著者所属(英): en
• 著者所属(英): Kyushu University Hospital
• 著者名: Masato, Nakamura; Sozo, Inoue; Yasunobu, Nohara; Naoki, Nakashima
• 著者名(英): Masato, Nakamura; Sozo, Inoue; Yasunobu, Nohara; Naoki, Nakashima
• 論文抄録 / 内容記述タイプ: Other
• 論文抄録 / 内容記述: In this paper, we propose a method for finding intervals of nursing activitivies from accelerometers and audio on mobile sensors which are attached to nurses in reality. If we can find the intervals of nursing activities correctly, it helps the data to be used for machine learning for activity recognition. We have extracted the times of nursing interactions between nurses and patients by A) recognize walking activity from accelerometers, B) recognize if s/he is in the patient's room or not at each time duration divided by walking activities, from the environmental noise levels of sounds, and, C) for the duration where s/he is assumed to be in the patient's room, apply voice activity detection by fundamental frequencies using Cepstrum method, and extract the duration in which a person speaks. As a result of the experience for 300sec of sensor data, we observed sufficient accuracy for each step of A)-C), and could reduce the time to 11.9% without no missing.
• 論文抄録(英) / 内容記述タイプ: Other
• 論文抄録(英) / 内容記述: In this paper, we propose a method for finding intervals of nursing activitivies from accelerometers and audio on mobile sensors which are attached to nurses in reality. If we can find the intervals of nursing activities correctly, it helps the data to be used for machine learning for activity recognition. We have extracted the times of nursing interactions between nurses and patients by A) recognize walking activity from accelerometers, B) recognize if s/he is in the patient's room or not at each time duration divided by walking activities, from the environmental noise levels of sounds, and, C) for the duration where s/he is assumed to be in the patient's room, apply voice activity detection by fundamental frequencies using Cepstrum method, and extract the duration in which a person speaks. As a result of the experience for 300sec of sensor data, we observed sufficient accuracy for each step of A)-C), and could reduce the time to 11.9% without no missing.
• 書誌レコードID / 収録物識別子タイプ: NCID
• 書誌レコードID / 収録物識別子: AA11838947
• 書誌情報: 研究報告ユビキタスコンピューティングシステム（UBI）; 巻 2013-UBI-37, 号 47, p. 1-4, 発行日 2013-03-07
• Notice: SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc.
• 出版者 / 言語: ja
• 出版者: 情報処理学会