{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,15]],"date-time":"2025-08-15T01:03:33Z","timestamp":1755219813209,"version":"3.43.0"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"type":"electronic","value":"9781643686080"}],"license":[{"start":{"date-parts":[[2025,8,7]],"date-time":"2025-08-07T00:00:00Z","timestamp":1754524800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,8,7]]},"abstract":"<jats:p>With the aging of the overall patient population, the incidence of patients developing delirium during hospitalization is increasing. This study aims to improve post-operative safety management and reduce the workload of nurses related to patient care. We have developed a monitoring system that uses 3D sensors to detect specific behaviors and motions that require attention in cases where patients exhibit abnormal behaviors, such as falls and self-removal of IV lines, and trigger alerts. In this paper, we present an algorithm for detecting dangerous motions. We use the point cloud data generated by the 3D sensors that collect 3D information. We analyze the motions of subjects based on changes in the point cloud data and tag specific human body motions and behaviors. When there are no obstacles in the imaging direction of the 3D sensors, we detect human body movements (supine position on the bed, half sitting up, and separated from the bed) with an F-measure of 98.33% and motions (thrashing limbs, touching mouth\/neck\/arms, no action) with an F-measure of 98.23%. We detect the basic motions that trigger alert notifications. However, the detection accuracy decreases depending on the imaging conditions and subject movements. We use invisible and safe near-infrared light for motion detection and recognition to perform imaging even after lights are turned off, without disturbing patients\u2019 sleep. Motion recognition using point cloud data is a privacy-friendly monitoring method with a low risk of acquiring personally identifiable information. In the future, we plan to verify the algorithm using actual patients and investigate the detection of motions in addition to those considered in this study.<\/jats:p>","DOI":"10.3233\/shti250864","type":"book-chapter","created":{"date-parts":[[2025,8,7]],"date-time":"2025-08-07T11:33:21Z","timestamp":1754566401000},"source":"Crossref","is-referenced-by-count":0,"title":["Development of Motion Detection Algorithm Using 3d Sensors for Patient Monitoring Support Service System"],"prefix":"10.3233","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6315-6078","authenticated-orcid":false,"given":"Masami","family":"Mukai","sequence":"first","affiliation":[{"name":"National Cancer Center Hospital, Division of Medical Informatics"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6494-2318","authenticated-orcid":false,"given":"Yukihiro","family":"Yoshida","sequence":"additional","affiliation":[{"name":"National Cancer Center Hospital, Department of Thoracic Surgery"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Masaya","family":"Yotsukura","sequence":"additional","affiliation":[{"name":"National Cancer Center Hospital, Department of Thoracic Surgery"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mieko","family":"Machida","sequence":"additional","affiliation":[{"name":"National Cancer Center Hospital, Department of Nursing"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Miyuki","family":"Kanemitsu","sequence":"additional","affiliation":[{"name":"National Cancer Center Hospital, Department of Nursing"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-6246-3134","authenticated-orcid":false,"given":"Yoshiaki","family":"Miura","sequence":"additional","affiliation":[{"name":"Takahata Precision Co., Ltd., Advanced Business Development & Promotion"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Katsuya","family":"Nagase","sequence":"additional","affiliation":[{"name":"Takahata Precision Co., Ltd., Advanced Business Development & Promotion"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yota","family":"Ozeki","sequence":"additional","affiliation":[{"name":"Takahata Precision Co., Ltd., Advanced Business Development & Promotion"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tomohisa","family":"Saito","sequence":"additional","affiliation":[{"name":"Takahata Precision Co., Ltd., Corporate Division"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Masato","family":"Kataoka","sequence":"additional","affiliation":[{"name":"Takahata Precision Co., Ltd., Advanced Business Development & Promotion"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shun-Ichi","family":"Watanabe","sequence":"additional","affiliation":[{"name":"National Cancer Center Hospital, Department of Thoracic Surgery"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","MEDINFO 2025 \u2014 Healthcare Smart \u00d7 Medicine Deep"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/SHTI250864","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,7]],"date-time":"2025-08-07T11:33:21Z","timestamp":1754566401000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/SHTI250864"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8,7]]},"ISBN":["9781643686080"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/shti250864","relation":{},"ISSN":["0926-9630","1879-8365"],"issn-type":[{"type":"print","value":"0926-9630"},{"type":"electronic","value":"1879-8365"}],"subject":[],"published":{"date-parts":[[2025,8,7]]}}}