{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T02:45:34Z","timestamp":1760237134896,"version":"build-2065373602"},"reference-count":22,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2020,3,5]],"date-time":"2020-03-05T00:00:00Z","timestamp":1583366400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100009105","name":"Ministry of Internal Affairs and Communications","doi-asserted-by":"publisher","award":["152302001"],"award-info":[{"award-number":["152302001"]}],"id":[{"id":"10.13039\/501100009105","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>This paper presents a novel bed-leaving sensor system for real-time recognition of bed-leaving behavior patterns. The proposed system comprises five pad sensors installed on a bed, a rail sensor inserted in a safety rail, and a behavior pattern recognizer based on machine learning. The linear characteristic between loads and output was obtained from a load test to evaluate sensor output characteristics. Moreover, the output values change linearly concomitantly with speed to attain the sensor with the equivalent load. We obtained benchmark datasets of continuous and discontinuous behavior patterns from ten subjects. Recognition targets using our sensor prototype and their monitoring system comprise five behavior patterns: sleeping, longitudinal sitting, lateral sitting, terminal sitting, and leaving the bed. We compared machine learning algorithms of five types to recognize five behavior patterns. The experimentally obtained results revealed that the proposed sensor system improved recognition accuracy for both datasets. Moreover, we achieved improved recognition accuracy after integration of learning datasets as a general discriminator.<\/jats:p>","DOI":"10.3390\/s20051415","type":"journal-article","created":{"date-parts":[[2020,3,6]],"date-time":"2020-03-06T07:33:46Z","timestamp":1583480026000},"page":"1415","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Development of Invisible Sensors and a Machine-Learning-Based Recognition System Used for Early Prediction of Discontinuous Bed-Leaving Behavior Patterns"],"prefix":"10.3390","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5485-2928","authenticated-orcid":false,"given":"Hirokazu","family":"Madokoro","sequence":"first","affiliation":[{"name":"Faculty of Systems Science and Technology, Akita Prefectural University, Yurihonjo City, Akita 015-0055, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1110-4342","authenticated-orcid":false,"given":"Kazuhisa","family":"Nakasho","sequence":"additional","affiliation":[{"name":"Faculty of Engineering, Yamaguchi University, Ube City, Yamaguchi 755-8611, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nobuhiro","family":"Shimoi","sequence":"additional","affiliation":[{"name":"Faculty of Systems Science and Technology, Akita Prefectural University, Yurihonjo City, Akita 015-0055, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8586-4304","authenticated-orcid":false,"given":"Hanwool","family":"Woo","sequence":"additional","affiliation":[{"name":"Faculty of Systems Science and Technology, Akita Prefectural University, Yurihonjo City, Akita 015-0055, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kazuhito","family":"Sato","sequence":"additional","affiliation":[{"name":"Faculty of Systems Science and Technology, Akita Prefectural University, Yurihonjo City, Akita 015-0055, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,3,5]]},"reference":[{"key":"ref_1","unstructured":"Takahashi, Y. 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