{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,17]],"date-time":"2026-06-17T19:21:16Z","timestamp":1781724076351,"version":"3.54.5"},"reference-count":25,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2018,2,5]],"date-time":"2018-02-05T00:00:00Z","timestamp":1517788800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"KIST flagship","award":["2E27200"],"award-info":[{"award-number":["2E27200"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Most motion recognition research has required tight-fitting suits for precise sensing. However, tight-suit systems have difficulty adapting to real applications, because people normally wear loose clothes. In this paper, we propose a gait recognition system with flexible piezoelectric sensors in loose clothing. The gait recognition system does not directly sense lower-body angles. It does, however, detect the transition between standing and walking. Specifically, we use the signals from the flexible sensors attached to the knee and hip parts on loose pants. We detect the periodic motion component using the discrete time Fourier series from the signal during walking. We adapt the gait detection method to a real-time patient motion and posture monitoring system. In the monitoring system, the gait recognition operates well. Finally, we test the gait recognition system with 10 subjects, for which the proposed system successfully detects walking with a success rate over     93 %.<\/jats:p>","DOI":"10.3390\/s18020468","type":"journal-article","created":{"date-parts":[[2018,2,5]],"date-time":"2018-02-05T10:12:49Z","timestamp":1517825569000},"page":"468","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":52,"title":["Flexible Piezoelectric Sensor-Based Gait Recognition"],"prefix":"10.3390","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0239-2469","authenticated-orcid":false,"given":"Youngsu","family":"Cha","sequence":"first","affiliation":[{"name":"Center for Robotics Research, Korea Institute of Science and Technology, Seoul 02792, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hojoon","family":"Kim","sequence":"additional","affiliation":[{"name":"Center for Robotics Research, Korea Institute of Science and Technology, Seoul 02792, Korea"},{"name":"School of Electrical Engineering, Korea University, Seoul 02841, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Doik","family":"Kim","sequence":"additional","affiliation":[{"name":"Center for Robotics Research, Korea Institute of Science and Technology, Seoul 02792, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2018,2,5]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1192","DOI":"10.1109\/SURV.2012.110112.00192","article-title":"A survey on human activity recognition using wearable sensors","volume":"15","author":"Lara","year":"2013","journal-title":"IEEE Commun. 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