{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,17]],"date-time":"2026-04-17T22:44:19Z","timestamp":1776465859257,"version":"3.51.2"},"reference-count":37,"publisher":"MDPI AG","issue":"22","license":[{"start":{"date-parts":[[2021,11,18]],"date-time":"2021-11-18T00:00:00Z","timestamp":1637193600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003725","name":"National Research Foundation of Korea","doi-asserted-by":"publisher","award":["2019R1G1A1009980"],"award-info":[{"award-number":["2019R1G1A1009980"]}],"id":[{"id":"10.13039\/501100003725","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Parkinson\u2019s disease (PD) is a common neurodegenerative disease, one of the symptoms of which is a gait disorder, which decreases gait speed and cadence. Recently, augmented feedback training has been considered to achieve effective physical rehabilitation. Therefore, we have devised a numerical modeling process and algorithm for gait detection and classification (GDC) that actively utilizes augmented feedback training. The numerical model converted each joint angle into a magnitude of acceleration (MoA) and a Z-axis angular velocity (ZAV) parameter. Subsequently, we confirmed the validity of both the GDC numerical modeling and algorithm. As a result, a higher gait detection and classification rate (GDCR) could be observed at a higher gait speed and lower acceleration threshold (AT) and gyroscopic threshold (GT). However, the pattern of the GDCR was ambiguous if the patient was affected by a gait disorder compared to a normal user. To utilize the relationships between the GDCR, AT, GT, and gait speed, we controlled the GDCR by using AT and GT as inputs, which we found to be a reasonable methodology. Moreover, the GDC algorithm could distinguish between normal people and people who suffered from gait disorders. Consequently, the GDC method could be used for rehabilitation and gait evaluation.<\/jats:p>","DOI":"10.3390\/s21227676","type":"journal-article","created":{"date-parts":[[2021,11,19]],"date-time":"2021-11-19T02:43:09Z","timestamp":1637289789000},"page":"7676","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Gait Disorder Detection and Classification Method Using Inertia Measurement Unit for Augmented Feedback Training in Wearable Devices"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1011-6985","authenticated-orcid":false,"given":"Hyeonjong","family":"Kim","sequence":"first","affiliation":[{"name":"Division of Mechanical Engineering, (National) Korea Maritime and Ocean University, Busan 49112, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ji-Won","family":"Kim","sequence":"additional","affiliation":[{"name":"Division of Biomedical Engineering, Konkuk University, Chungju 27478, Korea"},{"name":"BK21 Plus Research Institute of Biomedical Engineering, Konkuk University, Seoul 05029, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6871-2635","authenticated-orcid":false,"given":"Junghyuk","family":"Ko","sequence":"additional","affiliation":[{"name":"Division of Mechanical Engineering, (National) Korea Maritime and Ocean University, Busan 49112, Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,11,18]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"026113","DOI":"10.1063\/1.3147408","article-title":"Gait Dynamics in Parkinson\u2019s Disease: Common and Distinct Behavior among Stride Length, Gait Variability, and Fractal-like Scaling","volume":"19","author":"Hausdorff","year":"2009","journal-title":"Chaos Interdiscip. 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