{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,27]],"date-time":"2026-06-27T07:14:25Z","timestamp":1782544465819,"version":"3.54.5"},"reference-count":31,"publisher":"Public Library of Science (PLoS)","issue":"1","license":[{"start":{"date-parts":[[2025,1,3]],"date-time":"2025-01-03T00:00:00Z","timestamp":1735862400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Multimedia University and Universitas Telkom Joint research grant","award":["MMUE\/210063"],"award-info":[{"award-number":["MMUE\/210063"]}]},{"name":"Fundamental Research Grant Scheme","award":["FRGS\/1\/2020\/ICT02\/MMU\/02\/5"],"award-info":[{"award-number":["FRGS\/1\/2020\/ICT02\/MMU\/02\/5"]}]}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS ONE"],"abstract":"<jats:p>Parkinson\u2019s Disease (PD) is a neurodegenerative disorder that is often accompanied by slowness of movement (bradykinesia) or gradual reduction in the frequency and amplitude of repetitive movement (hypokinesia). There is currently no cure for PD, but early detection and treatment can slow down its progression and lead to better treatment outcomes. Vision-based approaches have been proposed for the early detection of PD using gait. Gait can be captured using appearance-based or model-based approaches. Although appearance-based gait contains comprehensive features, it is easily affected by factors such as dressing. On the other hand, model-based gait is robust against changes in dressing and external contours, but it is often too sparse to contain sufficient information. Therefore, we propose a fusion of appearance-based and model-based gait features for PD prediction. First, we extracted keypoint coordinates from gait captured in videos and modeled these keypoints as a point cloud. The silhouette images are also segmented from the videos to obtain an overall appearance representation of the subject. We then perform a binary classification of gait as normal or Parkinsonian using a novel fusion of the gait point cloud and silhouette features, obtaining AUC up to 0.87 and F1-Scores up to 0.82 (precision: 0.85, recall: 0.80).<\/jats:p>","DOI":"10.1371\/journal.pone.0315453","type":"journal-article","created":{"date-parts":[[2025,1,3]],"date-time":"2025-01-03T18:43:46Z","timestamp":1735929826000},"page":"e0315453","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":2,"title":["Parkinson\u2019s disease screening using a fusion of gait point cloud and silhouette features"],"prefix":"10.1371","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0901-3831","authenticated-orcid":true,"given":"Tee","family":"Connie","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Timilehin B.","family":"Aderinola","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jia You","family":"Ong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5867-9517","authenticated-orcid":true,"given":"Thian Song","family":"Ong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michael Kah Ong","family":"Goh","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bayu","family":"Erfianto","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bedy","family":"Purnama","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ming De","family":"Lim","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6634-7934","authenticated-orcid":true,"given":"Nor Izzati","family":"Saedon","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2025,1,3]]},"reference":[{"issue":"10291","key":"pone.0315453.ref001","doi-asserted-by":"crossref","first-page":"2284","DOI":"10.1016\/S0140-6736(21)00218-X","article-title":"Parkinson\u2019s disease","volume":"397","author":"BR Bloem","year":"2021","journal-title":"The Lancet"},{"issue":"5","key":"pone.0315453.ref002","doi-asserted-by":"crossref","first-page":"385","DOI":"10.1016\/S1474-4422(21)00030-2","article-title":"Challenges in the diagnosis of Parkinson\u2019s disease","volume":"20","author":"E Tolosa","year":"2021","journal-title":"The Lancet Neurology"},{"key":"pone.0315453.ref003","first-page":"1","article-title":"Artificial intelligence-assisted reduction in patients\u2019 waiting time for outpatient process: a retrospective cohort study","volume":"21","author":"X Li","year":"2021","journal-title":"BMC health services research"},{"issue":"5","key":"pone.0315453.ref004","doi-asserted-by":"crossref","first-page":"498","DOI":"10.1111\/1754-9485.13273","article-title":"Deep learning applied to automatic disease detection using chest x-rays","volume":"65","author":"DA Moses","year":"2021","journal-title":"Journal of Medical Imaging and Radiation Oncology"},{"key":"pone.0315453.ref005","doi-asserted-by":"crossref","first-page":"571","DOI":"10.1007\/s10489-020-01826-w","article-title":"Deep transfer learning-based automated detection of COVID-19 from lung CT scan slices","volume":"51","author":"S Ahuja","year":"2021","journal-title":"Applied Intelligence"},{"key":"pone.0315453.ref006","doi-asserted-by":"crossref","unstructured":"Ebrahimi-Ghahnavieh A, Luo S, Chiong R. 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