{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,28]],"date-time":"2026-09-28T23:46:49Z","timestamp":1790639209479,"version":"4.1.0"},"reference-count":39,"publisher":"SAGE Publications","issue":"7","license":[{"start":{"date-parts":[[2022,7,12]],"date-time":"2022-07-12T00:00:00Z","timestamp":1657584000000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Journal of Parkinson\u2019s Disease"],"published-print":{"date-parts":[[2022,7,12]]},"abstract":"<jats:sec>\n                    <jats:title>Background:<\/jats:title>\n                    <jats:p>Among motor symptoms of Parkinson\u2019s disease (PD), including rigidity and resting tremor, bradykinesia is a mandatory feature to define the parkinsonian syndrome. MDS-UPDRS III is the worldwide reference scale to evaluate the parkinsonian motor impairment, especially bradykinesia. However, MDS-UPDRS III is an agent-based score making reproducible measurements and follow-up challenging.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objective:<\/jats:title>\n                    <jats:p>Using a deep learning approach, we developed a tool to compute an objective score of bradykinesia based on the guidelines of the gold-standard MDS-UPDRS III.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods:<\/jats:title>\n                    <jats:p>We adapted and applied two deep learning algorithms to detect a two-dimensional (2D) skeleton of the hand composed of 21 predefined points, and transposed it into a three-dimensional (3D) skeleton for a large database of videos of parkinsonian patients performing MDS-UPDRS III protocols acquired in the Movement Disorder unit of Avicenne University Hospital.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results:<\/jats:title>\n                    <jats:p>We developed a 2D and 3D automated analysis tool to study the evolution of several key parameters during the protocol repetitions of the MDS-UPDRS III. Scores from 2D automated analysis showed a significant correlation with gold-standard ratings of MDS-UPDRS III, measured with coefficients of determination for the tapping (0.609) and hand movements (0.701) protocols using decision tree algorithms. The individual correlations of the different parameters measured with MDS-UPDRS III scores carry meaningful information and are consistent with MDS-UPDRS III guidelines.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion:<\/jats:title>\n                    <jats:p>We developed a deep learning-based tool to precisely analyze movement parameters allowing to reliably score bradykinesia for parkinsonian patients in a MDS-UPDRS manner.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3233\/jpd-223445","type":"journal-article","created":{"date-parts":[[2022,8,12]],"date-time":"2022-08-12T11:01:48Z","timestamp":1660302108000},"page":"2211-2222","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":25,"title":["Video-Based Automated Assessment of Movement Parameters Consistent with MDS-UPDRS III in Parkinson\u2019s Disease"],"prefix":"10.1177","volume":"12","author":[{"given":"Ga\u00ebtan","family":"Vignoud","sequence":"first","affiliation":[{"name":"Center for Interdisciplinary Research in Biology (CIRB), Coll\u00e8ge de France, CNRS, INSERM, Universit\u00e9 PSL, Paris, France"},{"name":"INRIA Paris, MAMBA (Modelling and Analysis in Medical and Biological Applications), Paris, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cl\u00e9ment","family":"Desjardins","sequence":"additional","affiliation":[{"name":"APHP, H\u00f4pital Avicenne, H\u00f4pitaux Universitaires de Paris-Seine Saint Denis (HUPSSD), Department of Neurology, Sorbonne Paris Nord, NS-PARK\/FCRIN network, Bobigny, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Quentin","family":"Salardaine","sequence":"additional","affiliation":[{"name":"APHP, H\u00f4pital Avicenne, H\u00f4pitaux Universitaires de Paris-Seine Saint Denis (HUPSSD), Department of Neurology, Sorbonne Paris Nord, NS-PARK\/FCRIN network, Bobigny, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marie","family":"Mongin","sequence":"additional","affiliation":[{"name":"APHP, H\u00f4pital Avicenne, H\u00f4pitaux Universitaires de Paris-Seine Saint Denis (HUPSSD), Department of Neurology, Sorbonne Paris Nord, NS-PARK\/FCRIN network, Bobigny, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"B\u00e9atrice","family":"Garcin","sequence":"additional","affiliation":[{"name":"APHP, H\u00f4pital Avicenne, H\u00f4pitaux Universitaires de Paris-Seine Saint Denis (HUPSSD), Department of Neurology, Sorbonne Paris Nord, NS-PARK\/FCRIN network, Bobigny, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Laurent","family":"Venance","sequence":"additional","affiliation":[{"name":"Center for Interdisciplinary Research in Biology (CIRB), Coll\u00e8ge de France, CNRS, INSERM, Universit\u00e9 PSL, Paris, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bertrand","family":"Degos","sequence":"additional","affiliation":[{"name":"Center for Interdisciplinary Research in Biology (CIRB), Coll\u00e8ge de France, CNRS, INSERM, Universit\u00e9 PSL, Paris, France"},{"name":"APHP, H\u00f4pital Avicenne, H\u00f4pitaux Universitaires de Paris-Seine Saint Denis (HUPSSD), Department of Neurology, Sorbonne Paris Nord, NS-PARK\/FCRIN network, Bobigny, France"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2022,8,10]]},"reference":[{"key":"ref001","doi-asserted-by":"publisher","DOI":"10.1002\/mds.26424"},{"key":"ref002","doi-asserted-by":"publisher","DOI":"10.1002\/mds.27431"},{"key":"ref003","doi-asserted-by":"publisher","DOI":"10.1016\/j.parkreldis.2017.01.010"},{"key":"ref004","doi-asserted-by":"publisher","DOI":"10.1093\/brain\/awz344"},{"key":"ref005","doi-asserted-by":"publisher","DOI":"10.1002\/mds.22340"},{"key":"ref006","doi-asserted-by":"publisher","DOI":"10.1002\/mds.21198"},{"key":"ref007","doi-asserted-by":"publisher","DOI":"10.1002\/mds.20220"},{"key":"ref008","doi-asserted-by":"publisher","DOI":"10.1002\/mds.20640"},{"key":"ref009","doi-asserted-by":"publisher","DOI":"10.1002\/mds.28108"},{"key":"ref010","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2021.102179"},{"key":"ref011","doi-asserted-by":"publisher","DOI":"10.1002\/mds.27790"},{"key":"ref012","doi-asserted-by":"publisher","DOI":"10.1212\/WNL.0000000000011654"},{"key":"ref013","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuropsychologia.2018.03.006"},{"key":"ref014","doi-asserted-by":"publisher","DOI":"10.3233\/JPD-160878"},{"key":"ref015","doi-asserted-by":"publisher","DOI":"10.1080\/14737175.2018.1530593"},{"key":"ref016","first-page":"4693019","volume":"2020","author":"Lu 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