{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,10]],"date-time":"2026-07-10T18:09:12Z","timestamp":1783706952043,"version":"3.55.0"},"reference-count":67,"publisher":"MDPI AG","issue":"19","license":[{"start":{"date-parts":[[2023,10,9]],"date-time":"2023-10-09T00:00:00Z","timestamp":1696809600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"The McCamish Center for Parkinson\u2019s Disease Innovation"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Characterizing motor subtypes of Parkinson\u2019s disease (PD) is an important aspect of clinical care that is useful for prognosis and medical management. Although all PD cases involve the loss of dopaminergic neurons in the brain, individual cases may present with different combinations of motor signs, which may indicate differences in underlying pathology and potential response to treatment. However, the conventional method for distinguishing PD motor subtypes involves resource-intensive physical examination by a movement disorders specialist. Moreover, the standardized rating scales for PD rely on subjective observation, which requires specialized training and unavoidable inter-rater variability. In this work, we propose a system that uses machine learning models to automatically and objectively identify some PD motor subtypes, specifically Tremor-Dominant (TD) and Postural Instability and Gait Difficulty (PIGD), from 3D kinematic data recorded during walking tasks for patients with PD (MDS-UPDRS-III Score, 34.7 \u00b1 10.5, average disease duration 7.5 \u00b1 4.5 years). This study demonstrates a machine learning model utilizing kinematic data that identifies PD motor subtypes with a 79.6% F1 score (N = 55 patients with parkinsonism). This significantly outperformed a comparison model using classification based on gait features (19.8% F1 score). Variants of our model trained to individual patients achieved a 95.4% F1 score. This analysis revealed that both temporal, spectral, and statistical features from lower body movements are helpful in distinguishing motor subtypes. Automatically assessing PD motor subtypes simply from walking may reduce the time and resources required from specialists, thereby improving patient care for PD treatments. Furthermore, this system can provide objective assessments to track the changes in PD motor subtypes over time to implement and modify appropriate treatment plans for individual patients as needed.<\/jats:p>","DOI":"10.3390\/s23198330","type":"journal-article","created":{"date-parts":[[2023,10,9]],"date-time":"2023-10-09T07:37:50Z","timestamp":1696837070000},"page":"8330","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Classifying Tremor Dominant and Postural Instability and Gait Difficulty Subtypes of Parkinson\u2019s Disease from Full-Body Kinematics"],"prefix":"10.3390","volume":"23","author":[{"given":"N. Jabin","family":"Gong","sequence":"first","affiliation":[{"name":"School of Computer Science, College of Computing, Georgia Institute of Technology, Atlanta, GA 30332, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gari D.","family":"Clifford","sequence":"additional","affiliation":[{"name":"Department of Biomedical Informatics, School of Medicine, Emory University, Atlanta, GA 30322, USA"},{"name":"Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, GA 30322, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christine D.","family":"Esper","sequence":"additional","affiliation":[{"name":"Jean and Paul Amos Parkinson\u2019s Disease and Movement Disorders Program, Department of Neurology, School of Medicine, Emory University, Atlanta, GA 30322, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stewart A.","family":"Factor","sequence":"additional","affiliation":[{"name":"Jean and Paul Amos Parkinson\u2019s Disease and Movement Disorders Program, Department of Neurology, School of Medicine, Emory University, Atlanta, GA 30322, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8361-8943","authenticated-orcid":false,"given":"J. Lucas","family":"McKay","sequence":"additional","affiliation":[{"name":"Department of Biomedical Informatics, School of Medicine, Emory University, Atlanta, GA 30322, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hyeokhyen","family":"Kwon","sequence":"additional","affiliation":[{"name":"Department of Biomedical Informatics, School of Medicine, Emory University, Atlanta, GA 30322, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,10,9]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"368","DOI":"10.1136\/jnnp.2007.131045","article-title":"Parkinson\u2019s disease: Clinical features and diagnosis","volume":"79","author":"Jankovic","year":"2008","journal-title":"J. Neurol. Neurosurg. 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