{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,10]],"date-time":"2026-10-10T00:57:49Z","timestamp":1791593869343,"version":"4.3.4"},"reference-count":85,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,5,19]],"date-time":"2026-05-19T00:00:00Z","timestamp":1779148800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Aging Neurosci."],"abstract":"<jats:p>The accurate diagnosis of Parkinson's disease (PD) remains challenging due to the heterogeneity of motor symptoms and the reliance on subjective clinical assessments. Although biomarkers such as dopaminergic imaging, fluid assays, and genetic testing can support diagnosis, their clinical utility is limited by cost, accessibility, and low sensitivity to early motor changes. Consequently, diagnosis depends largely on clinical observation, highlighting the need for more accurate, objective, and integrable tools to detect early motor symptoms. Advances in wearable sensing and computational modeling offer opportunities to address this gap. Multimodal approaches combining inertial measurement units (IMUs) and surface electromyography provide complementary information on movement and neuromuscular control. Moreover, IMU-derived kinematics can drive personalized musculoskeletal simulations, generating digital twins that estimate internal biomechanical quantities not directly observable from wearable data alone. This perspective aims to synthesize evidence and outline a clinically grounded framework for multimodal data fusion in PD, in which wearable- and model-derived features can be jointly analyzed. This approach enables the construction of a feature space capturing kinematic, neuromuscular, and biomechanical aspects of motor dysfunction, from which discriminative digital biomarkers may be derived. Rather than proposing new sensing or modeling technologies, the novelty lies in advancing a targeted integration strategy that evaluates which wearable modalities\u2013and combinations\u2013are most suitable for quantifying PD and driving musculoskeletal digital twins. Importantly, the framework is grounded in a protocol co-designed with movement-disorder specialists, ensuring clinically meaningful task selection, workflow compatibility, feasibility, and patient acceptability from the outset, supporting more interpretable and personalized diagnostic strategies for PD.<\/jats:p>","DOI":"10.3389\/fnagi.2026.1774177","type":"journal-article","created":{"date-parts":[[2026,5,19]],"date-time":"2026-05-19T05:39:45Z","timestamp":1779169185000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Toward future diagnostics of Parkinson's disease: a perspective on multimodal motor assessment and personalized digital twins"],"prefix":"10.3389","volume":"18","author":[{"given":"J\u00falia","family":"Rey Vilches","sequence":"first","affiliation":[{"name":"Department of Electrical and Photonics Engineering, Technical University of Denmark","place":["Kongens Lyngby, Denmark"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sadasivan","family":"Puthusserypady","sequence":"additional","affiliation":[{"name":"Department of Health Technology, Technical University of Denmark","place":["Kongens Lyngby, Denmark"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bo","family":"Biering-S\u00f8rensen","sequence":"additional","affiliation":[{"name":"Movement Disorder and Pain Research Center, Department of Neurology, Copenhagen University Hospital","place":["Rigshospitalet, Glostrup, Denmark"]},{"name":"Department of Public Health, Faculty of Health and Medical Sciences, University of Copenhagen","place":["Copenhagen, Denmark"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Trine H\u00f8rmann","family":"Thomsen","sequence":"additional","affiliation":[{"name":"Department of Health Technology, Technical University of Denmark","place":["Kongens Lyngby, Denmark"]},{"name":"Movement Disorder and Pain Research Center, Department of Neurology, Copenhagen University Hospital","place":["Rigshospitalet, Glostrup, Denmark"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Silvia","family":"Tolu","sequence":"additional","affiliation":[{"name":"Department of Electrical and Photonics Engineering, Technical University of Denmark","place":["Kongens Lyngby, Denmark"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,5,19]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"197","DOI":"10.1016\/j.gaitpost.2021.08.026","article-title":"Effect of different walking speeds on joint and muscle force estimation using anybody and opensim","volume":"90","author":"Alexander","year":"2021","journal-title":"Gait Posture"},{"key":"B2","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1016\/B978-0-12-819531-4.00004-3","article-title":"\u201cIntroduction to musculoskeletal modelling,\u201d","volume-title":"Computational Modelling of Biomechanics and Biotribology in the Musculoskeletal System","author":"Andersen","year":"2021"},{"key":"B3","doi-asserted-by":"publisher","first-page":"113068","DOI":"10.1016\/j.jbiomech.2025.113068","article-title":"Model-based vs. measured muscle activity in dynamic lifting tasks with and without back-support exoskeletons","volume":"194","author":"Ashtiani","year":"2025","journal-title":"J. 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