Artificial Intelligence-assisted MDS-UPDRS Assessment for Parkinson's Disease

Sponsor
Hong Kong University of Science and Technology
Study ID
NCT07381751
Status
Recruiting
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Conditions

Eligibility Criteria

Sex
ALL
Age
18 Years - 95 Years
Healthy Volunteers
Not accepted

Interventions

  • Observational — OTHER
    clinical profile, MDS-UPDRS III, Video Recording

Study Details

Idiopathic Parkinson's disease (PD) is a neurodegenerative disease that progressively causes both motor and non-motor symptoms. As the second most common neurodegenerative disease and most common movement disorder, it affects over 8.5 million people worldwide and 13,000 people in Hong Kong. The most classical symptoms of PD are resting tremors, rigidity of the muscles, bradykinesia (slowing of movement), and gait difficulty. Other symptoms include sleep disorders, psychiatric symptoms, cognitive impairment, and autonomic dysfunction. Its pathophysiology is marked by the loss of dopaminergic neurons and the accumulation of aggregates called Lewy bodies. The severity of PD-related motor symptoms is usually semi-quantitatively ("normal", "slight", "mild", "moderate", and "severe") evaluated by expert physicians and physiotherapists according to the Movement Disorder Society-sponsored revision of the Unified Parkinson's Disease Rating Scale Part III (MDS-UPDRS III). However, the MDS-UPDRS III is semiquantitative and subjective, which might mask mild treatment effects or even provide false-positive results. Moreover, it takes significant time and effort for assessment with expected inter-observer variations. To address these issues, various artificial intelligence (AI) technologies and telemedicine approaches have been investigated for patient evaluation. However, previous studies did not incorporate items assessing rigidity and postural stability, which require physical contact as per the MDS-UPDRS III instructions. Zhu et al. explored a motor symptom machine-rating system for the complete MDS-UPDRS III. Nevertheless, they employed a depth camera and conducted the tests within a strictly controlled ideal laboratory environment. For the widespread implementation of AI-assisted rating, the RGB camera is a more accessible alternative.

Key Dates

First listed
Feb 2, 2026
Start date
Jun 1, 2026
Status verified
Jan 2026
Primary completion
Feb 28, 2029
Completion
Feb 28, 2029

Study Design

Enrollment
500 participants (estimated)

Arms

  • Arm: PD group
    patients with Parkinson's disease

Primary Outcome Measure

AI-based motor assessment tool [ Time Frame: Baseline to 3 years ]

Central Contacts

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