NCT07381751

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

Not yet recruiting Last updated 2 February 2026

What this trial tests

trial testing Observational in Parkinson Disease in 500 participants. Not yet recruiting.

Timeline

1 March 2026

Primary endpoint
28 February 2029

28 February 2029

Quick facts

Lead sponsor	Hong Kong University of Science and Technology
Status	Not yet recruiting
Study type	OBSERVATIONAL
Enrollment	500
Start date	1 March 2026
Primary completion	28 February 2029
Estimated completion	28 February 2029
Sites	1 location across China

Drugs / interventions tested

• Observational — full drug profile →

Conditions studied

• Parkinson Disease — all drugs for Parkinson Disease →

Sponsor

Hong Kong University of Science and Technology

Who can join

Adults 18 to 95, any sex, with Parkinson Disease. Patients with the condition only — healthy volunteers not accepted.

Sponsor's own description

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.

Publications & conference data

No peer-reviewed publications indexed yet for this trial.