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

January 26, 2026 updated by: Hiu Yi Wong, Hong Kong University of Science and Technology

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.

Study Overview

Status

Not yet recruiting

Conditions

Intervention / Treatment

Detailed Description

This is a single-center, prospective, observational study designed to develop and validate an AI-based MDS-UPDRS III assessment system using RGB camera data. Participants will be recruited from Queen Elizabeth Hospital's neurology outpatient clinic. Each subject will undergo standard MDS-UPDRS III evaluation by a certified clinician or physiotherapist, alongside synchronized RGB-D video recording. The videos will be processed through a deep learning pipeline trained to estimate the MDS-UPDRS III scores.

Blinded evaluations will be performed to compare AI-generated scores with ground truth clinician ratings. Statistical analysis will include inter-rater agreement metrics (e.g., ICC, Cohen's kappa), sensitivity to change, and subgroup analyses.

Study Type

Observational

Enrollment (Estimated)

500

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

  • Name: Hiu Yi Wong, PhD
  • Phone Number: +852-23587344
  • Email: annawong@ust.hk

Study Contact Backup

  • Name: Qian Zhang, PhD
  • Phone Number: +852-23588766
  • Email: qianzh@ust.hk

Study Locations

  • China
      • Hong Kong, China
        • Hong Kong University of Science and Technology
        • Principal Investigator:
          • Qian Zhang, PhD
        • Contact:
        • Contact:
          • Qian Zhang, PhD
          • Phone Number: +852-23588766
          • Email: qianzh@ust.hk

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

Sampling Method

Probability Sample

Study Population

patients with Parkinson's disease

Description

Inclusion Criteria:

  1. Age ≥18 years
  2. Diagnosis of "Clinically Established PD" as defined by the Movement Disorder Society Clinical Diagnostic Criteria for Parkinson's disease (MDS-PD criteria) [12]
  3. Able to provide informed consent and willing to participate in video-recorded MDS-UPDRS Part III assessments
  4. No significant visual, auditory, or musculoskeletal impairments that would interfere with video-based motor assessments

Exclusion Criteria:

  1. Unwillingness to be video recorded for study purposes
  2. History of neurodevelopmental disorder, neurodegenerative disease other than PD, CNS infection, neuroinflammatory disease (e.g. multiple sclerosis, CNS lupus), malignancy within the last 10 years, cerebrovascular accident, HIV infection, systemic autoimmune disease, alcohol dependence or other substance use

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort
Intervention / Treatment
PD group
patients with Parkinson's disease
Other: Observational
clinical profile, MDS-UPDRS III, Video Recording

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
AI-based motor assessment tool
Time Frame: Baseline to 3 years
AI-based motor assessment tool utilizing RGB video for reliable and objective ratings of MDS-UPDRS III motor symptoms, including rigidity and postural stability.
Baseline to 3 years
Feasibility of implementing RGB camera-based assessments
Time Frame: 3 years
Feasibility of implementing RGB camera-based assessments in routine clinical settings will be assessed by the proportion of assessments in which the AI system is able to generate an estimated MDS-UPDRS Part III total score based on RGB video that can be directly compared with clinician-rated MDS-UPDRS Part III scores. Patients perform standardized motor tasks under physician guidance while RGB video is recorded using a smartphone. Clinician-rated MDS-UPDRS Part III scores are used as the ground truth. Feasibility outcomes will be reported as the percentage (%) of assessments with valid AI-generated scores over a 3-year study period.
3 years

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
System's effectiveness
Time Frame: 3 years
System effectiveness in estimating motor symptom severity will be measured by the agreement between AI-predicted and clinician-rated MDS-UPDRS Part III scores. RGB video is recorded using a smartphone while patients perform standardized motor tasks under physician supervision. Clinician-rated MDS-UPDRS Part III scores are used as the ground truth. The AI system generates predicted MDS-UPDRS Part III total scores (range 0-108, with higher scores indicating more severe motor impairment). System effectiveness will be evaluated using F1 score, correlation between predicted and clinician-rated scores, and sensitivity and specificity for the detection of clinically significant motor impairment based on predefined score thresholds. Effectiveness outcomes will be reported over a 3-year study period.
3 years
Patient and clinician satisfaction
Time Frame: baseline to 3 years
Patient satisfaction with the AI-assisted assessment system will be assessed using a study-specific questionnaire administered after completion of RGB camera-based motor tasks. Questionnaire items are rated on a Likert scale, with higher scores indicating greater satisfaction. Clinician evaluation of the AI-assisted assessment system will be assessed using a study-specific questionnaire evaluating perceived credibility, perceived effectiveness, and overall satisfaction with the system. Questionnaire items are rated on a Likert scale, with higher scores indicating more positive evaluations. Patient and clinician evaluation outcomes will be reported as mean ± standard deviation over the study period.
baseline to 3 years
System's performance
Time Frame: baseline to 3 years
System performance will be measured by the accuracy and mean absolute error (MAE) of AI-predicted MDS-UPDRS Part III total scores compared with clinician-rated scores. Patients perform standardized motor tasks under physician supervision while RGB video is recorded using a smartphone. Clinician-rated MDS-UPDRS Part III scores are used as the ground truth. System performance is defined as the accuracy and MAE of AI predictions. Performance outcomes will be summarized over the study period.
baseline to 3 years

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Hong Kong University of Science and Technology

Collaborators

The Queen Elizabeth Hospital

Investigators

  • Principal Investigator: Qian Zhang, PhD, Hong Kong University of Science and Technology

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

General Publications

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Estimated)

March 1, 2026

Primary Completion (Estimated)

February 28, 2029

Study Completion (Estimated)

February 28, 2029

Study Registration Dates

First Submitted

January 13, 2026

First Submitted That Met QC Criteria

January 26, 2026

First Posted (Actual)

February 2, 2026

Study Record Updates

Last Update Posted (Actual)

February 2, 2026

Last Update Submitted That Met QC Criteria

January 26, 2026

Last Verified

January 1, 2026

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • HREP-2025-0238

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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