Actively Recruiting

Phase Not Applicable
Age: 65Years - 80Years
All Genders
NCT06828679

Using AI Systems to Optimize the Clinical Outcome of Stroke Patients

Led by Chinese University of Hong Kong · Updated on 2025-12-22

400

Participants Needed

1

Research Sites

156 weeks

Total Duration

On this page

Sponsors

C

Chinese University of Hong Kong

Lead Sponsor

T

The Hong Kong Polytechnic University

Collaborating Sponsor

AI-Summary

What this Trial Is About

This project addresses the imminent challenge of providing adequate motor rehabilitation to a growing number of stroke survivors amidst the ageing population, decreasing age of stroke, and shortage of physical/occupational therapists in Hong Kong through AI and precision rehabilitation. To reduce the socioeconomic burden from the stroke survivors' loss of independence and their care (\>HK$15 billion/year), the efficacy of rehabilitation and efficiency of its delivery must be improved. These goals can be achieved by prescribing them with individually tailored rehabilitations predicted to yield maximal functional return. Defining a predictive model for such personalization remains challenging given the immense heterogeneity of stroke. The investigators aim to build an explainable AI system that predicts a subject's recovery potential and the treatment option that may realize this potential based on multi-modal pre-rehab assessments. Data from clinical, neuroimaging, neurophysiological, and multi-omic evaluations will be collected from stroke survivors (N≥400) before they undergo upper limb rehab with usual care, neuromuscular stimulation, robotic training, or acupuncture. Machine learning-extracted data features will be used to train decision-tree and neural-network AI algorithms for robust predictions. As soon as the model is validated, the investigators will deploy it to implement a personalized rehab program in the community. Our model's ability to predict the optimal intervention from a wide spectrum of input modalities distinguishes ours from previous less-than-accurate models. Our interdisciplinary team of 13 PIs with expertise in neurology, PT/OT, acupuncture, electrical/biomed. engineering, robotics, neuroscience, neuroimaging, multi-omics, data science, and clinical trial management will put us in a world-unique position to execute this project successfully and generate opportunities of interdisciplinary education. In the long run, our prediction system will accelerate marketization of new rehab strategies by facilitating their clinical-trial evaluations in more targeted subjects, thereby leading Hong Kong to be a future global hub of innovative rehabilitation.

CONDITIONS

Official Title

Using AI Systems to Optimize the Clinical Outcome of Stroke Patients

Who Can Participate

Age: 65Years - 80Years
All Genders

Eligibility Criteria

Eligible

You may qualify if you...

  • Age between 65 and 80 years
  • Stroke occurred 1 to 6 months ago affecting one side of the brain
  • Moderate to severe motor impairment in one upper limb (Fugl-Meyer score 10-50 out of 66)
  • Able to provide written informed consent
  • Detectable muscle activity on EMG in specific forearm muscles above 3 standard deviations from baseline
Not Eligible

You will not qualify if you...

  • Unconscious or bedridden
  • Uncontrollable diabetes
  • Expected inability to follow treatment schedule
  • Having a cardiac pacemaker
  • Severe other health problems such as heart failure, kidney failure, or abnormal liver function

AI-Screening

AI-Powered Screening

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Trial Site Locations

Total: 1 location

1

The Chinese University of Hong Kong

Hong Kong, Sha Tin, Hong Kong, 852

Actively Recruiting

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Research Team

Y

Yat Sing Kelvin Lau, MSc

CONTACT

How is the study designed?

Study Type

INTERVENTIONAL

Masking

DOUBLE

Allocation

RANDOMIZED

Model

PARALLEL

Primary Purpose

SUPPORTIVE_CARE

Number of Arms

4

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