Personalized Rehabilitation Pathways to Maximal Motor Functional Return Through an AI Recovery Prediction System for Diverse Stroke Survivors
Trial ID: NCT06828679
Status: RECRUITING
Study type: INTERVENTIONAL
Phase: NA
Start date: 2025-07-01
Completion date: 2028-06-30
Sponsor: Chinese University of Hong Kong
Collaborators: The Hong Kong Polytechnic University; City University of Hong Kong; Hong Kong Baptist University; The University of Western Australia
Conditions: Acute Stroke Intervention; Acute Stroke; Acute Ischemic Stroke
Interventions: Acupuncture; control group; Robotic Training; Neuromuscular Electrical Stimulation Group
Locations: The Chinese University of Hong Kong
Countries: Hong Kong
Enrollment: 400
Age range: 65 Years - 80 Years
Sex: ALL

Summary:
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.

Eligibility criteria:
IInclusion Criteria:

* Age 65-80
* 1-6 months after onset of a first-time unilateral stroke rostral to midbrain
* Moderate-to-severe motor impairment of one upper limb (Fugl-Meyer Assessment for Upper Extremity of 10-50 out of 66);
* Able to provide written informed consent;
* Detectable electromyographic (EMG) activities in flexor digitorum-flexor carpi radialis and extensor digitorum-extensor carpi ulnaris muscle groups, with EMG from each muscle group exceeding 3 standard deviations above baseline mean. This last criterion is essential for successful NMES training

Exclusion Criteria:

* Unconscious or bed-bound;
* Uncontrollable diabetes;
* Anticipated non-adherence to treatment schedule;
* On cardiac pacemaker;
* Other severe comorbidities (heart/kidney failure, deranged liver function).

Outcomes:
Surface EMG Recordings; Kinematic recordings; Cortico-muscular Coherence (CMC) from Electroencephalography (EEG) and EMG