Neuro-Intermuscular Coordination Enhancement (NICE) Rehabilitation Through Human-Machine Interaction in Chronic Stroke

Part of paid clinical trials in Houston, Texas.

Sponsor
University of Houston
Study ID
NCT07531264
Phase
EARLY_PHASE1
Status
Not Yet Recruiting

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Conditions

  • Chronic Stroke-related Upper-extremity Motor Impairment
  • Motor Module-guided Rehabilitation Targeting Impaired Intermuscular Coordination and Motor Recovery

Eligibility Criteria

Sex
ALL
Age
21 Years - 80 Years
Healthy Volunteers
Accepted

Interventions

  • Neuromuscular coordination enhancement (NICE) intervention — OTHER
    Neuro-Intermuscular Coordination Enhancement (NICE) is a motor module-guided rehabilitation intervention designed to improve upper-extremity motor recovery after stroke by retraining impaired intermuscular coordination patterns. Participants perform isometric upper-extremity force-generation tasks using a human-machine interface while receiving real-time visual feedback derived from motor module recruitment signals calculated from surface electromyography (EMG). Individualized motor module targets are derived from the participant's less-affected upper extremity and used to guide selective recruitment of impaired coordination patterns in the more-affected upper extremity. Participants will complete 18 one-hour training sessions over six weeks (3 sessions/week). During training, participants perform repetitive target-matching tasks that require preferential recruitment of specific motor modules while minimizing unintended activation of non-target modules.
  • EMG Amplitude Biofeedback Exercise — OTHER
    EMG Amplitude Biofeedback Exercise is an active comparator rehabilitation intervention designed to improve upper-extremity motor function after stroke through targeted muscle activation training. Participants perform isometric upper-extremity exercises using a human-machine interface with real-time EMG amplitude-based visual feedback. Individualized muscle activation targets derived from the less-affected upper extremity guide training of the more-affected upper extremity. Participants will complete 18 one-hour sessions over 6 weeks (3 sessions/week).

Study Details

The objective of this study is to develop Neuro-Intermuscular Coordination Enhancement (NICE) rehabilitation, a novel neuromuscular control signal-guided strategy that visually guides stroke patients to individually activate motor modules through human-machine interaction. Ultimately, the development will lead to better clinical motor recovery, better quality of life, and lowered healthcare costs associated with the impairment.

Key Dates

First listed
Apr 15, 2026
Start date
Aug 31, 2027
Status verified
Jun 2026
Primary completion
Aug 31, 2032
Completion
Aug 31, 2032

Study Design

Enrollment
48 participants (estimated)
Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
TREATMENT

Arms

  • Experimental: Neuromuscular coordination enhancement (NICE) intervention
    Post-stroke participants will perform a center-out task by activating individual motor modules (generating coordinated isometric contractions of muscles) to move the cursor on a screen while electromyographic (EMG) signals are recorded. Activation of each muscle (or muscle group) will be mapped to 1 of 4 directions within the multi-dimensional cursor space. We will derive the cursor position in real time using Motor module activation magnitudes recorded from arm muscles.
  • Active Comparator: EMG-amplitude biofeedback exercise
    Participants will perform a center-out target matching tasks where individual muscle EMGs are used to move a cursor on the visual feedback display to match one of 4 different targets presented to them. Here, just the EMG amplitude, and not the coordination is focused on.

Primary Outcome Measure

Fugl-Meyer Assessment (FMA) score [ Time Frame: Baseline, six- week, 10-week, and 18-week follow-ups. ]

Central Contacts

Locations (1)

FacilityCityStateZIPSite coordinators
University of HoustonHoustonTexas77045
JIN-SOOK ROH, PhD
6173680050
Jinsook Roh, PhD (PRINCIPAL_INVESTIGATOR)

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