Interactive Platform for Hand Motor Rehabilitation Using Electromyography and Optical Tracking
Source abstract
Abstract
Functional hand rehabilitation requires adaptive and quantitative tools capable of addressing grip-specific challenges. This study presents Handly, an interactive virtual-reality (VR) platform that integrates surface electromyography (sEMG) and markerless optical tracking for the assessment and training of six functional grips (Card, Cylindrical, Spherical, Hook, Grain, Pencil). A total of 10 healthy adults (5 males, 5 females; 18–30 years) participated in a feasibility study involving virtual object manipulation tasks across three difficulty levels. Performance metrics included the execution time, success rate, and number of objects collected. An individualized calibration protocol based on root mean square (RMS) analysis was implemented, using standardized isometric contractions (125–147 N) measured with a handheld dynamometer to establish subject-specific dynamic thresholds. A repeated-measures ANOVA confirmed significant effects of grip type and task level on execution time (p<0.001, ηp2=0.68) and success rate (p<0.01, ηp2=0.54), whereas the number of objects collected showed no significant differences (p=0.12). These findings demonstrate that Handly can reliably discriminate functional differences in neuromotor performance while adapting to individual EMG activation profiles. Although EMG data were sampled at 100 Hz, this rate proved sufficient for amplitude-based event detection. The platform’s dual capacity for quantitative assessment and adaptive motor training supports its potential for personalized neurorehabilitation, pending clinical validation in populations with upper-limb impairments.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Muscle activation and electromyography studies · Stroke Rehabilitation and Recovery · EEG and Brain-Computer Interfaces
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Industrial and Manufacturing Engineering, Institute of Engineering and Technology, Autonomous University of Ciudad Juarez, Chihuahua 32310, Mexico
References (33)
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