Enhanced Therapeutic Engagement: A Gamified Arduino Glove System for Hand Rehabilitation

This study integrates gamification with advanced sensor technology to enhance hand rehabilitation, focusing on fine and gross motor movements. The system uses an Arduinopowered glove with potentiometers and IMUs (Inertial Measurement Unit) to accurately record finger and hand motions. Our approach stands out by incorporating an initial assessment of hand function deficits and joint mobility limitations, allowing the rehabilitation process to be tailored to individual needs. Unlike similar systems, our method specifically targets both fine motor skills (small, precise movements) and gross motor skills (larger, broader movements) through customized games, addressing the unique challenges posed by post-stroke or orthopedic trauma. The pilot study, tested in healthy individuals, showed an increase in System Usability Scale (SUS) scores from 57.87 to 69.25, indicating improved user engagement. A strong correlation was found between the glove's measurements and manual goniometer readings for the MCP (Metacarpophalangeal) index finger (r = 0.712, p < 0.001), with no significant difference in measurements (t = 1.83, p = 0.076). These findings highlight the system's potential for accurate rehabilitation, though further calibration and clinical validation are needed.