Development of upper limb exoskeleton for elbow rehabilitation systems with fingerprint recognition for personalization
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Abstract
This work aimed to develop an easy-to-use elbow rehabilitation system with fingerprint recognition to ensure personalized movement accuracy. The system featured fingerprint scanning for user identification, an LCD display, Arduino-based control with manual and automatic modes, and a motor-driven elbow support
(0–85°). Ten healthy participants, aged 13 to 45 years, tested this system while fingerprint accuracy, motion precision, cycle time consistency, and motor temperature (monitored via thermocouple) were evaluated. Fingerprint verification and system activation showed a total delay of 185.3 ms, with 100% success for all fingers in dry conditions, while wet conditions resulted in verification failure. Rehabilitation cycle time remained stable at 7.39 ± 0.11 s. Furthermore, motion error averaged 1.29%. Motor temperature stabilized at 44°C within 60 min, confirming continuous safe operation.
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