A Vision-Based Gesture and Eye-Blink Controlled Exoskeleton Robotic Hand for Rehabilitation of Paralyzed Patients

This work proposes a novel, sensorless dual-modality robotic hand exoskeleton controlled entirely through computer vision via MediaPipe healthy-hand gesture and eye-blink tracking, eliminating the need for complex, calibration-heavy wearable biosignal sensors (EEG/EMG). The system introduces an end-to-end hardware control pipeline using the Web Serial API and an ESP32 microcontroller to drive an assistive glove. Empirical validation shows that while gesture control offers faster response times, a 2.0-second temporal gating mechanism for eye-blink control yields 100% gate-adherence accuracy, providing a reliable, calibration-free, and flexible assistive solution for patients with varying degrees of residual motor function.