Optical sensing based upper-limb exoskeleton for patient rehab

This dissertation presents the design and development of a smart upper-limb rehabilitation exoskeleton for assisting elbow movement. The system uses an optical sensing approach, based on infrared LEDs and photodiodes, to detect biceps muscle contraction as an alternative to traditional surface EMG. The weak optical signal is converted and conditioned using a transimpedance amplifier and filtering circuit, then processed by a Feather M4 microcontroller to control a stepper motor in real time. A lightweight 1-DOF exoskeleton structure was designed and 3D printed to support elbow flexion and extension. The final prototype demonstrates the feasibility of using optical muscle sensing for wearable rehabilitation assistance, achieving real-time motor response and functional movement support under controlled testing conditions. The project also discusses limitations related to signal stability, sensor placement, calibration, and future improvements such as adaptive control and machine learning-based signal interpretation.