Arduino: Used for building the rehabilitation device prototype, integrating sensors, and controlling the finger movement exercises.
Python: Utilized for data processing and analysis, as well as for creating scripts to monitor and manage rehabilitation progress.
CNN (Convolutional Neural Networks): Applied for analyzing sensor data and recognizing patterns in the finger movements, enhancing the device’s accuracy and responsiveness.
Sensors (e.g., flex sensors, pressure sensors): Integrated to track finger movement and provide real-time feedback during rehabilitation exercises.
Motor Control: Employed to actuate the mechanical components of the rehabilitation device for precise finger movement control.