Design and Simulation of a Wireless EEG-Based Control System with Alpha Wave Extraction for Human Hand Prothesis Actuation

This paper proposes the design and simulation of an electronic system for the real-time extraction of alpha waves (8–13 Hz) from electroencephalographic (EEG) signals to control a human hand prosthesis. The EEG signals are acquired non-invasively and shaped through analog filtering and amplification stages modeled in NI Multisim . These signals are digitized via the ADC of a primary Arduino Uno microcontroller and transmitted wirelessly using Bluetooth HC-05 modules to a secondary Arduino Uno. The slave unit interprets the alpha wave activity to drive five HS-311 servomotors that simulate finger movements in a prosthetic hand. A touch sensor enhances contextual control, allowing the prosthesis to distinguish between grasping and releasing actions. LED indicators are used for feedback during signal detection and command execution. Preliminary simulations and experimental validations demonstrate the feasibility and responsiveness of the system in detecting mental intention and performing basic prosthetic movements. This work lays the foundation for a cost-effective, brain-controlled assistive device using accessible hardware.