Flexion and Extension Motion for Prosthetic Hand Controlled by Single-Channel EEG

Over the past few decades, many researchers have tried to connect the human brain to digital devices. Brain-Computer Interface (BCI) directly connects the human brain to digital computer devices and controls them by capturing electrical signals generated in the brain. One of the most commonly used devices on the BCI system is an electroencephalogram (EEG). It is part of a non-invasive BCI, where the electrode must be placed outside the skull or on the scalp. However, signal processing for EEG is not easy, and it needs a complex computation method. This study applied the single-channel electroencephalogram (EEG) signal as the input signal for a prosthetic hand. A myoelectric hand was developed using 3D printer technology and incorporated motion feedback by coupling a potentiometer to finger linkage. Attention signal was transmitted from the EEG headset to the Arduino microcontroller using Bluetooth. On-off feedback control was applied as a control system for driving the finger flexion and extension of the Anthropomorphic Prosthetic Hand. Based on the test result, the hand can be commended using single-channel EEG for flexion and extension motion on the prosthetic hand.