Identification of Raw EEG Signal for Prosthetic Hand Application

This paper presents the identification of raw Electroencephalograph (EEG) signal for prosthetic hand application. The main aim of this study to identify the EEG signal from human brain in real time using Emotiv headset to control the prosthetic hand. Emotiv Epoc+ headset, Arduino Microcontroller and Prosthetic hand were the main equipment used in this work. The prosthetic hand movement in this work subjected only for opening and closing hand operation. This paper focuses on analyzing two different methodology of prosthetic hand controlling technique which is using the hand movement and facial expression technique. This study able to conclude that the raw EEG signal data obtained from facial expression method using eye blinking technique shows better performance in realtime for software and prosthetic hand integration by generating signal voltage peak more than 5000 μV compared to the usage of EEG data obtained from just hand movement technique.