Mind Controlled Wireless Robotic Arm Using Brain Computer Interface

摘要: Brain Computer Interface (BCI) provides an individual to communicate using brain activity through Electroencephalogram (EEG) for controlling devices. Robotic arm is one such application which assists physically challenged people in day activities. The proposed method helps interact and control the robotic wirelessly with user friendly interface. wireless module hardware interface used are cost effective. In this work, visual evoked potential based motor-imaginary hand movements like left, right, up down considered. Enobio-8 device acquiring EEG signals. Visual concept adapted signals from 14 healthy subjects of age group 20–23. These pre-processed a band pass filter 2 40Hz remove all artifacts. Multilevel wavelet transform extracting features specific interest. K-Nearest Neighbour (KNN), Linear Discriminant Analysis (LDA) Support Vector Machine (SVM) classifiers classifying movements. interfaced Arduino uno board it controlled via HC-05 Bluetooth module. results obtained LDA two scenarios: left/right up/down 87.5%. showed better performance when compared KNN SVM. accuracy 56% (left/right) 62% (up/down). SVM 81% 68% result promising bringing mind-controlled robots much closer human hand.