Wireless mobile robot control through human machine interface using brain signals

Abstract

Recent researches shows that Brain Computer Interface (BCI) technology provides effective way of communication between human and physical device. In this work, an EEG based wireless mobile robot is implemented for people suffer from motor disabilities can interact with physical devices based on Brain Computer Interface (BCI). An experimental model of mobile robot is explored and it can be controlled by human eye blink strength. EEG signals are acquired from NeuroSky Mind wave Sensor (single channel prototype) in non-invasive manner and Signal features are extracted by adopting Discrete Wavelet Transform (DWT) to amend the signal resolution. We analyze and compare the db4 and db7 wavelets for accurate classification of blink signals. Different classes of movements are achieved based on different blink strength of user. The experimental setup of adaptive human machine interface system provides better accuracy and navigates the mobile robot based on user command, so it can be adaptable for disabled people.