Robotic Vehicle Control Using Brain Computer Interface

Abstract

Brain Computer Interface (BCI) is an interfacing device that interacts with external device or computer. The principle of Brain Computer interface is based on Electroencephalography. Under the influence of external stimuli, human brain generates some responses on distinctive areas of the brain. These responses appear in the EEG signals captured from corresponding electrode positions on the scalp of the human subject. The responses appear in the EEG signal as a feature in the time domain, or a feature in the frequency domain depending upon the periodic nature of the stimuli. These features are then detected classified and then control signal is generated by an external device. This enables the subject to directly control an external device from the brain using the signals generated in response to stimulation. Brain-computer Interfcae has shown promising application to aid patients with Locked-in syndrome, Spinal Cord Injury (SCI), Acute Inflammatory Demyelinating Polyradiculoneuropathy (AIDP), Lock-down Syndrome and Amyotrophic Lateral Sclerosis (ALS). Until now, these patients needed human assistance to communicate. Brain-computer interface also has promising application for wheelchair control. Where these patients would be able to control electric wheelchairs using Brain Computer interface. In this work, a working model of Brain Computer Interface has been developed using PowerLab 16/35 and ML-138 bio-amplifier. The BCI is based on Steady State Visually Evoked Potential (SSVEP). SSVEP response is generated from the visual cortex of the subject when the subject is exposed to a flickering light source. A model robotic platform has also been controlled using the detected SSVEP Signal.