Brain Computer Interface for Micro-controller Driven Robot Based on Emotiv Sensors

Abstract

A Brain Computer Interface (BCI) is developed to navigate a micro-controller based robot using Emotiv sensors. The BCI system has a pipeline of 5 stages-signal acquisition, pre-processing, feature extraction, classification and CUDA inter-facing. It shall aid in serving a prototype for physical movement of neurological patients who are unable to control or operate on their muscular movements. All stages of the pipeline are designed to process bodily actions like eye blinks to command navigation of the robot. This prototype works on features learning and classification centric techniques using support vector machine. The suggested pipeline, ensures successful navigation of a robot in four directions in real time with accuracy of 93 percent.

PyDSLRep: A domain-specific language for robotic simulation in V-Rep

“…Like Silva, other authors have established frameworks and methodologies for the control [11][12][13][14][15], planning [16][17][18], and communications [19][20][21] of robotic agents, but they present the characteristics of DSLs to reduce development time in a flexible and efficient manner, and at the same time, increasing autonomy between hardware and software [8]. This autonomy is dependent on the domain knowledge for which the robotic agents are being used; this is, the problem requirements, proposed objectives, and system restrictions.…”

IJIMAI Editor's Note - Vol. 4 Issue 5

“…In this area of knowledge, neural sciences, we have chosen three papers. The first one [7], introduces a brain computer interface for microcontroller driven robot based on emotiv sensors, which will be useful for patients who are unable to control or operate their muscular movements. The second one [11], explores the relationships and links between blood markers and personal history of substance abuse with neuropsychological performance.…”