Design and evaluation of a P300-ERP based BCI system for real-time control of a mobile robot

2017

Full text Open access: Green Metadata (CSL-JSON)
DOI 10.1109/iww-bci.2017.7858177
Data confidence 70 medium
How this score is calculated

It is built from checkable properties of the record itself: whether the article has a DOI, how many independent sources confirmed its data, whether the required fields are filled in, and how recent the latest confirmation is. Disagreement between sources and a missing identifier lower it. A value of 80 or above means the record was published without further checking; 60 to 79 means it is published at reduced confidence, with a manual check advisable. A record verified by an editor by hand is never pushed below 90 by a recalculation. This scores our data about the article, not the article itself.

Abstract

With the development of Brain-Computer Interface (BCI) systems people with motor disabilities are able to control external devices using their thoughts. To control a device through BCI, brain activities of the user must be accurately translated to meaningful commands and a design of appropiate BCI paradigms play important roles in such tasks. This work presents a design and evaluation of a BCI system that is based on P300 Event-Related Potentials (ERP) in order to control a mobile robot platform into four directions (left, right, front, back). The ultimate goal of this research is to provide convienient way of controlling a mobile robot as an assistive home technology for disabled people. Low cost EPOC Emotiv headset was used in the BCI system to acquire brain signals with a Jaguar 4x4 Wheel robot as a control platform. We discuss a set of signal processing steps employed in detail and the utility of a regularized logistic regression classifier to detect visual stimuli induced P300 ERPs and, to control the Jaguar robot.