Jump to ContentJump to Main Navigation
Living machinesA handbook of research in biomimetics and biohybrid systems$
Users without a subscription are not able to see the full content.

Tony J. Prescott, Nathan Lepora, and Paul F.M.J Verschure

Print publication date: 2018

Print ISBN-13: 9780199674923

Published to Oxford Scholarship Online: June 2018

DOI: 10.1093/oso/9780199674923.001.0001

Show Summary Details
Page of

PRINTED FROM OXFORD SCHOLARSHIP ONLINE (www.oxfordscholarship.com). (c) Copyright Oxford University Press, 2019. All Rights Reserved. Under the terms of the licence agreement, an individual user may print out a PDF of a single chapter of a monograph in OSO for personal use (for details see www.oxfordscholarship.com/page/privacy-policy).date: 26 June 2019

Brain–machine interfaces

Brain–machine interfaces

Chapter:
(p.461) Chapter 49 Brain–machine interfaces
Source:
Living machines
Author(s):

Girijesh Prasad

Publisher:
Oxford University Press
DOI:10.1093/oso/9780199674923.003.0049

A brain–machine interface (BMI) is a biohybrid system intended as an alternative communication channel for people suffering from severe motor impairments. A BMI can involve either invasively implanted electrodes or non-invasive imaging systems. The focus in this chapter is on non-invasive approaches; EEG-based BMI is the most widely investigated. Event-related de-synchronization/ synchronization (ERD/ERS) of sensorimotor rhythms (SMRs), P300, and steady-state visual evoked potential (SSVEP) are the three main cortical activation patterns used for designing an EEG-based BMI. A BMI involves multiple stages: brain data acquisition, pre-processing, feature extraction, and feature classification, along with a device to communicate or control with or without neurofeedback. Despite extensive research worldwide, there are still several challenges to be overcome in making BMI practical for daily use. One such is to account for non-stationary brainwaves dynamics. Also, some people may initially find it difficult to establish a reliable BMI with sufficient accuracy. BMI research, however, is progressing in two broad areas: replacing neuromuscular pathways and neurorehabilitation.

Keywords:   BMI, EEG, event-related de-synchronization (ERD), event-related synchronization (ERS), steady-state visual evoked potential (SSVEP), P300, neurofeedback, non-stationary brainwaves dynamics

Oxford Scholarship Online requires a subscription or purchase to access the full text of books within the service. Public users can however freely search the site and view the abstracts and keywords for each book and chapter.

Please, subscribe or login to access full text content.

If you think you should have access to this title, please contact your librarian.

To troubleshoot, please check our FAQs , and if you can't find the answer there, please contact us .