Literature DB >> 30582549

EEG Signals-Based Longitudinal Control System for a Brain-Controlled Vehicle.

Yun Lu, Luzheng Bi.   

Abstract

Directly using brain signals to drive a vehicle may not only help persons with disabilities to regain driving ability but also provide a new alternative way for healthy people to control a vehicle. In this paper, we propose a new longitudinal control system based on electroencephalogram signals for brain-controlled vehicles (BCVs) by combining a user interface, a brain-computer interface (BCI) system, and a longitudinal control module. Driver-in-the-loop experiments were conducted by using two driving tests (i.e., the destination-approaching and car-following tests) with different subjects under two control conditions, i.e., the brain and manual control conditions. Experimental results show the feasibility of alone using brain signals to continuously perform the longitudinal control of a vehicle at a relatively high speed, at least for some users. This paper not only promotes the development of BCVs but also provides some insights into the research on how to apply BCIs to control other high-speed dynamic systems.

Entities:  

Year:  2018        PMID: 30582549     DOI: 10.1109/TNSRE.2018.2889483

Source DB:  PubMed          Journal:  IEEE Trans Neural Syst Rehabil Eng        ISSN: 1534-4320            Impact factor:   3.802


  2 in total

1.  A Comprehensive sLORETA Study on the Contribution of Cortical Somatomotor Regions to Motor Imagery.

Authors:  Mustafa Yazici; Mustafa Ulutas; Mukadder Okuyan
Journal:  Brain Sci       Date:  2019-12-13

2.  EEG-Controlled Wall-Crawling Cleaning Robot Using SSVEP-Based Brain-Computer Interface.

Authors:  Lei Shao; Longyu Zhang; Abdelkader Nasreddine Belkacem; Yiming Zhang; Xiaoqi Chen; Ji Li; Hongli Liu
Journal:  J Healthc Eng       Date:  2020-01-11       Impact factor: 2.682

  2 in total

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