105 Investigation of EEG activity induced by self-initiated finger movement : A brain computer interface study

2007 ◽  
Vol 2007.45 (0) ◽  
pp. 9-10
Author(s):  
Xuxin TIAN ◽  
Hiroaki MIZUHARA ◽  
Akio GOFUKU
Keyword(s):  
Brain Computer Interface ◽  
Computer Interface ◽  
Finger Movement ◽  
Eeg Activity ◽  
Interface Study

scholarly journals Brain Controlled Wheelchair using EEG Headset

2021 ◽  
Vol 9 (12) ◽  
pp. 239-242
Author(s):  
Gagandeep Singh Siledar
Keyword(s):  
Brain Computer Interface ◽  
Physical Disabilities ◽  
Computer Interface ◽  
Raspberry Pi ◽  
Finger Movement ◽  
Body Parts ◽  
Moving Body

Abstract: In this paper, a brain controlled wheelchair has been designed which tends to reduce the complexity of movement for paralyzed people who are not capable of using various wheelchairs operating on technologies like joystick, finger movement or gesture controlled due to disability of moving body parts. The entire model is centrally based on Brain-computer Interface (BCI) combined with Raspberry Pi 3 and EEG sensor headset capture signals based on Neurosky mindwave technology which are further processed using MATLAB. Despite of the physical disabilities, this model will help quadriplegic patients to assist on their own and feel independent. Keywords: EEG, BCI, Matlab, Raspberry Pi, Neurosignal, NeuroSkyTechnology.

scholarly journals Imaginary Control of a Mobile Vehicle Using Deep Learning Algorithm: A Brain Computer Interface Study

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Amin Hekmatmanesh ◽  
Hamed Mohammadi Azni ◽  
Huapeng Wu ◽  
Mohsen Afsharchi ◽  
Ming Li ◽  
...  
Keyword(s):  
Deep Learning ◽  
Learning Algorithm ◽  
Brain Computer Interface ◽  
Computer Interface ◽  
Deep Learning Algorithm ◽  
Mobile Vehicle ◽  
Interface Study

scholarly journals BRAIN-COMPUTER-INTERFACE – SUPPORTED MOTOR IMAGERY TRAININTG FOR PATIENTS WITH HEMIPARESIS

2013 ◽  
Vol 12 (2) ◽  
pp. 30-39 ◽  
Author(s):  
O. A. Mokienko ◽  
P. D. Bobrov ◽  
L. A. Chernikova ◽  
A. A. Frolov
Keyword(s):  
Healthy Volunteers ◽  
Motor Imagery ◽  
Healthy Subjects ◽  
Brain Computer Interface ◽  
Computer Interface ◽  
Eeg Activity ◽  
Cortical Damage ◽  
Control Quality ◽  
Interface Control ◽  
Sensorimotor Rhythm

The aim of study was to assess the feasibility of motor imagery supported brain-computer interface in patients with hemiparesis. 13 patients with central paresis of the hand and 15 healthy volunteers were learning to control EEG-based interface with feedback. No differences on interface control quality were found between patients and healthy subjects. The trainings were accompanied by the desynchronization of sensorimotor rhythm. In patients with cortical damage the source of EEG-activity was dislocated.

scholarly journals SOURCES OF EEG ACTIVITY MOST RELEVANT TO PERFORMANCE OF BRAIN-COMPUTER INTERFACE BASED ON MOTOR IMAGERY

2012 ◽  
Vol 22 (1) ◽  
pp. 21-37 ◽  
Author(s):  
Alexander Frolov ◽  
Dušan Húsek ◽  
Pavel Bobrov ◽  
Alexey Korshakov ◽  
Lyudmila Chernikova ◽  
...  
Keyword(s):  
Motor Imagery ◽  
Brain Computer Interface ◽  
Computer Interface ◽  
Eeg Activity

scholarly journals A Review- Brain Controlled Wheelchair using EEG headset

2021 ◽  
Vol 9 (11) ◽  
pp. 267-270
Author(s):  
Gagandeep Singh Siledar
Keyword(s):  
Review Paper ◽  
Brain Computer Interface ◽  
Physical Disabilities ◽  
Computer Interface ◽  
Raspberry Pi ◽  
Finger Movement ◽  
Body Parts ◽  
Moving Body

Abstract: In this review paper, a brain controlled wheelchair models has been discussed which tends to reduce the complexity of movement for paralyzed people who are not capable of using various wheelchairs operating on technologies like joystick, finger movement or gesture controlled due to disability of moving body parts. The entire model is centrally based on Brain-computer Interface (BCI) combined with Raspberry Pi 3 and EEG sensor headset capture signals based on Neurosky mindwave technology which are further processed using MATLAB. Despite of the physical disabilities, this model will help quadriplegic patients to assist on their own and feel independent. Keywords: EEG, BCI, Matlab, Raspberry Pi, Neurosignal, NeuroSkyTechnology

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