International Journal of Advance Computational Engineering and Networking (IJACEN)
.
Follow Us On :
current issues
Volume-12,Issue-1  ( Jan, 2024 )
Past issues
  1. Volume-11,Issue-12  ( Dec, 2023 )
  2. Volume-11,Issue-11  ( Nov, 2023 )
  3. Volume-11,Issue-10  ( Oct, 2023 )
  4. Volume-11,Issue-9  ( Sep, 2023 )
  5. Volume-11,Issue-8  ( Aug, 2023 )
  6. Volume-11,Issue-7  ( Jul, 2023 )
  7. Volume-11,Issue-6  ( Jun, 2023 )
  8. Volume-11,Issue-5  ( May, 2023 )
  9. Volume-11,Issue-4  ( Apr, 2023 )
  10. Volume-11,Issue-3  ( Mar, 2023 )

Statistics report
Apr. 2024
Submitted Papers : 80
Accepted Papers : 10
Rejected Papers : 70
Acc. Perc : 12%
Issue Published : 133
Paper Published : 1552
No. of Authors : 4025
  Journal Paper


Paper Title :
Controlling Vehicles Using EEG Signal and Eye-Arm Collaboration

Author :Mücahit Karaduman, Ali Karci

Article Citation :Mücahit Karaduman ,Ali Karci , (2020 ) " Controlling Vehicles Using EEG Signal and Eye-Arm Collaboration " , International Journal of Advance Computational Engineering and Networking (IJACEN) , pp. 25-30, Volume-8,Issue-5

Abstract : The researches and investigations on Brain signals get more popular in research areas. The remote controlling vehicles is the notice fiable research area in this concept. This study focused on this idea. In this study, electroencephalography (EEG) signals are firstly taken and analyzed. P300 potentials are taken into consideration when data are taken. The received data can be analyzed in real time by pre-processing step. The obtained EEG signals are classified by using entropy, route mean square, variance, expected value, max, min and standard deviation. For the control of the device, the closed eye and the arm standing below represent the first state, while the open eye and the air-standing arm represent the second state. In this way, in case of involuntary eye and arm movements, incorrect control of the device will be prevented. As a result of the study, the best classification result is obtained by ANN, while the best working time belongs to the proposed method. In this study, a person with proper muscular system can control the device. Moreover, for people with muscular system problems, the device can be brought to usable level with thought training for a while. Thus, the dream of 'remote control with thought' can be realized. Keywords - EEG, Brain Signal, Eye Movement, Machine Control.

Type : Research paper

Published : Volume-8,Issue-5


DOIONLINE NO - IJACEN-IRAJ-DOIONLINE-17154   View Here

Copyright: © Institute of Research and Journals

| PDF |
Viewed - 63
| Published on 2020-08-10
   
   
IRAJ Other Journals
IJACEN updates
Paper Submission is open now for upcoming Issue.
The Conference World

JOURNAL SUPPORTED BY