P300-based EEG signal interpretation system for robot navigation control
In recent years, Brain-Computer Interface (BCI) research has provoked an enormous interest among researchers from different fields. The most popular approach is a non-invasive method, using Electroencephalogram (EEG) analysis which acquires signals from the brain. The aim of this project is to devel...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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IDOSI Publications
2013
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| Online Access: | http://psasir.upm.edu.my/id/eprint/28694/ http://psasir.upm.edu.my/id/eprint/28694/1/P300.pdf |
| _version_ | 1848846187565678592 |
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| author | Hasan, Intan Helina Ramli, Abdul Rahman Ahmad, Siti Anom Osman, Rosiah |
| author_facet | Hasan, Intan Helina Ramli, Abdul Rahman Ahmad, Siti Anom Osman, Rosiah |
| author_sort | Hasan, Intan Helina |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | In recent years, Brain-Computer Interface (BCI) research has provoked an enormous interest among researchers from different fields. The most popular approach is a non-invasive method, using Electroencephalogram (EEG) analysis which acquires signals from the brain. The aim of this project is to develop a brain signal interpretation system that can convert one thought into multiple movements for mobile robot navigation. A signal interpretation system is designed and developed to receive the EEG signal via User Datagram Protocol (UDP) transmission, converts the signal to several robot commands that are pre-programmed according to the robot’s programming software and send the commands to the robot through the operating computer. Using signals from four electrodes to evaluate the signal interpretation system, a success rate of 75-80% is received, while a total response time of only 61 seconds needed by the system from the start of the stimuli until the robot has finished all commands sent by the system, as compared to the conventional method of one-thought-one-movement which can take around 30 seconds per command. With this system, user can expect faster execution of the robot commands, less thinking therefore less exhausting, making BCI a pleasant experience for all users regardless of their health conditions. |
| first_indexed | 2025-11-15T08:58:44Z |
| format | Article |
| id | upm-28694 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T08:58:44Z |
| publishDate | 2013 |
| publisher | IDOSI Publications |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-286942015-09-11T02:29:47Z http://psasir.upm.edu.my/id/eprint/28694/ P300-based EEG signal interpretation system for robot navigation control Hasan, Intan Helina Ramli, Abdul Rahman Ahmad, Siti Anom Osman, Rosiah In recent years, Brain-Computer Interface (BCI) research has provoked an enormous interest among researchers from different fields. The most popular approach is a non-invasive method, using Electroencephalogram (EEG) analysis which acquires signals from the brain. The aim of this project is to develop a brain signal interpretation system that can convert one thought into multiple movements for mobile robot navigation. A signal interpretation system is designed and developed to receive the EEG signal via User Datagram Protocol (UDP) transmission, converts the signal to several robot commands that are pre-programmed according to the robot’s programming software and send the commands to the robot through the operating computer. Using signals from four electrodes to evaluate the signal interpretation system, a success rate of 75-80% is received, while a total response time of only 61 seconds needed by the system from the start of the stimuli until the robot has finished all commands sent by the system, as compared to the conventional method of one-thought-one-movement which can take around 30 seconds per command. With this system, user can expect faster execution of the robot commands, less thinking therefore less exhausting, making BCI a pleasant experience for all users regardless of their health conditions. IDOSI Publications 2013 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/28694/1/P300.pdf Hasan, Intan Helina and Ramli, Abdul Rahman and Ahmad, Siti Anom and Osman, Rosiah (2013) P300-based EEG signal interpretation system for robot navigation control. World Applied Sciences Journal, 26 (5). pp. 566-572. ISSN 1818-4952; ESSN: 1991-6426 http://www.idosi.org/wasj/wasj26%285%292013.htm |
| spellingShingle | Hasan, Intan Helina Ramli, Abdul Rahman Ahmad, Siti Anom Osman, Rosiah P300-based EEG signal interpretation system for robot navigation control |
| title | P300-based EEG signal interpretation system for robot navigation control |
| title_full | P300-based EEG signal interpretation system for robot navigation control |
| title_fullStr | P300-based EEG signal interpretation system for robot navigation control |
| title_full_unstemmed | P300-based EEG signal interpretation system for robot navigation control |
| title_short | P300-based EEG signal interpretation system for robot navigation control |
| title_sort | p300-based eeg signal interpretation system for robot navigation control |
| url | http://psasir.upm.edu.my/id/eprint/28694/ http://psasir.upm.edu.my/id/eprint/28694/ http://psasir.upm.edu.my/id/eprint/28694/1/P300.pdf |