Wheelchair controlled by human brainwave using brain-computer interface system for paralyzed patient
Brain-Computer Interface (BCI) is a direct communication pathway between a human and external device. Integrated wheelchair controlled with human brainwave using a BCI system was designed and studied to help people with disabilities, especially for people who suffer from motor disorders such as peri...
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| Format: | Thesis |
| Language: | English English English |
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2020
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| Online Access: | http://eprints.uthm.edu.my/1108/ http://eprints.uthm.edu.my/1108/1/24p%20NORASYIMAH%20BINTI%20SAHAT.pdf http://eprints.uthm.edu.my/1108/2/NORASYIMAH%20BINTI%20SAHAT%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/1108/3/NORASYIMAH%20BINTI%20SAHAT%20WATERMARK.pdf |
| _version_ | 1848887376630251520 |
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| author | Sahat, Norasyimah |
| author_facet | Sahat, Norasyimah |
| author_sort | Sahat, Norasyimah |
| building | UTHM Institutional Repository |
| collection | Online Access |
| description | Brain-Computer Interface (BCI) is a direct communication pathway between a human and external device. Integrated wheelchair controlled with human brainwave using a BCI system was designed and studied to help people with disabilities, especially for people who suffer from motor disorders such as peripheral nerves and muscles. The invention aims to develop an integrated wheelchair which can be controlled by a paralyzed person using only a single electrode. In this research, the efficiency of the brainwave integrated wheelchair has been improved using human attention value, blink detection and eyebrow movement of the user to control the wheelchair. An encephalography (EEG) device called Mindwave Mobile Plus (MW+) has been employed to obtain attention value for the wheelchair movement, eye blink to change the mode of the wheelchair to move forward (F), to the right (R), backward (B) and to the left (L). Eyebrow movement was used to stop the wheelchair when using human brainwave as the signal quality value of 26 or 51 is produced. Analysis on the human attention value in different gender and age category also has been done. Male is easier to focus compared to the female. Teenagers have the highest attention value followed by the children while the adults have the lowest attention value among all age categories studied. The EEG of the human were analyzed by using Arduino Integrated Development Environment (IDE) software. The development of the integrated wheelchair is improved by using human’s attention value, blink detection and eyebrow movement and the threshold value of the attention level was set according to the gender and age category of the user. From the results and analysis, the threshold value for male children is 60, male teenager (70), male adult (40) while for the female children is 50, female teenager (50) and female adult (30). |
| first_indexed | 2025-11-15T19:53:24Z |
| format | Thesis |
| id | uthm-1108 |
| institution | Universiti Tun Hussein Onn Malaysia |
| institution_category | Local University |
| language | English English English |
| last_indexed | 2025-11-15T19:53:24Z |
| publishDate | 2020 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | uthm-11082021-09-22T04:42:39Z http://eprints.uthm.edu.my/1108/ Wheelchair controlled by human brainwave using brain-computer interface system for paralyzed patient Sahat, Norasyimah QP351-495 Neurophysiology and neuropsychology Brain-Computer Interface (BCI) is a direct communication pathway between a human and external device. Integrated wheelchair controlled with human brainwave using a BCI system was designed and studied to help people with disabilities, especially for people who suffer from motor disorders such as peripheral nerves and muscles. The invention aims to develop an integrated wheelchair which can be controlled by a paralyzed person using only a single electrode. In this research, the efficiency of the brainwave integrated wheelchair has been improved using human attention value, blink detection and eyebrow movement of the user to control the wheelchair. An encephalography (EEG) device called Mindwave Mobile Plus (MW+) has been employed to obtain attention value for the wheelchair movement, eye blink to change the mode of the wheelchair to move forward (F), to the right (R), backward (B) and to the left (L). Eyebrow movement was used to stop the wheelchair when using human brainwave as the signal quality value of 26 or 51 is produced. Analysis on the human attention value in different gender and age category also has been done. Male is easier to focus compared to the female. Teenagers have the highest attention value followed by the children while the adults have the lowest attention value among all age categories studied. The EEG of the human were analyzed by using Arduino Integrated Development Environment (IDE) software. The development of the integrated wheelchair is improved by using human’s attention value, blink detection and eyebrow movement and the threshold value of the attention level was set according to the gender and age category of the user. From the results and analysis, the threshold value for male children is 60, male teenager (70), male adult (40) while for the female children is 50, female teenager (50) and female adult (30). 2020-11 Thesis NonPeerReviewed text en http://eprints.uthm.edu.my/1108/1/24p%20NORASYIMAH%20BINTI%20SAHAT.pdf text en http://eprints.uthm.edu.my/1108/2/NORASYIMAH%20BINTI%20SAHAT%20COPYRIGHT%20DECLARATION.pdf text en http://eprints.uthm.edu.my/1108/3/NORASYIMAH%20BINTI%20SAHAT%20WATERMARK.pdf Sahat, Norasyimah (2020) Wheelchair controlled by human brainwave using brain-computer interface system for paralyzed patient. Masters thesis, Universiti Tun Hussein Onn Malaysia. |
| spellingShingle | QP351-495 Neurophysiology and neuropsychology Sahat, Norasyimah Wheelchair controlled by human brainwave using brain-computer interface system for paralyzed patient |
| title | Wheelchair controlled by human brainwave using brain-computer interface system for paralyzed patient |
| title_full | Wheelchair controlled by human brainwave using brain-computer interface system for paralyzed patient |
| title_fullStr | Wheelchair controlled by human brainwave using brain-computer interface system for paralyzed patient |
| title_full_unstemmed | Wheelchair controlled by human brainwave using brain-computer interface system for paralyzed patient |
| title_short | Wheelchair controlled by human brainwave using brain-computer interface system for paralyzed patient |
| title_sort | wheelchair controlled by human brainwave using brain-computer interface system for paralyzed patient |
| topic | QP351-495 Neurophysiology and neuropsychology |
| url | http://eprints.uthm.edu.my/1108/ http://eprints.uthm.edu.my/1108/1/24p%20NORASYIMAH%20BINTI%20SAHAT.pdf http://eprints.uthm.edu.my/1108/2/NORASYIMAH%20BINTI%20SAHAT%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/1108/3/NORASYIMAH%20BINTI%20SAHAT%20WATERMARK.pdf |