Development of an Electrooculogram (EOG) and Surface Electromyogram (sEMG)-Based Human Computer Interface (HCI) Using a Bone Conduction Headphone Integrated Bio-Signal Acquisition System
Human–computer interface (HCI) methods based on the electrooculogram (EOG) signals generated from eye movement have been continuously studied because they can transmit the commands to a computer or machine without using both arms. However, usability and appearance are the big obstacles to practical...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-08-01
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| Series: | Electronics |
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| Online Access: | https://www.mdpi.com/2079-9292/11/16/2561 |
| _version_ | 1797445860215226368 |
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| author | Ha Na Jo Sung Woo Park Han Gyeol Choi Seok Hyun Han Tae Seon Kim |
| author_facet | Ha Na Jo Sung Woo Park Han Gyeol Choi Seok Hyun Han Tae Seon Kim |
| author_sort | Ha Na Jo |
| collection | DOAJ |
| description | Human–computer interface (HCI) methods based on the electrooculogram (EOG) signals generated from eye movement have been continuously studied because they can transmit the commands to a computer or machine without using both arms. However, usability and appearance are the big obstacles to practical applications since conventional EOG-based HCI methods require skin electrodes outside the eye near the lateral and medial canthus. To solve these problems, in this paper, we report development of an HCI method that can simultaneously acquire EOG and surface-electromyogram (sEMG) signals through electrodes integrated into bone conduction headphones and transmit the commands through the horizontal eye movements and various biting movements. The developed system can classify the position of the eyes by dividing the 80-degree range (from −40 degrees to the left to +40 degrees to the right) into 20-degree sections and can also recognize the three biting movements based on the bio-signals obtained from the three electrodes, so a total of 11 commands can be delivered to a computer or machine. The experimental results showed the interface has accuracy of 92.04% and 96.10% for EOG signal-based commands and sEMG signal-based commands, respectively. As for the results of virtual keyboard interface application, the accuracy was 97.19%, the precision was 90.51%, and the typing speed was 5.75–18.97 letters/min. The proposed interface system can be applied to various HCI and HMI fields as well as virtual keyboard applications. |
| first_indexed | 2024-03-09T13:31:53Z |
| format | Article |
| id | doaj.art-1f475be7165b4adcbf4419eaa7dbdbc2 |
| institution | Directory Open Access Journal |
| issn | 2079-9292 |
| language | English |
| last_indexed | 2024-03-09T13:31:53Z |
| publishDate | 2022-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Electronics |
| spelling | doaj.art-1f475be7165b4adcbf4419eaa7dbdbc22023-11-30T21:16:46ZengMDPI AGElectronics2079-92922022-08-011116256110.3390/electronics11162561Development of an Electrooculogram (EOG) and Surface Electromyogram (sEMG)-Based Human Computer Interface (HCI) Using a Bone Conduction Headphone Integrated Bio-Signal Acquisition SystemHa Na Jo0Sung Woo Park1Han Gyeol Choi2Seok Hyun Han3Tae Seon Kim4Department of Artificial Intelligence, Korea University, Seoul 02841, KoreaSchool of Information, Communications and Electronics Engineering, Catholic University of Korea, Bucheon 14662, KoreaSchool of Information, Communications and Electronics Engineering, Catholic University of Korea, Bucheon 14662, KoreaSchool of Information, Communications and Electronics Engineering, Catholic University of Korea, Bucheon 14662, KoreaSchool of Information, Communications and Electronics Engineering, Catholic University of Korea, Bucheon 14662, KoreaHuman–computer interface (HCI) methods based on the electrooculogram (EOG) signals generated from eye movement have been continuously studied because they can transmit the commands to a computer or machine without using both arms. However, usability and appearance are the big obstacles to practical applications since conventional EOG-based HCI methods require skin electrodes outside the eye near the lateral and medial canthus. To solve these problems, in this paper, we report development of an HCI method that can simultaneously acquire EOG and surface-electromyogram (sEMG) signals through electrodes integrated into bone conduction headphones and transmit the commands through the horizontal eye movements and various biting movements. The developed system can classify the position of the eyes by dividing the 80-degree range (from −40 degrees to the left to +40 degrees to the right) into 20-degree sections and can also recognize the three biting movements based on the bio-signals obtained from the three electrodes, so a total of 11 commands can be delivered to a computer or machine. The experimental results showed the interface has accuracy of 92.04% and 96.10% for EOG signal-based commands and sEMG signal-based commands, respectively. As for the results of virtual keyboard interface application, the accuracy was 97.19%, the precision was 90.51%, and the typing speed was 5.75–18.97 letters/min. The proposed interface system can be applied to various HCI and HMI fields as well as virtual keyboard applications.https://www.mdpi.com/2079-9292/11/16/2561human–computer interface (HCI)electrooculogram (EOG)surface electromyogram (sEMG)horizontal gaze anglevirtual keyboard |
| spellingShingle | Ha Na Jo Sung Woo Park Han Gyeol Choi Seok Hyun Han Tae Seon Kim Development of an Electrooculogram (EOG) and Surface Electromyogram (sEMG)-Based Human Computer Interface (HCI) Using a Bone Conduction Headphone Integrated Bio-Signal Acquisition System Electronics human–computer interface (HCI) electrooculogram (EOG) surface electromyogram (sEMG) horizontal gaze angle virtual keyboard |
| title | Development of an Electrooculogram (EOG) and Surface Electromyogram (sEMG)-Based Human Computer Interface (HCI) Using a Bone Conduction Headphone Integrated Bio-Signal Acquisition System |
| title_full | Development of an Electrooculogram (EOG) and Surface Electromyogram (sEMG)-Based Human Computer Interface (HCI) Using a Bone Conduction Headphone Integrated Bio-Signal Acquisition System |
| title_fullStr | Development of an Electrooculogram (EOG) and Surface Electromyogram (sEMG)-Based Human Computer Interface (HCI) Using a Bone Conduction Headphone Integrated Bio-Signal Acquisition System |
| title_full_unstemmed | Development of an Electrooculogram (EOG) and Surface Electromyogram (sEMG)-Based Human Computer Interface (HCI) Using a Bone Conduction Headphone Integrated Bio-Signal Acquisition System |
| title_short | Development of an Electrooculogram (EOG) and Surface Electromyogram (sEMG)-Based Human Computer Interface (HCI) Using a Bone Conduction Headphone Integrated Bio-Signal Acquisition System |
| title_sort | development of an electrooculogram eog and surface electromyogram semg based human computer interface hci using a bone conduction headphone integrated bio signal acquisition system |
| topic | human–computer interface (HCI) electrooculogram (EOG) surface electromyogram (sEMG) horizontal gaze angle virtual keyboard |
| url | https://www.mdpi.com/2079-9292/11/16/2561 |
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