Design of Wearable Headset with Steady State Visually Evoked Potential-Based Brain Computer Interface
Brain–computer interface (BCI) is a system that allows people to communicate directly with external machines via recognizing brain activities without manual operation. However, for most current BCI systems, conventional electroencephalography (EEG) machines and computers are usually required to acqu...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2019-10-01
|
| Series: | Micromachines |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-666X/10/10/681 |
| _version_ | 1811205750434824192 |
|---|---|
| author | Bor-Shyh Lin Bor-Shing Lin Tzu-Hsiang Yen Chien-Chin Hsu Yao-Chin Wang |
| author_facet | Bor-Shyh Lin Bor-Shing Lin Tzu-Hsiang Yen Chien-Chin Hsu Yao-Chin Wang |
| author_sort | Bor-Shyh Lin |
| collection | DOAJ |
| description | Brain–computer interface (BCI) is a system that allows people to communicate directly with external machines via recognizing brain activities without manual operation. However, for most current BCI systems, conventional electroencephalography (EEG) machines and computers are usually required to acquire EEG signal and translate them into control commands, respectively. The sizes of the above machines are usually large, and this increases the limitation for daily applications. Moreover, conventional EEG electrodes also require conductive gels to improve the EEG signal quality. This causes discomfort and inconvenience of use, while the conductive gels may also encounter the problem of drying out during prolonged measurements. In order to improve the above issues, a wearable headset with steady-state visually evoked potential (SSVEP)-based BCI is proposed in this study. Active dry electrodes were designed and implemented to acquire a good EEG signal quality without conductive gels from the hairy site. The SSVEP BCI algorithm was also implemented into the designed field-programmable gate array (FPGA)-based BCI module to translate SSVEP signals into control commands in real time. Moreover, a commercial tablet was used as the visual stimulus device to provide graphic control icons. The whole system was designed as a wearable device to improve convenience of use in daily life, and it could acquire and translate EEG signal directly in the front-end headset. Finally, the performance of the proposed system was validated, and the results showed that it had excellent performance (information transfer rate = 36.08 bits/min). |
| first_indexed | 2024-04-12T03:36:41Z |
| format | Article |
| id | doaj.art-71ae2351a8ba41699fa3686055f7df56 |
| institution | Directory Open Access Journal |
| issn | 2072-666X |
| language | English |
| last_indexed | 2024-04-12T03:36:41Z |
| publishDate | 2019-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Micromachines |
| spelling | doaj.art-71ae2351a8ba41699fa3686055f7df562022-12-22T03:49:24ZengMDPI AGMicromachines2072-666X2019-10-01101068110.3390/mi10100681mi10100681Design of Wearable Headset with Steady State Visually Evoked Potential-Based Brain Computer InterfaceBor-Shyh Lin0Bor-Shing Lin1Tzu-Hsiang Yen2Chien-Chin Hsu3Yao-Chin Wang4Institute of Imaging and Biomedical Photonics, National Chiao Tung University, Hsinchu City 30010, TaiwanDepartment of Computer Science and Information Engineering, National Taipei University, New Taipei City 23741, TaiwanInstitute of Imaging and Biomedical Photonics, National Chiao Tung University, Hsinchu City 30010, TaiwanDepartment of Emergency Medicine, Chi Mei Medical Center, Tainan City 71004, TaiwanDepartment of Computer Science and Information Engineering, Cheng Shiu University, Kaohsiung City 83347, TaiwanBrain–computer interface (BCI) is a system that allows people to communicate directly with external machines via recognizing brain activities without manual operation. However, for most current BCI systems, conventional electroencephalography (EEG) machines and computers are usually required to acquire EEG signal and translate them into control commands, respectively. The sizes of the above machines are usually large, and this increases the limitation for daily applications. Moreover, conventional EEG electrodes also require conductive gels to improve the EEG signal quality. This causes discomfort and inconvenience of use, while the conductive gels may also encounter the problem of drying out during prolonged measurements. In order to improve the above issues, a wearable headset with steady-state visually evoked potential (SSVEP)-based BCI is proposed in this study. Active dry electrodes were designed and implemented to acquire a good EEG signal quality without conductive gels from the hairy site. The SSVEP BCI algorithm was also implemented into the designed field-programmable gate array (FPGA)-based BCI module to translate SSVEP signals into control commands in real time. Moreover, a commercial tablet was used as the visual stimulus device to provide graphic control icons. The whole system was designed as a wearable device to improve convenience of use in daily life, and it could acquire and translate EEG signal directly in the front-end headset. Finally, the performance of the proposed system was validated, and the results showed that it had excellent performance (information transfer rate = 36.08 bits/min).https://www.mdpi.com/2072-666X/10/10/681brain–computer interface (bci)steady-state visually evoked potentials (ssvep)field-programmable gate array (fpga)wearable |
| spellingShingle | Bor-Shyh Lin Bor-Shing Lin Tzu-Hsiang Yen Chien-Chin Hsu Yao-Chin Wang Design of Wearable Headset with Steady State Visually Evoked Potential-Based Brain Computer Interface Micromachines brain–computer interface (bci) steady-state visually evoked potentials (ssvep) field-programmable gate array (fpga) wearable |
| title | Design of Wearable Headset with Steady State Visually Evoked Potential-Based Brain Computer Interface |
| title_full | Design of Wearable Headset with Steady State Visually Evoked Potential-Based Brain Computer Interface |
| title_fullStr | Design of Wearable Headset with Steady State Visually Evoked Potential-Based Brain Computer Interface |
| title_full_unstemmed | Design of Wearable Headset with Steady State Visually Evoked Potential-Based Brain Computer Interface |
| title_short | Design of Wearable Headset with Steady State Visually Evoked Potential-Based Brain Computer Interface |
| title_sort | design of wearable headset with steady state visually evoked potential based brain computer interface |
| topic | brain–computer interface (bci) steady-state visually evoked potentials (ssvep) field-programmable gate array (fpga) wearable |
| url | https://www.mdpi.com/2072-666X/10/10/681 |
| work_keys_str_mv | AT borshyhlin designofwearableheadsetwithsteadystatevisuallyevokedpotentialbasedbraincomputerinterface AT borshinglin designofwearableheadsetwithsteadystatevisuallyevokedpotentialbasedbraincomputerinterface AT tzuhsiangyen designofwearableheadsetwithsteadystatevisuallyevokedpotentialbasedbraincomputerinterface AT chienchinhsu designofwearableheadsetwithsteadystatevisuallyevokedpotentialbasedbraincomputerinterface AT yaochinwang designofwearableheadsetwithsteadystatevisuallyevokedpotentialbasedbraincomputerinterface |