Hybrid Brain–Computer Interface System Using Auditory Stimulation and Speech Imagination Paradigms for Assistive Technology
In the case of paralysis with visual and tactile impairments, brain–computer interfaces (BCIs) based on auditory and mental imagery paradigms are alternative methods for controlling external devices. This study demonstrates the use of a hybrid BCI via auditory stimulation and speech imagi...
| الحاوية / القاعدة: | IEEE Access |
|---|---|
| المؤلفون الرئيسيون: | , |
| التنسيق: | مقال |
| اللغة: | الإنجليزية |
| منشور في: |
IEEE
2023-01-01
|
| الموضوعات: | |
| الوصول للمادة أونلاين: | https://ieeexplore.ieee.org/document/10138171/ |
| _version_ | 1856893673197797376 |
|---|---|
| author | Manorot Borirakarawin Yunyong Punsawad |
| author_facet | Manorot Borirakarawin Yunyong Punsawad |
| author_sort | Manorot Borirakarawin |
| collection | DOAJ |
| container_title | IEEE Access |
| description | In the case of paralysis with visual and tactile impairments, brain–computer interfaces (BCIs) based on auditory and mental imagery paradigms are alternative methods for controlling external devices. This study demonstrates the use of a hybrid BCI via auditory stimulation and speech imagination for assistive technology. The proposed auditory BCI using Thai vowel and numeral stimulus patterns as well as multi-loudspeaker position settings for multi-command BCI are investigated. To avoid auditory stimulation during resting periods, a speech imagery method is used to enable an audio stimulator. We observe the classification efficiency of speech imagery and auditory BCIs from selected electroencephalogram channels using the proposed algorithms. We examine the efficiency of using the proposed BCI in the presence of background noise (speech). One command is created using the proposed speech-imagination paradigm. Four commands are created using the proposed auditory stimulation paradigm. We design an experiment to verify the proposed BCI paradigm and classification algorithms for real-time processing. The results show that the average classification accuracy of the proposed auditory BCI using numeral stimuli and scatter patterns without speech noise is 72.2% to 83.3%, respectively. The efficiency under background noise is approximately two times lower than that without background noise. |
| format | Article |
| id | doaj-art-cb4e2b967bb84eb3bdbf737ed8cf3945 |
| institution | Directory of Open Access Journals |
| issn | 2169-3536 |
| language | English |
| publishDate | 2023-01-01 |
| publisher | IEEE |
| record_format | Article |
| spelling | doaj-art-cb4e2b967bb84eb3bdbf737ed8cf39452025-08-19T20:27:18ZengIEEEIEEE Access2169-35362023-01-0111530795309010.1109/ACCESS.2023.328063610138171Hybrid Brain–Computer Interface System Using Auditory Stimulation and Speech Imagination Paradigms for Assistive TechnologyManorot Borirakarawin0Yunyong Punsawad1https://orcid.org/0000-0002-6994-9682School of Informatics, Walailak University, Nakhon Si Thammarat, ThailandSchool of Informatics, Walailak University, Nakhon Si Thammarat, ThailandIn the case of paralysis with visual and tactile impairments, brain–computer interfaces (BCIs) based on auditory and mental imagery paradigms are alternative methods for controlling external devices. This study demonstrates the use of a hybrid BCI via auditory stimulation and speech imagination for assistive technology. The proposed auditory BCI using Thai vowel and numeral stimulus patterns as well as multi-loudspeaker position settings for multi-command BCI are investigated. To avoid auditory stimulation during resting periods, a speech imagery method is used to enable an audio stimulator. We observe the classification efficiency of speech imagery and auditory BCIs from selected electroencephalogram channels using the proposed algorithms. We examine the efficiency of using the proposed BCI in the presence of background noise (speech). One command is created using the proposed speech-imagination paradigm. Four commands are created using the proposed auditory stimulation paradigm. We design an experiment to verify the proposed BCI paradigm and classification algorithms for real-time processing. The results show that the average classification accuracy of the proposed auditory BCI using numeral stimuli and scatter patterns without speech noise is 72.2% to 83.3%, respectively. The efficiency under background noise is approximately two times lower than that without background noise.https://ieeexplore.ieee.org/document/10138171/Brain-computer interfacehybrid BCIelectroencephalogramevent-related potentialsauditory stimulationspeech imagination |
| spellingShingle | Manorot Borirakarawin Yunyong Punsawad Hybrid Brain–Computer Interface System Using Auditory Stimulation and Speech Imagination Paradigms for Assistive Technology Brain-computer interface hybrid BCI electroencephalogram event-related potentials auditory stimulation speech imagination |
| title | Hybrid Brain–Computer Interface System Using Auditory Stimulation and Speech Imagination Paradigms for Assistive Technology |
| title_full | Hybrid Brain–Computer Interface System Using Auditory Stimulation and Speech Imagination Paradigms for Assistive Technology |
| title_fullStr | Hybrid Brain–Computer Interface System Using Auditory Stimulation and Speech Imagination Paradigms for Assistive Technology |
| title_full_unstemmed | Hybrid Brain–Computer Interface System Using Auditory Stimulation and Speech Imagination Paradigms for Assistive Technology |
| title_short | Hybrid Brain–Computer Interface System Using Auditory Stimulation and Speech Imagination Paradigms for Assistive Technology |
| title_sort | hybrid brain x2013 computer interface system using auditory stimulation and speech imagination paradigms for assistive technology |
| topic | Brain-computer interface hybrid BCI electroencephalogram event-related potentials auditory stimulation speech imagination |
| url | https://ieeexplore.ieee.org/document/10138171/ |
| work_keys_str_mv | AT manorotborirakarawin hybridbrainx2013computerinterfacesystemusingauditorystimulationandspeechimaginationparadigmsforassistivetechnology AT yunyongpunsawad hybridbrainx2013computerinterfacesystemusingauditorystimulationandspeechimaginationparadigmsforassistivetechnology |
