A brain computer interface for robust wheelchair control application based on pseudorandom code modulated Visual Evoked Potential
In this pilot study, a novel and minimalistic Brain Computer Interface (BCI) based wheelchair control application was developed. The system was based on pseudorandom code modulated Visual Evoked Potentials (c-VEPs). The visual stimuli in the scheme were generated based on the Gold code, and the VEPs were recognized and classified using subject-specific algorithms. The system provided the ability of controlling a wheelchair model (LEGO(®) MINDSTORM(®) EV3 robot) in 4 different directions based on the elicited c-VEPs. Ten healthy subjects were evaluated in testing the system where an average accuracy of 97% was achieved. The promising results illustrate the potential of this approach when considering a real wheelchair application.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2015 |
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| Erschienen: |
2015 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:2015 |
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| Enthalten in: |
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference - 2015(2015) vom: 05. Aug., Seite 602-5 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Mohebbi, Ali [VerfasserIn] |
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| Links: |
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| Themen: |
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| Anmerkungen: |
Date Completed 22.03.2018 Date Revised 28.09.2020 published: Print Citation Status MEDLINE |
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| doi: |
10.1109/EMBC.2015.7318434 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM256186065 |
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| 245 | 1 | 2 | |a A brain computer interface for robust wheelchair control application based on pseudorandom code modulated Visual Evoked Potential |
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| 500 | |a Date Revised 28.09.2020 | ||
| 500 | |a published: Print | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a In this pilot study, a novel and minimalistic Brain Computer Interface (BCI) based wheelchair control application was developed. The system was based on pseudorandom code modulated Visual Evoked Potentials (c-VEPs). The visual stimuli in the scheme were generated based on the Gold code, and the VEPs were recognized and classified using subject-specific algorithms. The system provided the ability of controlling a wheelchair model (LEGO(®) MINDSTORM(®) EV3 robot) in 4 different directions based on the elicited c-VEPs. Ten healthy subjects were evaluated in testing the system where an average accuracy of 97% was achieved. The promising results illustrate the potential of this approach when considering a real wheelchair application | ||
| 650 | 4 | |a Journal Article | |
| 700 | 1 | |a Engelsholm, Signe K D |e verfasserin |4 aut | |
| 700 | 1 | |a Puthusserypady, Sadasivan |e verfasserin |4 aut | |
| 700 | 1 | |a Kjaer, Troels W |e verfasserin |4 aut | |
| 700 | 1 | |a Thomsen, Carsten E |e verfasserin |4 aut | |
| 700 | 1 | |a Sorensen, Helge B D |e verfasserin |4 aut | |
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