A Brain Computer Interface for Robust Wheelchair Control Application Based on Pseudorandom Code Modulated Visual Evoked Potential.

Ali Mohebbi; Signe K.D. Engelsholm; Sadasivan Puthusserypady; Troels W. Kjaer; Carsten E. Thomsen; Helge Bjarup Dissing Sørensen

doi:10.1109/EMBC.2015.7318434

A Brain Computer Interface for Robust Wheelchair Control Application Based on Pseudorandom Code Modulated Visual Evoked Potential.

Ali Mohebbi, Signe K.D. Engelsholm, Sadasivan Puthusserypady, Troels W. Kjaer, Carsten E. Thomsen, Helge Bjarup Dissing Sørensen

Department of Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

Abstract

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 R MINDSTORM R 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.

Original language	English
Title of host publication	Proceedings of 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Publisher	IEEE
Publication date	2015
Pages	602-605
ISBN (Print)	978-1-4244-9270-1
DOIs	https://doi.org/10.1109/EMBC.2015.7318434
Publication status	Published - 2015
Event	37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society - Milano, Italy Duration: 25 Aug 2015 → 29 Aug 2015 Conference number: 37

Conference

Conference	37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Number	37
Country/Territory	Italy
City	Milano
Period	25/08/2015 → 29/08/2015

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10.1109/EMBC.2015.7318434

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Mohebbi, A., Engelsholm, S. K. D., Puthusserypady, S., Kjaer, T. W., Thomsen, C. E., & Sørensen, H. B. D. (2015). A Brain Computer Interface for Robust Wheelchair Control Application Based on Pseudorandom Code Modulated Visual Evoked Potential. In Proceedings of 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (pp. 602-605). IEEE. https://doi.org/10.1109/EMBC.2015.7318434

Mohebbi, Ali ; Engelsholm, Signe K.D. ; Puthusserypady, Sadasivan ; Kjaer, Troels W. ; Thomsen, Carsten E. ; Sørensen, Helge Bjarup Dissing. / A Brain Computer Interface for Robust Wheelchair Control Application Based on Pseudorandom Code Modulated Visual Evoked Potential. Proceedings of 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 2015. pp. 602-605

@inproceedings{4efbdf75bcb84e3886cc64716e2c1ec6,

title = "A Brain Computer Interface for Robust Wheelchair Control Application Based on Pseudorandom Code Modulated Visual Evoked Potential.",

abstract = "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 R MINDSTORM R 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.",

author = "Ali Mohebbi and Engelsholm, {Signe K.D.} and Sadasivan Puthusserypady and Kjaer, {Troels W.} and Thomsen, {Carsten E.} and S{\o}rensen, {Helge Bjarup Dissing}",

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doi = "10.1109/EMBC.2015.7318434",

language = "English",

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pages = "602--605",

booktitle = "Proceedings of 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society",

publisher = "IEEE",

address = "United States",

note = "37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2015 ; Conference date: 25-08-2015 Through 29-08-2015",

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Mohebbi, A, Engelsholm, SKD, Puthusserypady, S, Kjaer, TW, Thomsen, CE & Sørensen, HBD 2015, A Brain Computer Interface for Robust Wheelchair Control Application Based on Pseudorandom Code Modulated Visual Evoked Potential. in Proceedings of 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, pp. 602-605, 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Milano, Italy, 25/08/2015. https://doi.org/10.1109/EMBC.2015.7318434

A Brain Computer Interface for Robust Wheelchair Control Application Based on Pseudorandom Code Modulated Visual Evoked Potential. / Mohebbi, Ali; Engelsholm, Signe K.D.; Puthusserypady, Sadasivan; Kjaer, Troels W.; Thomsen, Carsten E.; Sørensen, Helge Bjarup Dissing.

Proceedings of 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 2015. p. 602-605.

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

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AB - 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 R MINDSTORM R 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.

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Mohebbi A, Engelsholm SKD, Puthusserypady S, Kjaer TW, Thomsen CE, Sørensen HBD. A Brain Computer Interface for Robust Wheelchair Control Application Based on Pseudorandom Code Modulated Visual Evoked Potential. In Proceedings of 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE. 2015. p. 602-605 https://doi.org/10.1109/EMBC.2015.7318434

A Brain Computer Interface for Robust Wheelchair Control Application Based on Pseudorandom Code Modulated Visual Evoked Potential.

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