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Error potential detection during continuous movement of an artificial arm controlled by brain–computer interface

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Abstract

Patients who benefit from Brain–Computer Interfaces (BCIs) may have difficulties to generate more than one distinct brain pattern which can be used to control applications. Other BCI issues are low performance, accuracy, and, depending on the type of BCI, a long preparation and/or training time. This study aims to show possible solutions. First, we used time-coded motor imagery (MI) with only one pattern. Second, we reduced the training time by recording only 20 trials of active MI to set up a BCI classifier. Third, we investigated a way to record error potentials (ErrPs) during continuous feedback. Ten subjects controlled an artificial arm by performing MI over target time periods between 1 and 4 s. The subsequent movement of this arm served as continuous feedback. Discrete events, which are required to elicit ErrPs, were added by mounting blinking LEDs on top of the continuously moving arm to indicate the future movements. Time epochs after these events were used to evaluate ErrPs offline. The achieved error rate for the arm movement was on average 26.9%. Obtained ErrPs looked similar to results from the previous studies dealing with error detection and the detection rate was above chance level which is a positive outcome and encourages further investigation.

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Acknowledgments

This work is supported by the European ICT Programme Project FP7-224631. This paper only reflects the authors’ views and funding agencies are not liable for any use that may be made of the information contained herein.

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Authors and Affiliations

  1. Institute for Knowledge Discovery, BCI Lab, Graz University of Technology, Krenngasse 37, 8010, Graz, Austria

    Alex Kreilinger, Christa Neuper & Gernot R. Müller-Putz

  2. Department of Psychology, University of Graz, Universitätsplatz 2, 8010, Graz, Austria

    Christa Neuper

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  1. Alex Kreilinger
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  2. Christa Neuper
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  3. Gernot R. Müller-Putz
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Correspondence to Alex Kreilinger.

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Kreilinger, A., Neuper, C. & Müller-Putz, G.R. Error potential detection during continuous movement of an artificial arm controlled by brain–computer interface. Med Biol Eng Comput 50, 223–230 (2012). https://doi.org/10.1007/s11517-011-0858-4

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  • DOI: https://doi.org/10.1007/s11517-011-0858-4

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