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A comparison of subject-dependent and subject-independent channel selection strategies for single-trial P300 brain computer interfaces

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Abstract

Brain computer interfaces (BCI) represent an alternative for patients whose cognitive functions are preserved, but are unable to communicate via conventional means. A commonly used BCI paradigm is based on the detection of event-related potentials, particularly the P300, immersed in the electroencephalogram (EEG). In order to transfer laboratory-tested BCIs into systems that can be used by at homes, it is relevant to investigate if it is possible to select a limited set of EEG channels that work for most subjects and across different sessions without a significant decrease in performance. In this work, two strategies for channel selection for a single-trial P300 brain computer interface were evaluated and compared. The first strategy was tailored specifically for each subject, whereas the second strategy aimed at finding a subject-independent set of channels. In both strategies, genetic algorithms (GAs) and recursive feature elimination algorithms were used. The classification stage was performed using a linear discriminant. A dataset of EEG recordings from 18 healthy subjects was used test the proposed configurations. Performance indexes were calculated to evaluate the system. Results showed that a fixed subset of four subject-independent EEG channels selected using GA provided the best compromise between BCI setup and single-trial system performance.

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Funding sources

This work was financially supported by the National University of Entre Ríos (UNER), PID No. 6163.

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Authors and Affiliations

  1. Laboratory for Rehabilitation Engineering and Neuromuscular and Sensory Research (LIRINS), Faculty of Engineering, National University of Entre Ríos (UNER), Route 11 km. 10, 3100, Oro Verde, Argentina

    Yanina Atum, Marianela Pacheco, Rubén Acevedo, Carolina Tabernig & José Biurrun Manresa

  2. Institute for Research and Development in Bioengineering and Bioinformatics (IBB), National Scientific and Technical Research Council, CONICET-UNER, Route 11 km. 10, 3100, Oro Verde, Argentina

    José Biurrun Manresa

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  1. Yanina Atum
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Correspondence to Yanina Atum.

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Atum, Y., Pacheco, M., Acevedo, R. et al. A comparison of subject-dependent and subject-independent channel selection strategies for single-trial P300 brain computer interfaces. Med Biol Eng Comput 57, 2705–2715 (2019). https://doi.org/10.1007/s11517-019-02065-z

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