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A Hardware/Software Prototype of EEG-based BCI System for Home Device Control

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Abstract

This paper presents a design exploration of a new EEG-based embedded system for home devices control. Two main issues are addressed in this work: the first one consists of an adaptive filter design to increase the classification accuracy for motor imagery. The second issue deals with the design of an efficient hardware/software embedded architeclture integrating the entire EEG signal processing chain. In this embedded system organization, the pre-processing techniques, which are time consuming, are integrated as hardware accelerators. The remaining blocks (Intellectual Properties - IP) are developed as embedded-software running on an embedded soft-core processor. The pre-processing step is designed to be self-adjusted according to the intrinsic characteristics of each subject. The feature extraction process uses the Common Spatial Pattern (CSP) as a filter due to its effectiveness to extract the ERD/ERS (Event-Related Desynchronization/ Synchronization) effect, where the classifier is based on the Mahalanobis distance. The advantage of the proposed system lies in its simplicity and short processing time while maintaining a high performance in term of classification accuracy. A prototype of the embedded system has been implemented on an Altera FPGA-based platform (Stratix-IV). It is shown that the proposed architecture can effectively extract discriminative features for motor imagery with a maximum frequency of 150 MHz. The proposed system was validated on EEG data of twelve subjects from the BCI competition data sets. The prototype performs a fast classification within time delay of 0.399 second per trial, an accuracy average of 94.47 %, an average transfer rate over all subjects of 20.74 bits/min. The estimated power consumption of the proposed system is around 1.067 Watt (based on an integrated tool-power analysis of Altera corporation).

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Authors and Affiliations

  1. ETIS, CNRS UMR8051, University Cergy Pontoise, ENSEA, 6 avenue du Ponceau, 95014, Cergy Pontoise, France

    Kais Belwafi, Fakhreddine Ghaffari & Olivier Romain

  2. ENISo of Sousse, University of Sousse, Erriyadh 4023, Sousse, Tunisia

    Kais Belwafi

  3. Electrical Engineering Department, King Saud University, Box 800, 11421, Riyadh, Saudi Arabia

    Ridha Djemal

Authors
  1. Kais Belwafi
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  2. Fakhreddine Ghaffari
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  3. Ridha Djemal
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  4. Olivier Romain
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Correspondence to Kais Belwafi.

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The authors declare that they have no conflict of interest and no problem with Ethical Approval. This project was funded by the National Plan for Science, Technology and Innovation (MAARIFAH), King Abdulaziz City for Science and Technology, Kingdom of Saudi Arabia, Award Number (ELE1730).

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Belwafi, K., Ghaffari, F., Djemal, R. et al. A Hardware/Software Prototype of EEG-based BCI System for Home Device Control. J Sign Process Syst 89, 263–279 (2017). https://doi.org/10.1007/s11265-016-1192-8

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  • DOI: https://doi.org/10.1007/s11265-016-1192-8

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