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Optimization of Wheelchair Control via Multi-Modal Integration: Combining Webcam and EEG

Author

Listed:
  • Lassaad Zaway

    (Laboratory of Computer Embedded System, National School of Engineering of Sfax, University of Sfax, Sfax 3029, Tunisia
    National School of Engineering of Gabes, University of Gabes, Gabes 6029, Tunisia)

  • Nader Ben Amor

    (Laboratory of Computer Embedded System, National School of Engineering of Sfax, University of Sfax, Sfax 3029, Tunisia)

  • Jalel Ktari

    (Laboratory of Computer Embedded System, National School of Engineering of Sfax, University of Sfax, Sfax 3029, Tunisia)

  • Mohamed Jallouli

    (Laboratory of Computer Embedded System, National School of Engineering of Sfax, University of Sfax, Sfax 3029, Tunisia)

  • Larbi Chrifi Alaoui

    (Laboratory of Innovative Technologies, University of Picardie Jules Verne, 80000 Amiens, France)

  • Laurent Delahoche

    (Laboratory of Innovative Technologies, University of Picardie Jules Verne, 80000 Amiens, France)

Abstract

Even though Electric Powered Wheelchairs (EPWs) are a useful tool for meeting the needs of people with disabilities, some disabled people find it difficult to use regular EPWs that are joystick-controlled. Smart wheelchairs that use Brain–Computer Interface (BCI) technology present an efficient solution to this problem. This article presents a cutting-edge intelligent control wheelchair that is intended to improve user involvement and security. The suggested method combines facial expression analysis via a camera with EEG signal processing using the EMOTIV Insight EEG dataset. The system generates control commands by identifying specific EEG patterns linked to facial expressions such as eye blinking, winking left and right, and smiling. Simultaneously, the system uses computer vision algorithms and inertial measurements to analyze gaze direction in order to establish the user’s intended steering. The outcomes of the experiments prove that the proposed system is reliable and efficient in meeting the various requirements of people, presenting a positive development in the field of smart wheelchair technology.

Suggested Citation

  • Lassaad Zaway & Nader Ben Amor & Jalel Ktari & Mohamed Jallouli & Larbi Chrifi Alaoui & Laurent Delahoche, 2024. "Optimization of Wheelchair Control via Multi-Modal Integration: Combining Webcam and EEG," Future Internet, MDPI, vol. 16(5), pages 1-16, May.
    • Handle: RePEc:gam:jftint:v:16:y:2024:i:5:p:158-:d:1388307
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    References listed on IDEAS

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