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Brain-Controlled, AR-Based Home Automation System Using SSVEP-Based Brain-Computer Interface and EOG-Based Eye

Seonghun Park, Jisoo Ha, Jimin Park

    IEEE Transactions on Neural Systems and Rehabilitation Engineering : a Publication of the IEEE Engineering in Medicine and Biology Society
    |April 4, 2023
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    Summary

    This study developed an augmented reality brain-computer interface (BCI) for home appliance control, specifically for elderly users. The system demonstrated successful control and high usability, outperforming previous BCI systems for this demographic.

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    Area of Science:

    • Neuroscience
    • Human-Computer Interaction
    • Assistive Technology

    Background:

    • Brain-computer interfaces (BCIs) offer alternative communication channels, primarily for disabled or elderly individuals.
    • Existing BCI applications are often tested on young, healthy populations, limiting their applicability for target users.
    • There is a need for user-friendly BCI systems tailored for the elderly population.

    Purpose of the Study:

    • To develop and evaluate an online home appliance control system using a steady-state visual evoked potential (SSVEP)-based BCI.
    • To integrate augmented reality (AR) visual stimulation and an electrooculogram (EOG)-based eye tracker for enhanced user interaction.
    • To assess the performance and usability of the developed BCI system in individuals aged over 65.

    Main Methods:

    • Developed an SSVEP-based BCI system integrated with an AR environment for visual stimulation.
    • Incorporated an EOG-based eye tracker for user input, including an eye-blink switch.
    • Tested the online home appliance control system with 13 participants aged over 65, allowing user preference for device selection methods.

    Main Results:

    • All 13 elderly participants successfully controlled five home appliances using the proposed AR-based BCI system.
    • The system usability scale scores exceeded 70, indicating good user acceptance and ease of use.
    • The BCI performance achieved by the system surpassed previously reported results for BCI systems designed for the elderly.

    Conclusions:

    • The developed AR-based SSVEP BCI system is effective for home appliance control in elderly individuals.
    • The system offers a viable and high-performing solution for assistive technology, improving quality of life for the elderly.
    • This study highlights the potential of integrating AR and BCI for accessible smart home environments.