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Retrospectively supervised click decoder calibration for self-calibrating point-and-click brain-computer interfaces.

Beata Jarosiewicz1, Anish A Sarma2, Jad Saab3

  • 1Neuroscience, Brown University, Providence, RI 02912, United States; Center for Neurorestoration and Neurotechnology, Rehabilitation R&D Service, Veterans Affairs Medical Center, Providence, RI 02908, United States; Brown Institute for Brain Science, Brown University, Providence, RI 02912, United States.

Journal of Physiology, Paris
|March 14, 2017
PubMed

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Summary
This summary is machine-generated.

Brain-computer interfaces (BCIs) now recalibrate automatically during use, improving control for individuals with motor disabilities. This innovation eliminates tedious calibration, enhancing BCI clinical utility for typing and daily tasks.

Area of Science:

  • Neuroscience
  • Biomedical Engineering
  • Rehabilitation Technology

Background:

  • Brain-computer interfaces (BCIs) offer independence for individuals with severe motor disabilities.
  • Neural signal nonstationarities challenge long-term BCI decoding stability.
  • Frequent recalibration interrupts BCI use and user experience.

Purpose of the Study:

  • To extend retrospective methods for calibrating both kinematic and click decoders in BCIs.
  • To enable continuous BCI operation without user-initiated recalibration tasks.
  • To improve the clinical applicability of intracortical BCIs.

Main Methods:

  • Retrospectively labeled neural data for "click" and "non-click" events during BCI use.
  • Utilized linear discriminant analysis (LDA) for click log-likelihood.
Keywords:
Adaptive classificationAmyotrophic lateral sclerosis (ALS)Augmentative and assistive communication (AAC)Brain-Machine Interface (BMI)Spinal cord injury (SCI)Stroke

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  • Employed retrospective target inference (RTI) for movement direction.
  • Applied supervised classifier training for decoder calibration.
  • Integrated real-time bias correction and firing rate tracking.

    • Main Results:

    • A BrainGate participant with ALS (T9) achieved sustained high-performance BCI control over 29 days and 11 sessions.
    • Continuous typing and cursor control were maintained without interruption for recalibration.
    • The novel calibration method proved effective for both cursor movement and clicking.

    Conclusions:

    • Retrospectively labeled decoder calibration significantly enhances BCI usability and clinical utility.
    • This approach removes the need for explicit, time-consuming calibration tasks.
    • Advances intracortical BCIs for individuals with severe motor impairments, restoring independence.