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Cursor control by Kalman filter with a non-invasive body-machine interface.

Ismael Seáñez-González1, Ferdinando A Mussa-Ivaldi

  • 1Department of Biomedical Engineering, Northwestern University, McCormick School of Engineering and Applied Science, 2145 Sheridan Road, Evanston, IL 60208, USA. Sensory Motor and Performance Program, Rehabilitation Institute of Chicago, 345 E. Superior St, Suite 1406, Chicago, IL 60611-2654, USA.

Journal of Neural Engineering
|September 23, 2014
PubMed
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This study introduces a new upper-body motion-controlled computer cursor system using inertial measurement units (IMUs). Utilizing redundant IMU signals enhances control performance, offering a promising alternative to brain-machine interfaces.

Area of Science:

  • Biomedical Engineering
  • Human-Computer Interaction
  • Rehabilitation Engineering

Background:

  • Traditional human-machine interfaces (HMIs) can be limited for individuals with severe motor impairments.
  • Brain-machine interfaces (BMIs) offer potential but are invasive and complex.
  • Non-invasive body-machine interfaces (BMIs) are an emerging area for assistive technology.

Purpose of the Study:

  • To develop and evaluate a novel 2D computer cursor control system using inertial measurement units (IMUs) on the upper body.
  • To investigate the impact of redundant IMU signal utilization on cursor control performance.
  • To explore the potential of IMU-based HMIs as an alternative or complement to BMIs.

Main Methods:

  • A calibration method mapped shoulder motions to cursor kinematics.

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  • A Kalman filter estimated cursor coordinates from upper-body motions.
  • Performance was assessed using a center-out reaching task with varying IMU data inputs.

    • Main Results:

    • Leveraging redundant IMU signals significantly improved cursor control performance.
    • The developed IMU-based HMI demonstrated effective 2D cursor control.
    • The system shows potential as a non-invasive alternative to BMIs.

    Conclusions:

    • This novel IMU-based HMI system enhances cursor control through redundant signal processing.
    • The technology provides a viable, non-invasive platform for assistive device control.
    • It holds promise for individuals with high-tetraplegia to operate assistive technologies like wheelchairs.