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Soft, conformal bioelectronics for a wireless human-wheelchair interface.

Saswat Mishra1, James J S Norton2, Yongkuk Lee1

  • 1Department of Mechanical and Nuclear Engineering, School of Engineering, Virginia Commonwealth University, Richmond, VA 23284, USA.

Biosensors & Bioelectronics
|February 3, 2017
PubMed
Summary

Researchers developed a comfortable, dry bioelectronic sensor for controlling wheelchairs using eye movements. This new system offers high-fidelity electrooculograms (EOGs) for precise, hands-free robotic wheelchair navigation.

Keywords:
Conformal contactElectrooculogramsFractal structureHuman-wheelchair interfaceSoft electrodeStretchable electronics

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Area of Science:

  • Biomedical Engineering
  • Rehabilitation Technology
  • Human-Machine Interface

Background:

  • Over 3 million individuals worldwide depend on wheelchairs for mobility.
  • Current non-invasive electrophysiological interfaces often cause discomfort and skin irritation due to gel and adhesive electrodes.
  • There is a need for more ergonomic and user-friendly human-machine interfaces for assistive devices.

Purpose of the Study:

  • To introduce a novel, comfortable, dry bioelectronic sensor for electrooculogram (EOG) recording.
  • To evaluate the performance of the soft biosensor compared to conventional gel electrodes.
  • To demonstrate the feasibility of using this system for hands-free control of a robotic wheelchair.

Main Methods:

  • Development of a mechanically comfortable, dry bioelectronic sensor with conformal skin contact.
  • Recording of electrooculograms (EOGs) using the novel sensor and conventional gel electrodes.
  • Quantitative signal analysis and infrared thermography to assess sensor performance and comfort.
  • Implementation of a classification algorithm with optimized features for eye movement detection.
  • Integration of the soft bioelectronics into a Bluetooth-enabled system for robotic wheelchair control.

Main Results:

  • The soft biosensor achieved high-fidelity EOG recordings comparable to traditional gel electrodes.
  • Infrared thermography indicated the advantages of the soft biosensor for ergonomic applications.
  • A classification algorithm achieved 94% accuracy in identifying five distinct eye movements.
  • The Bluetooth-enabled system enabled precise, hands-free control of a robotic wheelchair using EOG signals.

Conclusions:

  • The developed soft, dry bioelectronic sensor provides a comfortable and effective alternative to conventional EOG electrodes.
  • This technology facilitates an ergonomic human-machine interface for assistive devices.
  • The system demonstrates significant potential for intuitive and precise control of robotic wheelchairs, enhancing mobility for users.