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Implications for a Wireless, External Device System to Study Electrocorticography.

David Rotermund1, Jonas Pistor2, Janpeter Hoeffmann3

  • 1Institute for Theoretical Physics, University of Bremen, 28359 Bremen, Germany. davrot@neuro.uni-bremen.de.

Sensors (Basel, Switzerland)
|April 5, 2017
PubMed

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Summary
This summary is machine-generated.

This study presents an open-source, wireless brain implant design using readily available components. This reusable system simplifies the creation of neuronal interfaces for medical applications.

Area of Science:

  • Biomedical Engineering
  • Neuroscience
  • Medical Devices

Background:

  • Implantable neuronal interfaces are crucial for future medical applications.
  • Developing these implants is complex, requiring expertise across multiple technological domains.
  • Wireless data and energy transmission are essential to mitigate infection risks and long-term complications associated with wired implants.

Purpose of the Study:

  • To investigate the feasibility of a reusable design for wireless neuronal implants and base stations.
  • To provide a starting point for research groups entering the field of brain-computer interfaces.
  • To develop a fully wireless system using only commercial off-the-shelf components.

Main Methods:

  • Designed a wireless neuronal implant system utilizing exclusively commercial off-the-shelf components.
Keywords:
ECoGneuro-implantneuro-prostheticopen hardwarewireless implant

Related Experiment Videos

  • Developed an external base station compatible with the implant.
  • Ensured all design files are available as open source to facilitate adoption.

    • Main Results:

    • Successfully created a fully wireless neuronal implant capable of measuring electrocorticography (ECoG) signals.
    • The system enables simultaneous recording from 128 locations on the brain's surface.
    • The design is based on accessible, non-proprietary components, promoting wider use.

    Conclusions:

    • A reusable, open-source design for wireless neuronal implants is achievable using commercial off-the-shelf components.
    • This approach lowers the barrier to entry for developing advanced brain-computer interfaces.
    • The presented system offers a practical foundation for future medical applications requiring brain interfaces.