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This study presents a closed-loop system for automated vagus nerve stimulation (VNS) during motor rehabilitation. The system uses video analysis to detect successful movements and wirelessly trigger transcutaneous VNS (tVNS), aiding motor recovery.

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Area of Science:

  • Neuroscience
  • Rehabilitation Engineering
  • Biomedical Technology

Background:

  • Vagus nerve stimulation (VNS) shows promise for motor rehabilitation in animals.
  • Translating VNS to human rehabilitation requires non-invasive, automated, real-time movement quality assessment.
  • Existing methods lack objective, automated, and minimally constrained approaches for VNS triggering.

Purpose of the Study:

  • To develop an integrated closed-loop system for automated transcutaneous VNS (tVNS) triggered by real-time movement classification.
  • To create a conformable tVNS electrode for non-invasive application.
  • To demonstrate the system's efficacy in a dance therapy use case (backward walking).

Main Methods:

  • Developed a markerless video analysis model for real-time movement classification.
  • Integrated the video analysis with a wireless system to trigger tVNS upon detecting successful movements.
  • Utilized Bluetooth Low Energy for communication between the classification and stimulation components.
  • Designed a film-like, conformable tVNS electrode for the outer ear.

Main Results:

  • The video analysis model achieved 0.91 precision and 0.72 recall for step detection, with a 0.93 F1 score for classifying successful backward steps.
  • The integrated system successfully triggered tVNS in 71.3% of successful movements.
  • The system demonstrated a low latency of 2.24 seconds from video capture to tVNS delivery.

Conclusions:

  • The developed closed-loop system enables real-time, automated, and non-invasive neurostimulation for motor rehabilitation.
  • This technology represents a significant advancement towards patient-driven, at-home rehabilitation.
  • The system showcases the potential of low-cost, automated closed-loop neurostimulation technologies.