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Nerve stimulator for regional anaesthesia procedures with automatic interactive closed-loop control.

Carlos A Ferri1, Antonio A F Quevedo1,2

  • 1a Department of Biomedical Engineering, School of Electrical and Computer Engineering , University of Campinas , Campinas , Brazil.

Journal of Medical Engineering & Technology
|March 16, 2019
PubMed
Summary
This summary is machine-generated.

This study introduces an automated method for controlling peripheral nerve stimulator intensity, using accelerometers and electromyography (EMG). The automated technique proved as effective as manual adjustments, with no significant differences in procedure or blockade latency times.

Keywords:
Nerve stimulatoraccelerometerautomatic controlelectromyographyregional anaesthesia

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Area of Science:

  • Anesthesiology
  • Biomedical Engineering
  • Neuroscience

Background:

  • Peripheral nerve stimulators are widely used by anesthesiologists.
  • Current commercial devices require manual adjustment of stimulus intensity.
  • Automation of stimulus control could improve efficiency and precision.

Purpose of the Study:

  • To develop and validate an automated method for controlling current intensity in peripheral nerve stimulators.
  • To assess the efficacy of using accelerometer and surface electromyography (sEMG) sensors for this automation.
  • To compare the performance of the automated method against manual intensity adjustment.

Main Methods:

  • Modified an existing nerve stimulator prototype by integrating an accelerometer and an sEMG module.
  • Conducted tests in two phases: sensor behavior observation and control algorithm implementation.
  • Compared procedure time, blockade latency, and needle-nerve distance between manual and automated methods.

Main Results:

  • No significant differences were observed in procedure time (manual: 12.5 ± 2.3s; automatic: 11.6 ± 1.9s) or blockade latency (manual: 11.6 ± 1.1s; automatic: 11.9 ± 1.2s).
  • Similar needle-nerve distances were achieved with both manual and automated control across various current intensities (1.0, 0.8, 0.5, 0.3 mA).
  • The accelerometer alone was sufficient for detecting muscle contractions.

Conclusions:

  • Automating current intensity updates using accelerometer and/or electromyography is a satisfactory technique.
  • The use of an accelerometer alone is sufficient for detecting muscle contractions during nerve stimulation.
  • This automation offers a viable alternative to manual control in peripheral nerve stimulation.