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Updated: Sep 9, 2025

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An algorithmic procedure for measuring deep brain stimulation-induced capsular activation using motor evoked

Eric R Cole1,2,3, Enrico Opri4, Seyyed Bahram Borgheai2

  • 1Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, GA, 30332, USA.

Medrxiv : the Preprint Server for Health Sciences
|September 5, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces an automated method to detect motor evoked potentials (mEPs) using electromyography, offering an objective measure for deep brain stimulation (DBS) side effects in Parkinson's disease patients.

Keywords:
DBS side effectscorticospinal tractinternal capsuleprogrammingsignal processing

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Area of Science:

  • Neuroscience
  • Biomedical Engineering
  • Clinical Neurology

Background:

  • Deep brain stimulation (DBS) for Parkinson's disease requires precise parameter adjustment to prevent motor side effects.
  • Current methods rely on subjective patient self-reporting, leading to potential treatment delays and suboptimal outcomes.
  • Motor evoked potentials (mEPs) detected via electromyography (EMG) present a promising objective biomarker for these side effects.

Purpose of the Study:

  • To develop and validate an automated algorithm for detecting and quantifying mEPs.
  • To establish a reliable biomarker for objective assessment of DBS-induced motor side effects.
  • To improve the precision and efficiency of DBS programming and surgical targeting.

Main Methods:

  • Developed signal processing techniques to accurately detect mEPs, minimizing stimulation artifacts and noise.
  • Integrated multi-channel EMG responses into a single 'mEP score' biomarker.
  • Analyzed intraoperative recordings from 54 subthalamic nucleus (STN) leads to characterize mEP features (frequency, latency, amplitude, waveform similarity).

Main Results:

  • Successfully automated the detection and quantification of mEPs.
  • Demonstrated that the mEP score correlates with DBS amplitude and contact configuration, aligning with known STN-capsular anatomy.
  • Quantified key physiological characteristics of mEPs across a large patient cohort.

Conclusions:

  • The developed automated approach provides an end-to-end solution for measuring DBS-induced motor side effects.
  • This biomarker can aid in optimizing DBS programming and surgical targeting for Parkinson's disease.
  • Objective mEP measurement enhances the precision and efficiency of Parkinson's disease treatment.