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Closed-loop programming using external responses for deep brain stimulation in Parkinson's disease.

Fuyuko Sasaki1, Genko Oyama1, Satoko Sekimoto1

  • 1Department of Neurology, Juntendo University School of Medicine, Tokyo, Japan.

Parkinsonism & Related Disorders
|February 8, 2021
PubMed
Summary

A new closed-loop algorithm (CLA) for deep brain stimulation (DBS) programming in Parkinson's disease (PD) offers similar symptom improvement to standard methods but requires fewer programming steps. This approach optimizes DBS settings efficiently for both patients and clinicians.

Keywords:
Automated programmingClosed loop programmingDeep brain stimulationObjective assessmentParkinson's diseaseWearable sensor

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Area of Science:

  • Neurology
  • Biomedical Engineering
  • Movement Disorders

Background:

  • Deep brain stimulation (DBS) is a key treatment for Parkinson's disease (PD).
  • Programming DBS requires expertise and time, with increasing complexity due to new technologies.
  • Current methods face challenges in optimizing stimulation parameters efficiently.

Purpose of the Study:

  • To evaluate the efficacy of a closed-loop algorithm (CLA) for DBS programming in PD patients.
  • To compare CLA with standard of care (SOC) programming using objective motor assessments.
  • To determine if CLA reduces the number of programming steps needed.

Main Methods:

  • A randomized, double-blind, crossover study involving 12 PD patients with bilateral subthalamic nucleus DBS.
  • DBS programming was performed using both SOC and CLA methods.
  • Outcomes measured included Unified Parkinson's Disease Rating Scale Part III (UPDRS-III) and sensor-based motor scores, alongside programming step counts.

Main Results:

  • Both SOC and CLA significantly improved UPDRS-III and sensor-based scores compared to baseline.
  • No significant difference in clinical efficacy was found between SOC and CLA.
  • CLA programming required significantly fewer steps than SOC programming.
  • No serious adverse events were reported.

Conclusions:

  • CLA is a viable method for optimizing DBS settings in PD, providing comparable therapeutic benefits to SOC.
  • CLA significantly reduces the number of programming sessions required.
  • Automated DBS programming via CLA can lessen the clinical and patient burden associated with device management.