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Reconstructing time-domain data from discontinuous Percept™ PC and RC output using external data acquisition and

Jinxin Chen1, Mandy M Koop2, Kenneth B Baker3

  • 1Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States of America.

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Summary

Timing errors in Medtronic deep brain stimulation (DBS) recordings were identified and corrected using a novel algorithm. This method improves the accuracy of time synchronization for long-term DBS data analysis.

Keywords:
Biomedical signalsEvoked potentialsFrequency analysisFunctional electrical stimulationSignal acquisition and processing

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Area of Science:

  • Neuroscience
  • Biomedical Engineering
  • Signal Processing

Background:

  • Medtronic Percept™ PC and RC deep brain stimulation (DBS) systems offer recording capabilities.
  • Changes in stimulation frequency during DBS recording introduce time-domain segmentation and timing errors.
  • Accurate temporal data is crucial for analyzing neural activity during DBS.

Purpose of the Study:

  • To quantify timing errors in Medtronic Percept™ PC and RC DBS recordings.
  • To develop and validate an algorithm for correcting these timing errors.
  • To enable accurate time synchronization in DBS data, particularly for long recordings.

Main Methods:

  • Ex-vivo local field potential recordings were performed using Percept™ DBS leads.
  • Stimulation frequency was altered, and timing discrepancies were measured against an external gold-standard stimulator.
  • A novel algorithm was developed to correct timing shifts based on observed error patterns and true frequency change events.

Main Results:

  • Significant timing errors, characterized by sawtooth patterns and linear ramps with sudden drops, were observed in both PC and RC systems.
  • Raw timing errors ranged from -400 to 400ms for PC and -1 to 1s for RC.
  • The developed algorithm successfully reduced timing errors to -10.07±45.06ms for PC and -23.52±17.32ms for RC.

Conclusions:

  • The study successfully characterized and quantified timing errors in Medtronic DBS recordings.
  • A novel algorithm effectively corrects these timing errors, significantly improving temporal accuracy.
  • This approach is applicable in-vivo, potentially using electroencephalography, to enhance the reliability of long-term DBS data analysis.