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

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.