Characterization of the stimulus waveforms generated by implantable pulse generators for deep brain stimulation. Issue 4 (April 2018)

• Record Type: Journal Article
• Authors: Lempka, Scott F.; Howell, Bryan; Gunalan, Kabilar; Machado, Andre G.; McIntyre, Cameron C.
• Is Part Of: Clinical neurophysiology. Volume 129:Issue 4(2018:Apr.)
• Page Start: 731
• Page End: 742
• Publication Date: 2018-04
• Subjects: Deep brain stimulation -- Neuromodulation -- Neurostimulation -- Neural activation -- Computational modeling -- Parkinson's disease; Neurophysiology -- Periodicals; Electroencephalography -- Periodicals; Electromyography -- Periodicals; Neurology -- Periodicals; 612.8
• DOI: 10.1016/j.clinph.2018.01.015
• Languages: English
• ISSNs: 1388-2457

Abstract

Highlights: The electrode interface and IPG circuitry affect the voltages applied to the brain. Accurate representation of the IPG output affects theoretical axonal activation. Clinical decision support utilizing DBS models should include basic IPG circuitry. Abstract: Objective: To determine the circuit elements required to theoretically describe the stimulus waveforms generated by an implantable pulse generator (IPG) during clinical deep brain stimulation (DBS). Methods: We experimentally interrogated the Medtronic Activa PC DBS IPG and defined an equivalent circuit model that accurately captured the output of the IPG. We then compared the detailed circuit model of the clinical stimulus waveforms to simplified representations commonly used in computational models of DBS. We quantified the errors associated with these simplifications using theoretical activation thresholds of myelinated axons in response to DBS. Results: We found that the detailed IPG model generated substantial differences in activation thresholds compared to simplified models. These differences were largest for bipolar stimulation with long pulse widths. Average errors were ∼3 to 24% for voltage-controlled stimulation and ∼2 to 11% for current-controlled stimulation. Conclusions: Our results demonstrate the importance of including basic circuit elements (e.g. blocking capacitors, lead wire resistance, electrode capacitance) in model analysis of DBS. Significance: Computational models of DBS are now commonly used in academic research, industrial technology development, and in the selection of clinical stimulation parameters. Incorporating a realistic representation of the IPG output is necessary to improve the accuracy and utility of these clinical and scientific tools.