Investigating Impact of Current Pulse Waveform and Simulation Frequency on Deep Brain Stimulation

Bio-computational models have a significant impact on the design and development of medical devices. This approach allows investigation of various medical device parameter settings which would be infeasible to design by using the experimental test. Using the optimal parameters for these neuromodulator systems is crucial for the patient safety. Computational modelling is a fundamental tool in the challenge to improve targeting and stimulation parameters in deep brain stimulation (DBS). Specifically, it may be difficult to design an optimal neuromodulator for Parkinson's disease fusing DBS due to variations in many parameters including simulation waveform shape, pulse width, and amplitude as well as passive factors. This study investigates the impact of using different waveforms based on different pulse widths using such advanced bio-computational modelling systems. The volume conductor of a human head was generated based on average human head thickness including fundamental tissue layers. Then, the DBS electrode array was designed and merged with the computational model to analyse the results using different frequency ranges. Also, the fundamentals of the computational model developments were highlighted for the computational model designers. Then, the results were calculated based on electrical and current density distributions using time-based simulation. It was shown that the simulation frequency and simulation waveform shape have a significant impact on the outcome. The results suggested that the capacitive effect cannot be ignored at the higher frequency levels due to having a significant impact on the electrical potential, current density, and electric field distributions in the region of interest.