Fabrication and Dose–Response Simulation of Soft Dual-Sided Deep Brain Stimulation Electrode

A 16-channel dual-sided flexible electrode based on a polyimide substrate was designed and fabricated using micro-electromechanical system (MEMS) technology. The electrode exhibited an average impedance of 5.9 kΩ at 1 kHz and a charge storage capacity (CSC) of 10.63 mC/cm<sup>2</sup>. Concurrently, a three-dimensional finite element model incorporating electrical stimulation and micromotion-induced damage was established. The simulation results demonstrated that the implantation trauma caused by the bilateral electrode was significantly lower compared with silicon-based and cylindrical electrodes, while also enabling directional stimulation. Furthermore, leveraging the design of experiments (DOE) methodology, a multivariate regression model was developed to investigate the influence of key stimulation parameters-namely, current amplitude, frequency, and pulse width-on the volume of tissue activated (VTA). The results indicated that the regression model provided accurate predictions of VTA (R<sup>2</sup> = 0.912). Among the parameters, current amplitude and pulse width exerted a statistically significant influence on VTA size (<i>p</i> < 0.001), whereas the effect of frequency was comparatively minor (<i>p</i> = 0.387 > 0.05). This study presents the first successful fabrication and comprehensive dose-response analysis of a flexible bilateral DBS electrode. Its attributes of low implantation trauma, multi-channel capability, and directional stimulation offer a novel paradigm for precise neuromodulation. Additionally, the established stimulation parameter-VTA response model provides a robust theoretical foundation for optimizing therapeutic parameters in subsequent clinical applications.

Authors

Institutions

Publication Details

Journal
Micromachines
Published
2025-08-18
DOI
https://doi.org/10.3390/mi16080945
Primary Topic
Neuroscience and Neural Engineering
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Fabrication and Dose–Response Simulation of Soft Dual-Sided Deep Brain Stimulation Electrode

Bei Tong, Li Huang, Guoting Fu, Dengfei Yang et al.
Micromachines
Neuroscience and Neural Engineering
article

Fabrication and Dose–Response Simulation of Soft Dual-Sided Deep Brain Stimulation Electrode

Bei Tong, Li Huang, Guoting Fu, Dengfei Yang, Jian Zhang, Changmao Ni
article en

Abstract

A 16-channel dual-sided flexible electrode based on a polyimide substrate was designed and fabricated using micro-electromechanical system (MEMS) technology. The electrode exhibited an average impedance of 5.9 kΩ at 1 kHz and a charge storage capacity (CSC) of 10.63 mC/cm<sup>2</sup>. Concurrently, a three-dimensional finite element model incorporating electrical stimulation and micromotion-induced damage was established. The simulation results demonstrated that the implantation trauma caused by the bilateral electrode was significantly lower compared with silicon-based and cylindrical electrodes, while also enabling directional stimulation. Furthermore, leveraging the design of experiments (DOE) methodology, a multivariate regression model was developed to investigate the influence of key stimulation parameters-namely, current amplitude, frequency, and pulse width-on the volume of tissue activated (VTA). The results indicated that the regression model provided accurate predictions of VTA (R<sup>2</sup> = 0.912). Among the parameters, current amplitude and pulse width exerted a statistically significant influence on VTA size (<i>p</i> < 0.001), whereas the effect of frequency was comparatively minor (<i>p</i> = 0.387 > 0.05). This study presents the first successful fabrication and comprehensive dose-response analysis of a flexible bilateral DBS electrode. Its attributes of low implantation trauma, multi-channel capability, and directional stimulation offer a novel paradigm for precise neuromodulation. Additionally, the established stimulation parameter-VTA response model provides a robust theoretical foundation for optimizing therapeutic parameters in subsequent clinical applications.

MicromachinesVol. 16(8)
Wuhan University of Technology (CN)
Openalex Percentile: Top 77%
Neuroscience and Neural Engineering
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.