Optimizing Multi-Channel tES to Improve Robustness to Electrode Displacement: A Simulation Study
Poster No:
40
Submission Type:
Abstract Submission
Authors:
Sangwoo Lee1, Jaehoon Jeong1, Chang-Hwan Im1
Institutions:
1Hanyang University, Seoul, Seoul
First Author:
Co-Author(s):
Introduction:
In the conventional transcranial electrical stimulation (tES) with a pair of electrodes, small drift of electrode locations could alter the pattern of electric field inside the brain [1]. In this paper, we hypothesized that the similar problem might arise when a commercialized tES system with multiple electrodes mounted on an elastic cap is used. Therefore, the influence of the electrode displacement on the electric field was investigated. In addition, a new optimization method considering the possible displacements of the electrodes was proposed to improve the robustness to the electrode displacement during the repeated use of the tES system.
Methods:
A digitizer is used to estimate the average displacement of electrodes during repeated self-wearing of the electrode cap. Ten participants tried on a cap by themselves a total of 25 times. We generated five models for finite element method (FEM) based on the electrode locations of the international 10-10 EEG system: the original location, forward shift, backward shift, rightward shift, and leftward shift.
Left hand motor cortex (HM), right intraparietal sulcus (IPS), left dorsolateral prefrontal cortex (DLPFC), and visual cortex (VC) were set as the regions of interest (ROIs). We optimized the input current distributions for each of the five electrode locations using the FEM-based field simulation and the least squares algorithm to best modulate the designated ROIs.
We then generated a new current distribution by averaging the five optimization results. We compared how the intensity of electric field (from the mean value within the ROI) and the focality of electric field (from the maximum value outside the ROI divided by the minimum value within the ROI) decreased when the electrode locations were shifted.
Left hand motor cortex (HM), right intraparietal sulcus (IPS), left dorsolateral prefrontal cortex (DLPFC), and visual cortex (VC) were set as the regions of interest (ROIs). We optimized the input current distributions for each of the five electrode locations using the FEM-based field simulation and the least squares algorithm to best modulate the designated ROIs.
We then generated a new current distribution by averaging the five optimization results. We compared how the intensity of electric field (from the mean value within the ROI) and the focality of electric field (from the maximum value outside the ROI divided by the minimum value within the ROI) decreased when the electrode locations were shifted.
Results:
The average displacement of electrodes was 1.08 cm, based on which the electrode locations were shifted. Our method showed higher intensity and focality in all ROIs, exhibiting the superiority of the proposed method.
Conclusions:
In this study, we improved the robustness of tES to the electrode shift by employing a new optimization method that averages optimization results for five FEM models with different electrode displacements. It is expected that the proposed optimization method can be a useful tool to improve the robustness and reliability of tES in practical scenarios.
Brain Stimulation:
Non-invasive Electrical/tDCS/tACS/tRNS 1
Modeling and Analysis Methods:
Methods Development 2
Keywords:
Modeling
Other - transcranial electrical stimulation(tES); Finite element method(FEM; Electrode Drift
1|2Indicates the priority used for review