An Automated Electrode Placement Method for Optimizing Non-Invasive Electromagnetic Brain Stimulation

Transcranial electrical stimulation techniques such as transcranial direct current stimulation (tDCS), transcranial alternating current stimulation (tACS), and temporal interference stimulation (TIS) require accurate and reproducible electrode placement to achieve precise electric field targeting. However, conventional electroencephalography (EEG) electrode placement systems (10–20 and 10–10) cover only the scalp and are limited in stimulating cerebellar or deep brain regions. In this study, we developed an extended EEG-based electrode localization algorithm that includes both facial and lower occipital regions on a 3D human head mesh model. The algorithm, implemented in MATLAB, uses four anatomical landmarks to automatically compute 3D electrode coordinates and introduces new chin and posterior (inferior occipital) reference points to expand coverage. The proposed method minimizes spatial placement error and provides a standardized, visualizable framework for high-precision electromagnetic stimulation in research and clinical applications.