MRCP 기반 EEG 특징을 이용한 tDCS에 의한 개인별 운동 능력 향상 예측

Abstract

Transcranial direct current stimulation (tDCS) is a non-invasive neuromodulation technique that modulates cortical excitability and induces neural plasticity, thereby drawing attention for its potential to enhance motor function. However, even with identical stimulation protocols, some individuals do not exhibit improvements in motor performance, highlighting the need for electrophysiological markers that reflect inter-individual variability in responsiveness. In this study, we propose a machine learning-based predictive model to estimates tDCS-induced motor improvement using EEG features derived from movement-related cortical potentials (MRCPs), achieving a classification accuracy of 71.07%±8.84% across 15 participants.