Cognitive Improvement Estimation using EEG Imaging after tDCS Therapy

Brain is the most important organ in the human body. The effects of brain impairment are wide ranging and include cognition, fatigue, sleep issues, headaches, dizziness, impaired self-awareness, clinical depression, attention and concentration problems, epilepsy, struggle in making decisions and many more. The objective of this paper is to the efficacy of noninvasive neuro modulatory technique Transcranial direct current stimulation (tDCS) in the estimation of brain cognitive state improvement using changes in small electrical brain voltages recorded by Electroencephalogram (EEG). Event related De synchronization (ERDs) is applied to the Motor Imagery Period (MIP) and Rest Period (RP) of pre stimulation and post stimulation EEG data of ten subjects. Common Spatial Pattern (CSP) is used for feature extraction and Linear Discrimination Analysis (LDA) a machine learning model is applied on these features for classification. The results suggest a decrease of contralateral ERDs oscillatory activity related to an event as per the hypothesis in anodal post stimulation than pre stimulation across all channels for six subjects. Further LDA applied on CSP proved that the classification accuracy between Motor imagery period (MIP) and the Rest period (RP) after the stimulation therapy is higher than the Pre stimulation Motor Imagery period (MIP) and Rest period (RP).