Mental State Evaluation with Machine Learning by utilizing Brain Signals

Abstract

Mental State of the subject is evaluated by using EEG signals. EEG signal from the brain is taken by using Mind wave kit, which gives the raw EEG waves by the non-invasive method only using single electrode. To induce emotion in to the subject different emotional videos are shown and respective emotion EEGs are collected. so the electrical different EEG wave Alpha, Beta, Delta, Gama and theta varies, different waves having its nativity according to the emotional changes. Lucid scribe toolkit support to collection of data from the Mobile mind wave, the data exported to the excel and by finding the minimum and maximum value of every EEG wave, this is in the numerical values with known Mental states are set with numerical values like 0 neutral, 1 Happy, 2 Disgust, 3 Sad, 4 Angry. In this work Mental state evaluation using signal processing is carried by preparing 280 datasets are prepared by showing them different videos related to respective emotions. By using neuro sky's Mindwave kit brain waves are recorded at the forehead values are tabulated accordingly. 280 datasets are fed into Orange, open-source machine learning and data visualization module and algorithms are compared by extracting confusion matrices.