• Varsha Ankush Jamadade

The research on neural engineering that focuses on the classification of emotional, mental, physical and no stress through the use of Electroencephalography (EEG) signal analysis is presented. In this study, stress is classified through an objective measure which is EEG signal analysis. The features of the EEG recordings are pre-processed to remove baseline drift. Statistical features and power spectral density features are extracted for classification. Artificial Neural Network (ANN) is used for the classification. Stress will then be classified into emotional, mental, high stress and no stress through quantitative analysis of EEG signals.

EEG, Physiological, ANN, Mental Stress, Emotional Stress, no Stress, High stress

"Stress Measurement and Classification using EEG Signal Analysis", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.310-318, June 2019, Available :http://www.jetir.org/papers/JETIR1907E46.pdf

"Stress Measurement and Classification using EEG Signal Analysis", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp310-318, June 2019, Available at : http://www.jetir.org/papers/JETIR1907E46.pdf