Abstract
Machine learning has become the frontier for advanced development techniques, and this is very prevalent in the field of medical science and engineering. Emotion recognition using signals are directly received from the brain can be used to accurately identify and diagnose medical health and psychological problems. In this paper, EEG signals are used to predict the active mood or emotional state of the person’s brain wave signals. Data is fed thorough all the given algorithms and tuned. DEAP data in the dataset that is fed into all the above algorithms and the results are observed. In the comparative testing phase, SVM is the most accurate machine learning algorithm, yielding a resulting f1 of about 84.73%. The results of this proposed paper shows the different grading patterns that are used to predict the various sentimental states.
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Geetha, A., Bharathi, S.S., Bernard, A.R., Teja, R.Y., Pradeep, K. (2022). Emotional Recognition System Using EEG and Psycho Physiological Signals. In: Hu, YC., Tiwari, S., Trivedi, M.C., Mishra, K.K. (eds) Ambient Communications and Computer Systems. Lecture Notes in Networks and Systems, vol 356. Springer, Singapore. https://doi.org/10.1007/978-981-16-7952-0_30
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DOI: https://doi.org/10.1007/978-981-16-7952-0_30
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