Anytime multipurpose emotion recognition from EEG data using a Liquid State Machine based framework

• Published in: Artificial intelligence in medicine Vol. 86; pp. 1 - 8
• Main Authors: Al Zoubi, Obada, Awad, Mariette, Kasabov, Nikola K.
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier B.V 01.03.2018
• Subjects: Brain - physiology; Brain Waves; Computer Simulation; EEG; Electroencephalography - methods; Emotion recognition; Emotions; Feature extraction; Humans; Liquid State Machine; Machine Learning; Pattern recognition; Pattern Recognition, Automated - methods; Photic Stimulation; Predictive Value of Tests; Reproducibility of Results; Signal Processing, Computer-Assisted; Time Factors; Emotion recognition; Feature extraction; Pattern recognition; Liquid State Machine; EEG; Machine learning

Recent technological advances in machine learning offer the possibility of decoding complex datasets and discern latent patterns. In this study, we adopt Liquid State Machines (LSM) to recognize the emotional state of an individual based on EEG data. LSM were applied to a previously validated EEG da...