EEG dynamics during music appreciation
EEG dynamics during music appreciation
This study explores the electroencephalographic (EEG) correlates of emotions during music listening. Principal component analysis (PCA) is used to correlate EEG features with complex music appreciation. This study also applies machine-leaning algorithms to demonstrate the feasibility of classifying EEG dynamics in four subjectively-reported emotional states. The high classification accuracy (81.58+/-3.74%) demonstrates the feasibility of using EEG features to assess emotional states of human subjects. Further, the spatial and spectral patterns of the EEG most relevant to emotions seem reproducible across subjects.
- University of California, San Diego United States
- University of California, San Diego United States
- National Taiwan University of Arts Taiwan
Brain Mapping, Principal Component Analysis, Emotions, Humans, Electroencephalography, Electrodes, Music
Brain Mapping, Principal Component Analysis, Emotions, Humans, Electroencephalography, Electrodes, Music
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