@inproceedings{84f403076f5648739e0bf8046ce8db50,
title = "Generalizations of the subject-independent feature set for music-induced emotion recognition",
abstract = "Electroencephalogram (EEG)-based emotion recognition has been an intensely growing field. Yet, how to achieve acceptable accuracy on a practical system with as fewer electrodes as possible is less concerned. This study evaluates a set of subject-independent features, based on differential power asymmetry of symmetric electrode pairs [1], with emphasis on its applicability to subject variability in music-induced emotion classification problem. Results of this study have evidently validated the feasibility of using subject-independent EEG features to classify four emotional states with acceptable accuracy in second-scale temporal resolution. These features could be generalized across subjects to detect emotion induced by music excerpts not limited to the music database that was used to derive the emotion-specific features.",
author = "Lin, {Yuan Pin} and Chen, {Jyh Horng} and Duann, {Jeng Ren} and Lin, {Chin Teng} and Jung, {Tzyy Ping}",
year = "2011",
doi = "10.1109/IEMBS.2011.6091505",
language = "???core.languages.en_GB???",
isbn = "9781424441211",
series = "Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS",
pages = "6092--6095",
booktitle = "33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011",
note = "33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011 ; Conference date: 30-08-2011 Through 03-09-2011",
}