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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Jonghwa Kim Andre, E. |
| Copyright Year | 2008 |
| Description | Author affiliation: Fac. of Appl. Comput. Sci., Univ. of Augsburg, Augsburg (Jonghwa Kim; Andre, E.) |
| Abstract | Endowing the computer with the ability to recognize human emotional states is the most important prerequisites for realizing an affect-sensitive human-computer interaction. In this paper, we deal with all the essential stages of an automatic emotion recognition system using multichannel physiological measures, from data collection to the classification process. Particularly we develop two different classification methods, feature-level fusion and emotion-specific classification scheme. Four-channel biosensors were used to measure electromyogram, electrocardiogram, skin conductivity, and respiration changes while subjects were listening to music. A wide range of physiological features from various analysis domains is proposed to correlate them with emotional states. Classification of four musical emotions is performed by using feature-level fusion combined with an extended linear discriminant analysis (pLDA). Furthermore, by exploiting a dichotomic property of the 2D emotion model, we developed a novel scheme of emotion-specific multilevel dichotomous classification (EMDC) and compare its performance with direct multiclass classification using the pLDA feature-level fusion. Improved recognition accuracy of 95% and 70% for subject-dependent and subject-independent classification, respectively, is achieved by using the EMDC scheme. |
| Starting Page | 114 |
| Ending Page | 119 |
| File Size | 663105 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781424421435 |
| DOI | 10.1109/MFI.2008.4648119 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2008-08-20 |
| Publisher Place | South Korea |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Time series analysis Electrocardiography Electromyography Heart rate variability Emotion recognition Entropy Biosensors |
| Content Type | Text |
| Resource Type | Article |
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