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• W2553519098 abstract "Emotion recognition is of major importance towards the acceptability of Human-Computer Interaction systems, and several approaches to emotion classification using features extracted from biosignals have already been developed. This analysis is, in general, performed on a signal-specific basis, and can bring a significant complexity to those systems. In this paper we propose a signal-independent approach on marking specific signal events. In this preliminary study, the developed algorithm was applied on ECG and EMG signals. Based on a morphological analysis of the signal, the algorithm allows the detection of significant events within those signals. The performance of our algorithm proved to be comparable with that achieved by signal-specific processing techniques on events detection. Since no previous knowledge or signal-specific pre-processing steps are required, the presented approach is particularly interesting for automatic feature extraction in the context of emotion recognition systems." @default.
• W2553519098 created "2016-11-30" @default.
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• W2553519098 date "2012-01-01" @default.
• W2553519098 modified "2023-09-23" @default.
• W2553519098 title "Towards Emotion Related Feature Extraction based on Generalized Source-Independent Event Detection" @default.
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• W2553519098 doi "https://doi.org/10.5220/0003891900710078" @default.
• W2553519098 hasPublicationYear "2012" @default.
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