Towards emotion related feature extraction based on generalized source-independent event detection

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.