ECG Signal Feature Selection for Emotion Recognition - Lichen Xun; Gang Zheng (Institute of Advanced Engineering and Science, 2013)
This paper aims to study the selection of features based on ECG in emotion recognition. In the process of features selection, we start from existing feature selection algorithm, and pay special attention to some of the intuitive value on ECG waveform as well. Through the use of ANOVA and heuristic search, we picked out the different features to distinguish joy and pleasure these two emotions, then we combine this with pathological analysis of ECG signals by the view of the medical experts to discuss the logic corresponding relation between ECG waveform and emotion distinguish. Through experiment, using the method in this paper we only picked out five features and reached 92% of accuracy rate in the recognition of joy and pleasure. DOI: http://dx.doi.org/10.11591/telkomnika.v11i3.2215