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Proceedings 2017, 1(3), 140; doi:10.3390/IS4SI-2017-04005

Inherent Emotional Feature Extraction of Neonatal Cry

Center for Data Mining and Systems Biology, College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China
Presented at the IS4SI 2017 Summit DIGITALISATION FOR A SUSTAINABLE SOCIETY, Gothenburg, Sweden, 12–16 June 2017.
Author to whom correspondence should be addressed.
Published: 9 June 2017
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Mining the inherent emotional feature of life is of great significance, and the method to extract the inherent emotional feature with a small number of samples is explored based on neonatal cry in this study. The minimum embedding dimension is taken as the nonlinear feature representing nervous system activity and emotion, and is also analyzed at multiple scales. It is found that the minimum embedding dimension of pain cries is higher than that of sad cries, and has a certain change rule in different frequency bands. The results are consistent with related emotional research of brain nerve activity and the characteristics of the pain cry, and may help in the study of information ecology of the brain in different emotions.
Keywords: inherent emotional feature extraction; nonlinear method; minimum embedding dimension; neonatal cry inherent emotional feature extraction; nonlinear method; minimum embedding dimension; neonatal cry
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Zhao, X.; Meng, J.; Xu, W. Inherent Emotional Feature Extraction of Neonatal Cry. Proceedings 2017, 1, 140.

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