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Human emotion characterization by heart rate variability analysis guided by respiration

Valderas Yamuza, MT; Bolea, J; Orini, M; Laguna, P; Orrite, C; Vallverdu, M; Bailon, R; (2019) Human emotion characterization by heart rate variability analysis guided by respiration. IEEE Journal of Biomedical and Health Informatics , 23 (6) pp. 2446-2454. 10.1109/JBHI.2019.2895589. Green open access

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Abstract

Developing a tool which identifies emotions based on their effect on cardiac activity may have a potential impact on clinical practice, since it may help in the diagnosing of psycho-neural illnesses. In this study, a method based on the analysis of heart rate variability (HRV) guided by respiration is proposed. The method was based on redefining the high frequency (HF) band, not only to be centered at the respiratory frequency, but also to have a bandwidth dependent on the respiratory spectrum. The method was first tested using simulated HRV signals, yielding the minimum estimation errors as compared to classical and respiratory frequency centered at HF band based definitions, independently of the values of the sympathovagal ratio. Then, the proposed method was applied to discriminate emotions in a database of video-induced elicitation. Five emotional states, relax, joy, fear, sadness and anger, were considered. The maximum correlation between HRV and respiration spectra discriminated joy vs. relax, joy vs. each negative valence emotion, and fear vs. sadness with p-value ≤ 0.05 and AUC ≥ 0.70. Based on these results, human emotion characterization may be improved by adding respiratory information to HRV analysis.

Type: Article
Title: Human emotion characterization by heart rate variability analysis guided by respiration
Open access status: An open access version is available from UCL Discovery
DOI: 10.1109/JBHI.2019.2895589
Publisher version: https://doi.org/10.1109/JBHI.2019.2895589
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Heart rate variability, Videos, Resonant frequency, Correlation, Bandwidth, Frequency estimation
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Cardiovascular Science
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Cardiovascular Science > Population Science and Experimental Medicine
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Cardiovascular Science > Population Science and Experimental Medicine > MRC Unit for Lifelong Hlth and Ageing
URI: https://discovery.ucl.ac.uk/id/eprint/10080053
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