Quantifying the lagged Poincaré plot geometry of ultrashort heart rate variability series: automatic recognition of odor hedonic tone

Medical & Biological Engineering & Computing volume 58, pages1099–1112(2020)Cite this article

Abstract

The application of Poincaré plot analysis to characterize inter-beat interval dynamics has been successfully proposed in the scientific literature for the assessment of humans’ physiological states and related aberrations. In this study, we proposed novel descriptors to trace the evolution of Poincaré plot shape over the lags. Their reliability in ultra-short cardiovascular series analysis was validated on synthetic inter-beat series generated through a physiologically plausible integral pulse frequency modulation model. Furthermore, we used the proposed approach for the investigation of the direct relationship between autonomic nervous system (ANS) dynamics and hedonic olfactory elicitation, in a group of 30 healthy subjects. Participants with a similar olfactory threshold were selected, and were asked to score 5-s stimuli in terms of arousal and valence levels according to the Russell’s circumflex model of affect. Their ANS response was investigated in 35-s windows after the elicitation. Experimental results showed a gender-specific, high discriminant power of the proposed approach, discerning between pleasant and unpleasant odorants with an accuracy of 83.33% and 73.33% for men and for women, respectively.

Olfaction plays a crucial role in our life and is strictly related to the Autonomic Nervous System (ANS) activity, which can be monitored studying Heart Rate Variability. We used the Lagged Poincare Plot approach to recognize gender-specific ANS response in 35-second windows after the elicitation through pleasant/unpleasant odorants.

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Acknowledgments

Work partially supported by the Italian Ministry of Education and Research (MIUR) in the framework of the CrossLab project (Departments of Excellence).

Funding

Research partly supported by AEI and FEDER under the projects RTI2018-097723-B-I00, by CIBER de Bioingenieria, Biomateriales y Nanomedicina through Instituto de Salud Carlos III, by LMP44-18 and BSICoS group (T39-17R) funded by Gobierno de Aragón.

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Affiliations

  1. Department of Information Engineering, Research Centre E. Piaggio, University of Pisa, Via G. Caruso 16, Pisa, Italy

    M. Nardelli, G. Valenza, A. Greco, A. Lanatá & E. P. Scilingo

  2. BSICoS Group, Aragón Institute of Engineering Research (I3A), IIS Aragón, University of Zaragoza, Zaragoza, Spain

    R. Bailón

  3. CIBER of Bioengineering, Biomaterials and Nanomedicine (CIBER - BBN), Madrid, Spain

    R. Bailón

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  1. M. Nardelli
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  2. G. Valenza
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  5. E. P. Scilingo
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Correspondence to M. Nardelli.

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Nardelli, M., Valenza, G., Greco, A. et al. Quantifying the lagged Poincaré plot geometry of ultrashort heart rate variability series: automatic recognition of odor hedonic tone. Med Biol Eng Comput 58, 1099–1112 (2020). https://doi.org/10.1007/s11517-019-02095-7

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Keywords

  • Lagged poincaré plot
  • Pattern recognition
  • Support vector machine
  • Affective computing
  • Olfactory elicitation