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Author (up) A. Lanata; A. Guidi; G. Valenza; P. Baragli; E. P. Scilingo doi  openurl
  Title Quantitative heartbeat coupling measures in human-horse interaction Type Conference Article
  Year 2016 Publication 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) Abbreviated Journal 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (E  
  Volume Issue Pages 2696-2699  
  Keywords electrocardiography; medical signal processing; signal classification; time series; Dtw; Hrv; Mpc; Msc; complex biological systems; dynamic time warping; grooming; heart rate variability time series; heartbeat dynamics; human-horse dynamic interaction; magnitude squared coherence; magnitude-phase coupling; mean phase coherence; nearest mean classifier; quantitative heartbeat coupling; real human-animal interaction; time duration; visual-olfactory interaction; Coherence; Couplings; Electrocardiography; Heart rate variability; Horses; Protocols; Time series analysis  
  Abstract Abstractó We present a study focused on a quantitative estimation of a human-horse dynamic interaction. A set of measures based on magnitude and phase coupling between heartbeat dynamics of both humans and horses in three different conditions is reported: no interaction, visual/olfactory interaction and grooming. Specifically, Magnitude Squared Coherence (MSC), Mean Phase Coherence (MPC) and Dynamic Time Warping (DTW) have been used as estimators of the amount of coupling between human and horse through the analysis of their heart rate variability (HRV) time series in a group of eleven human subjects, and one horse. The rationale behind this study is that the interaction of two complex biological systems go towards a coupling process whose dynamical evolution is modulated by the kind and time duration of the interaction itself. We achieved a congruent and consistent

statistical significant difference for all of the three indices. Moreover, a Nearest Mean Classifier was able to recognize the three classes of interaction with an accuracy greater than 70%. Although preliminary, these encouraging results allow a discrimination of three distinct phases in a real human-animal interaction opening to the characterization of the empirically proven relationship between human and horse.
 
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (E  
  Series Volume Series Issue Edition  
  ISSN 1557-170x ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number Equine Behaviour @ team @ Serial 6175  
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Author (up) Lanata, A.; Guidi, A.; Valenza, G.; Baragli, P.; Scilingo, E. P. openurl 
  Title The Role of Nonlinear Coupling in Human-Horse Interaction: a Preliminary Study Type Conference Article
  Year 2017 Publication 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) Abbreviated Journal EMBC  
  Volume Issue Pages  
  Keywords  
  Abstract This study focuses on the analysis of humanhorse

dynamic interaction using cardiovascular information

exclusively. Specifically, the Information Theoretic Learning

(ITL) approach has been applied to a Human-Horse Interaction

paradigm, therefore accounting for the nonlinear information

of the heart-heart interplay between humans and horses.

Heartbeat dynamics was gathered from humans and horses

during three experimental conditions: absence of interaction,

visual-olfactory interaction, and brooming. Cross Information

Potential, Cross Correntropy, and Correntropy Coefficient were

computed to quantitatively estimate nonlinear coupling in a

group of eleven subjects and one horse. Results showed a

statistical significant difference on all of the three interaction

phases. Furthermore, a Support Vector Machine classifier

recognized the three conditions with an accuracy of 90:9%.

These preliminary and encouraging results suggest that ITL

analysis provides viable metrics for the quantitative evaluation

of human-horse interaction.
 
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number Equine Behaviour @ team @ Serial 6176  
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