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The role of nonlinear coupling in Human-Horse Interaction: A preliminary study.
Abstract: This study focuses on the analysis of human-horse 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.
Publication Date: 2017-10-25 PubMed ID: 29060119DOI: 10.1109/EMBC.2017.8037075Google Scholar: Lookup The Equine Research Bank provides access to a large database of publicly available scientific literature. Inclusion in the Research Bank does not imply endorsement of study methods or findings by Mad Barn.
- Journal Article
Summary
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The research discusses the application of Information Theoretic Learning (ITL) in understanding the dynamics of human-horse interaction using cardiovascular data.
Research Overview
This study is geared towards understanding the dynamics involved in human-horse interaction through the analysis of cardiovascular information. Specific attention is given to the nonlinear interaction between the heartbeats of the human and the horse. As part of the research methodology, the study utilized the Information Theoretic Learning (ITL) approach.
Methodology
- The research involved three experimental conditions designed to analyze the interaction between humans and horses. These conditions were: absence of interaction, visual-olfactory interaction, and brooming.
- Data on heartbeat dynamics from both humans and horses were collected for each of the three conditions.
- The study also used different quantifying metrics, including Cross Information Potential, Cross Correntropy, and Correntropy Coefficient, to estimate the nonlinear coupling in a group of eleven subjects and one horse.
Results
- The results showed a statistically significant difference across all three interaction phases. This difference indicates the varied impacts of the experimental conditions on the interaction between humans and horses.
- Moreover, a Support Vector Machine classifier successfully recognized and classified the three experimental conditions with an accuracy of 90.9%, indicating the reliability of these conditions in defining interaction dynamics.
Conclusion
- The study concluded with promising results suggesting that the Information Theoretic Learning (ITL) analysis offers vital metrics for the quantitative evaluation of human-horse interaction.
The research is a preliminary study that opens up further studies in understanding human-animal interaction, specifically with horses, through the use of cardiovascular data. The research outcome may help enhance training methods, improve interaction, and potentially facilitate better cohabitation with horses.
Cite This Article
APA
Lanata A, Guidi A, Valenza G, Baragli P, Scilingo EP.
(2017).
The role of nonlinear coupling in Human-Horse Interaction: A preliminary study.
Annu Int Conf IEEE Eng Med Biol Soc, 2017, 1320-1323.
https://doi.org/10.1109/EMBC.2017.8037075 Publication
Researcher Affiliations
MeSH Terms
- Animals
- Heart Rate
- Horses
- Humans
- Nonlinear Dynamics
Citations
This article has been cited 4 times.- Chang T, Akin S, Kim MK, Murray L, Kim B, Cho S, Huh S, Teke S, Couetil L, Jun MB, Lee CH. A Programmable Dual-Regime Spray for Large-Scale and Custom-Designed Electronic Textiles. Adv Mater 2022 Mar;34(9):e2108021.
- Scopa C, Contalbrigo L, Greco A, Lanatà A, Scilingo EP, Baragli P. Emotional Transfer in Human-Horse Interaction: New Perspectives on Equine Assisted Interventions. Animals (Basel) 2019 Nov 26;9(12).
- Semin GR, Scandurra A, Baragli P, Lanatà A, D'Aniello B. Inter- and Intra-Species Communication of Emotion: Chemosignals as the Neglected Medium. Animals (Basel) 2019 Oct 31;9(11).
- Hediger K, Meisser A, Zinsstag J. A One Health Research Framework for Animal-Assisted Interventions. Int J Environ Res Public Health 2019 Feb 21;16(4).
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