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Measuring Human-Animal Interaction with Smartwatches: An Initial Experiment

In: Collaborative Innovation Networks

Author

Listed:
  • Katharina Stolz

    (Otto-Friedrich-University of Bamberg)

  • Teresa Heyder

    (Otto-Friedrich-University of Bamberg)

  • Peter A. Gloor

    (MIT Center for Collective Intelligence)

  • Oliver Posegga

    (Otto-Friedrich-University of Bamberg)

Abstract

The paper describes and evaluates an explorative approach to quantify the relationship between trainable animals and their owners. Data on human-animal interaction has been collected by using Pebble smartwatches and by observing different kinds of animal training sessions. Tracking movement of horses and dogs with the Pebble Watch was successful with horses but not with dogs. Besides the breed and behavior of the animal, weather conditions and the way of attaching the Pebble influenced the measurement quality. In summary, the experiment indicates that there might be a connection between the heart rate (BPM), the average movement (VMC), and the mood data (pleasance and activation) of an animal and its owner during training sessions.

Suggested Citation

  • Katharina Stolz & Teresa Heyder & Peter A. Gloor & Oliver Posegga, 2019. "Measuring Human-Animal Interaction with Smartwatches: An Initial Experiment," Studies on Entrepreneurship, Structural Change and Industrial Dynamics, in: Yang Song & Francesca Grippa & Peter A. Gloor & João Leitão (ed.), Collaborative Innovation Networks, pages 165-182, Springer.
    • Handle: RePEc:spr:seschp:978-3-030-17238-1_10
    DOI: 10.1007/978-3-030-17238-1_10
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    Cited by:

    1. Luis A. Corujo & Emily Kieson & Timo Schloesser & Peter A. Gloor, 2021. "Emotion Recognition in Horses with Convolutional Neural Networks," Future Internet, MDPI, vol. 13(10), pages 1-13, September.

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