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Dynamic Model of Athletes’ Emotions Based on Wearable Devices

  • Damien Dupré
  • Ben Bland
  • Andrew Bolster
  • Gawain Morrison
  • Gary McKeown
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 603)

Abstract

With the development of wearable sensors, it is now possible to assess the dynamic progression of physiological rhythms such as heart rate, breathing rate or galvanic skin response in ways and places that were previously impractical. This paper presents a new application that synchronizes the emotional patterns from these time-series in order to model athletes’ emotion during physical activity. This data analysis computes a best-fitting model for analyzing the patterns given by these measurements “in the wild”. The recording setup used to measure and synchronize multiple biometric physiological sensors can be called a BAN (Body Area Network) of personal measurements. By monitoring physical activity, it is now possible to calculate optimal patterns for managing athletes’ emotion. The data provided here are not restricted by a lab environment but close to the “ground truth” of ecologically valid physiological changes. The data allow the provision of accurate feedback to athletes about their emotion (e.g. in cases such as an unexpected increase or an expected decrease of physiological activity).

Keywords

Physiology Wearable sensors Multimodal measure Outdoor activities Time-series 

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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Damien Dupré
    • 1
  • Ben Bland
    • 2
  • Andrew Bolster
    • 2
  • Gawain Morrison
    • 2
  • Gary McKeown
    • 1
  1. 1.School of PsychologyQueen’s UniversityBelfastUK
  2. 2.SensumCo. Ltd.BelfastUK

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