Affiliation:
1. Computer Science and Systems Engineering Department, Engineering Research Institute of Aragon (I3A), University of Zaragoza, 50018 Zaragoza, Spain
2. Electronic Engineering and Communications Department, Engineering Research Institute of Aragon (I3A), University of Zaragoza, 50009 Zaragoza, Spain
Abstract
Wearable technology is playing an increasing role in the development of user-centric applications. In the field of sports, this technology is being used to implement solutions that improve athletes’ performance, reduce the risk of injury, or control fatigue, for example. Emotions are involved in most of these solutions, but unfortunately, they are not monitored in real-time or used as a decision element that helps to increase the quality of training sessions, nor are they used to guarantee the health of athletes. In this paper, we present a wearable and a set of machine learning models that are able to deduce runners’ emotions during their training. The solution is based on the analysis of runners’ electrodermal activity, a physiological parameter widely used in the field of emotion recognition. As part of the DJ-Running project, we have used these emotions to increase runners’ motivation through music. It has required integrating the wearable and the models into the DJ-Running mobile application, which interacts with the technological infrastructure of the project to select and play the most suitable songs at each instant of the training.
Funder
Spanish Ministerio de Economía y Competitividad
Aragonese Government
Subject
Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry