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Emotion Detection in Ageing Adults from Physiological Sensors

  • Arturo Martínez-Rodrigo
  • Roberto Zangróniz
  • José Manuel Pastor
  • José Miguel Latorre
  • Antonio Fernández-Caballero
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 376)

Abstract

The increasing life expectancy is causing a fast ageing population around the globe, which is raising the demand on assistive systems based on ambient intelligence. While numerous papers have focused on the physical aspects in elderly, only a few works have attempted to regulate their emotional state. In this work, a new approach for monitoring and detecting the emotional state in elderly is presented. First, different physiological signals are acquired by means of wearable sensors, and data are transmitted to the embedded system. Next, noise and artifacts are removed by applying different signal processing techniques, depending on the signal behavior. Finally, several temporal and statistical markers are extracted and used to feed the classification model. In this very first version, a logistic regression model is used to detect two possible emotional states. In order to calibrate the model and adjust the boundary decision, twenty volunteers have agreed to be monitored and recorded to train the model. Finally, a decision maker regulates the environment, acting directly upon the elderly’s emotional state.

Keywords

Emotion detection Ageing adults Physiological sensors 

Notes

Acknowledgments

This work was partially supported by Spanish Ministerio de Economía y Competitividad / FEDER under TIN2013-47074-C2-1-R grant.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Arturo Martínez-Rodrigo
    • 1
  • Roberto Zangróniz
    • 1
  • José Manuel Pastor
    • 1
  • José Miguel Latorre
    • 2
  • Antonio Fernández-Caballero
    • 3
  1. 1.Universidad de Castilla-La ManchaInstituto de Tecnologías AudiovisualesCuencaSpain
  2. 2.Universidad de Castilla-La ManchaInstituto de Investigacin En Discapacidades NeurolgicasAlbaceteSpain
  3. 3.Universidad de Castilla-La ManchaInstituto de Investigacin En Informitica de AlbaceteAlbaceteSpain

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