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Authors: Thomas Kaegi-Trachsel 1 ; Juerg Gutknecht 1 and Dennis Majoe 2

Affiliations: 1 ETH, Switzerland ; 2 MA Systems and Control Limited, United Kingdom

Keyword(s): Mental health, Depression, Activity sensing, Wearable Smart sensor.

Related Ontology Subjects/Areas/Topics: Biomedical Engineering ; Biomedical Signal Processing ; Cloud Computing ; Devices ; e-Health ; Health Information Systems ; Human-Computer Interaction ; Physiological Computing Systems ; Platforms and Applications ; Telemedicine ; Wearable Sensors and Systems

Abstract: The ambulatory activity of a person may be used as one component within an overall wearable sensor system that predicts the onset of mental health problems. Ergonomic smart sensors that can determine the total energy expenditure and type of ambulation may provide unique insights to the coping behaviour of stressed people. Rather than relying on wearable computers, a single smart miniature sensor that is worn 24/7 should perform the complex embedded recognition tasks while meeting difficult battery life, wireless communications and ergonomic constraints. The development and testing of such a smart sensor is described which takes into account action timeline variations, as well as action variations both intra individual and inter individual.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Kaegi-Trachsel, T.; Gutknecht, J. and Majoe, D. (2011). MENTAL HEALTH DECLINE PREDICTION - A Smart Sensor for Day to Day Activity Recognition. In Proceedings of the International Conference on Health Informatics (BIOSTEC 2011) - HEALTHINF; ISBN 978-989-8425-34-8; ISSN 2184-4305, SciTePress, pages 219-227. DOI: 10.5220/0003150002190227

@conference{healthinf11,
author={Thomas Kaegi{-}Trachsel. and Juerg Gutknecht. and Dennis Majoe.},
title={MENTAL HEALTH DECLINE PREDICTION - A Smart Sensor for Day to Day Activity Recognition},
booktitle={Proceedings of the International Conference on Health Informatics (BIOSTEC 2011) - HEALTHINF},
year={2011},
pages={219-227},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003150002190227},
isbn={978-989-8425-34-8},
issn={2184-4305},
}

TY - CONF

JO - Proceedings of the International Conference on Health Informatics (BIOSTEC 2011) - HEALTHINF
TI - MENTAL HEALTH DECLINE PREDICTION - A Smart Sensor for Day to Day Activity Recognition
SN - 978-989-8425-34-8
IS - 2184-4305
AU - Kaegi-Trachsel, T.
AU - Gutknecht, J.
AU - Majoe, D.
PY - 2011
SP - 219
EP - 227
DO - 10.5220/0003150002190227
PB - SciTePress