MENTAL HEALTH DECLINE PREDICTION - A Smart Sensor for Day to Day Activity Recognition
Thomas Kaegi-Trachsel, Juerg Gutknecht, Dennis Majoe
2011
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.
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Paper Citation
in Harvard Style
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 - Volume 1: HEALTHINF, (BIOSTEC 2011) ISBN 978-989-8425-34-8, pages 219-227. DOI: 10.5220/0003150002190227
in Bibtex Style
@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 - Volume 1: HEALTHINF, (BIOSTEC 2011)},
year={2011},
pages={219-227},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003150002190227},
isbn={978-989-8425-34-8},
}
in EndNote Style
TY - CONF
JO - Proceedings of the International Conference on Health Informatics - Volume 1: HEALTHINF, (BIOSTEC 2011)
TI - MENTAL HEALTH DECLINE PREDICTION - A Smart Sensor for Day to Day Activity Recognition
SN - 978-989-8425-34-8
AU - Kaegi-Trachsel T.
AU - Gutknecht J.
AU - Majoe D.
PY - 2011
SP - 219
EP - 227
DO - 10.5220/0003150002190227