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Authors: Samuel Hugueny ; David A. Clifton and Lionel Tarassenko

Affiliation: University of Oxford, United Kingdom

ISBN: 978-989-674-018-4

Keyword(s): Patient monitoring, Telemetry, Novelty detection, Multivariate extreme value theory.

Related Ontology Subjects/Areas/Topics: Applications and Services ; Artificial Intelligence ; Biomedical Engineering ; Biomedical Signal Processing ; Computer Vision, Visualization and Computer Graphics ; Data Manipulation ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Medical Image Detection, Acquisition, Analysis and Processing ; Methodologies and Methods ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Real-Time Systems ; Sensor Networks ; Soft Computing

Abstract: Conventional patient monitoring is performed by generating alarms when vital signs exceed pre-determined thresholds, but the false-alarm rate of such monitors in hospitals is so high that alarms are typically ignored. We propose a principled, probabilistic method for combining vital signs into a multivariate model of patient state, using extreme value theory (EVT) to generate robust alarms if a patient's vital signs are deemed to have become sufficiently ``extreme''. Our proposed formulation operates many orders of magnitude faster than existing methods, allowing on-line learning of models, leading ultimately to patient-specific monitoring.

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Paper citation in several formats:
Hugueny S., A. Clifton D. and Tarassenko L. (2010). PROBABILISTIC PATIENT MONITORING USING EXTREME VALUE THEORY - A Multivariate, Multimodal Methodology for Detecting Patient Deterioration.In Proceedings of the Third International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2010) ISBN 978-989-674-018-4, pages 5-12. DOI: 10.5220/0002690200050012

@conference{biosignals10,
author={Samuel Hugueny and David A. Clifton and Lionel Tarassenko},
title={PROBABILISTIC PATIENT MONITORING USING EXTREME VALUE THEORY - A Multivariate, Multimodal Methodology for Detecting Patient Deterioration},
booktitle={Proceedings of the Third International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2010)},
year={2010},
pages={5-12},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002690200050012},
isbn={978-989-674-018-4},
}

TY - CONF

JO - Proceedings of the Third International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2010)
TI - PROBABILISTIC PATIENT MONITORING USING EXTREME VALUE THEORY - A Multivariate, Multimodal Methodology for Detecting Patient Deterioration
SN - 978-989-674-018-4
AU - Hugueny S.
AU - A. Clifton D.
AU - Tarassenko L.
PY - 2010
SP - 5
EP - 12
DO - 10.5220/0002690200050012

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