Title: Clinical decision support in physiological monitoring

Authors: J. Mark Ansermino, Stephan K.W. Schwarz, Guy A. Dumont, Chris Brouse, Yang Ping, Joanne Lim, Dustin Dunsmuir, Jeremy Daniels

Addresses: Faculty of Medicine, Department of Anesthesiology, Pharmacology & Therapeutics, The University of British Columbia, 2176 Health Sciences Mall, Vancouver, British Columbia, V6T 1Z3, Canada. ' Faculty of Medicine, Department of Anesthesiology, Pharmacology & Therapeutics, The University of British Columbia, 2176 Health Sciences Mall, Vancouver, British Columbia, V6T 1Z3, Canada. ' Department of Electrical and Computer Engineering, The University of British Columbia, 2332 Main Mall, Vancouver, British Columbia, V6T 1Z4, Canada. ' Department of Electrical and Computer Engineering, The University of British Columbia, 2332 Main Mall, Vancouver, British Columbia, V6T 1Z4, Canada. ' Department of Electrical and Computer Engineering, The University of British Columbia, 2332 Main Mall, Vancouver, British Columbia, V6T 1Z4, Canada. ' Department of Anesthesia, British Columbia Children's Hospital, 1L7 – 4480 Oak Street, Vancouver, British Columbia, V6H 3V4, Canada. ' Department of Anesthesia, British Columbia Children's Hospital, 1L7 – 4480 Oak Street, Vancouver, British Columbia, V6H 3V4, Canada. ' Department of Anesthesia, British Columbia Children's Hospital, 1L7 – 4480 Oak Street, Vancouver, British Columbia, V6H 3V4, Canada

Abstract: Effective use of the information produced by current and future physiological sensors can be used to improve monitoring, diagnosis, and treatment of patients. The successful introduction of intelligent monitoring and automated control promises to harness this information to enhance safety, as it has in aviation. Intelligent data analysis requires a multifaceted approach. A range of techniques that include statistical characterisation, modelling, feature extraction, and prediction augmented with expert knowledge can be used to present the salient information and combine information from multiple sources. We present a collaborative effort to embrace intelligent monitoring and automated control for physiological monitoring.

Keywords: clinical decision support; decision support systems; DSS; expert systems; physiological monitoring; automation; automated control; anaesthesia; knowledge authoring; adaptive feature extraction; patient safety; intelligent data analysis; controlled drug delivery; modelling.

DOI: 10.1504/IJBET.2010.032696

International Journal of Biomedical Engineering and Technology, 2010 Vol.3 No.3/4, pp.264 - 286

Published online: 13 Apr 2010 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article