Nonlinear modeling of cardiovascular response to exercise

Wang, L; Su, SW; Chan, GSH; Celler, BG; Cheng, TM; Savkin, AV

Nonlinear modeling of cardiovascular response to exercise

Wang, L Su, SW

Chan, GSH Celler, BG Cheng, TM Savkin, AV

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Publication Type:: Conference Proceeding
Citation:: BIOSIGNALS 2008 - Proceedings of the 1st International Conference on Bio-inspired Systems and Signal Processing, 2008, 1 pp. 40 - 46
Issue Date:: 2008-12-01

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Field	Value	Language
dc.contributor.author	Wang, L	en_US
dc.contributor.author	Su, SW https://orcid.org/0000-0002-5720-8852	en_US
dc.contributor.author	Chan, GSH	en_US
dc.contributor.author	Celler, BG	en_US
dc.contributor.author	Cheng, TM	en_US
dc.contributor.author	Savkin, AV	en_US
dc.date.issued	2008-12-01	en_US
dc.identifier.citation	BIOSIGNALS 2008 - Proceedings of the 1st International Conference on Bio-inspired Systems and Signal Processing, 2008, 1 pp. 40 - 46	en_US
dc.identifier.isbn	9789898111180	en_US
dc.identifier.uri	http://hdl.handle.net/10453/11129
dc.description.abstract	This study experimentally investigates the relationships between central cardiovascular variables and oxygen uptake based on nonlinear analysis and modeling. Ten healthy subjects were studied using cycle-ergometry exercise tests with constant workloads ranging from 25 Watt to 125 Watt. Breath by breath gas exchange, heart rate, cardiac output, stroke volume and blood pressure were measured at each stage. The modeling results proved that the nonlinear modeling method (Support Vector Regression) outperforms traditional regression method (reducing Estimation Error between 59% and 80%, reducing Testing Error between 53% and 72%) and is the ideal approach in the modeling of physiological data, especially with small training data set.	en_US
dc.relation.ispartof	BIOSIGNALS 2008 - Proceedings of the 1st International Conference on Bio-inspired Systems and Signal Processing	en_US
dc.title	Nonlinear modeling of cardiovascular response to exercise	en_US
dc.type	Conference Proceeding
utslib.citation.volume	1	en_US
utslib.for	0914 Resources Engineering and Extractive Metallurgy	en_US
dc.location.activity	Madeira, Portugal	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Biomedical Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CHT - Health Technologies
utslib.copyright.status	open_access
pubs.publication-status	Published	en_US
pubs.volume	1	en_US

Abstract:

This study experimentally investigates the relationships between central cardiovascular variables and oxygen uptake based on nonlinear analysis and modeling. Ten healthy subjects were studied using cycle-ergometry exercise tests with constant workloads ranging from 25 Watt to 125 Watt. Breath by breath gas exchange, heart rate, cardiac output, stroke volume and blood pressure were measured at each stage. The modeling results proved that the nonlinear modeling method (Support Vector Regression) outperforms traditional regression method (reducing Estimation Error between 59% and 80%, reducing Testing Error between 53% and 72%) and is the ideal approach in the modeling of physiological data, especially with small training data set.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/11129