Modelling, Regulating and Controlling Cardiovascular Responses by using Wearable Sensors

Alqudah, Hamzah Mohammad Salem

Modelling, Regulating and Controlling Cardiovascular Responses by using Wearable Sensors

Alqudah, Hamzah Mohammad Salem

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Publication Type:: Thesis
Issue Date:: 2019

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Field	Value	Language
dc.contributor.author	Alqudah, Hamzah Mohammad Salem
dc.date.accessioned	2020-04-21T22:58:46Z
dc.date.available	2020-04-21T22:58:46Z
dc.date.issued	2019
dc.identifier.uri	http://hdl.handle.net/10453/140158
dc.description	University of Technology Sydney. Faculty of Engineering and Information Technology.	en_AU
dc.description.abstract	Physical exercise has significant benefits for humans in improving the health and quality of their lives, by strengthening the functions of their cardiovascular and respiratory systems. However, it is very important to control the intensity of the exercise within the capability of the individual to maximize the efficiency of the exercise and ensure the safety of the exercises. The maximal rate of oxygen uptake (VO₂ₘₐₓ) and Heart Rate (HR) are the important determinants of cardiovascular fitness and health status; their measurements can help in cardiac diseases detection. In this thesis, we first developed two reliable and valid wearable exercise monitoring systems by using TI e Z430-Chronos watch as well as iPhone App, which can control the exercise intensity through audio stimulations and audio command to improve cardiovascular fitness of various exercisers. Various exercises including treadmill exercise and stair climbing were performed under the monitoring and controlling of the developed wearable devices together with the portable gas analyzer, K4b². Based on experimental data, we applied the non-parametric model to investigate the dynamics of Heart Rate (HR) response to stairs exercise status. The self-designed application provides a reliable technique to record HR data and to present safe and understandable exercise instructions. The protocol of the experiment guarantees a continuously monitoring of HR. The identification result of different period numbers are compared, and the models, which includes three types of parametric models and one nonparametric model, are also presented. In conclusion, the developed portable monitoring systems, exercise protocols, and HR models have great potential to accurately predict and regulate the dynamic cardiorespiratory response to moderate strength exercise, promote safer exercise and guide the cardiac patient’s during the outpatient cardiac rehabilitation phase.	en_AU
dc.format	Thesis (PhD)
dc.language.iso	en_AU	en_AU
dc.relation	https://opus.lib.uts.edu.au/bitstream/10453/140158/2/02whole.pdf
dc.rights	The author owns the copyright in this thesis including all reproduction and reuse rights for the work. The work may not be altered without the permission of the copyright owner. Attribution is essential when quoting or paraphrasing from this thesis.
dc.rights	au.edu.uts.lib/ppc
dc.rights	info:eu-repo/semantics/openAccess
dc.title	Modelling, Regulating and Controlling Cardiovascular Responses by using Wearable Sensors	en_AU
dc.type	Thesis	en_AU
utslib.copyright.status	open_access

Abstract:

Physical exercise has significant benefits for humans in improving the health and quality of their lives, by strengthening the functions of their cardiovascular and respiratory systems. However, it is very important to control the intensity of the exercise within the capability of the individual to maximize the efficiency of the exercise and ensure the safety of the exercises. The maximal rate of oxygen uptake (VO₂ₘₐₓ) and Heart Rate (HR) are the important determinants of cardiovascular fitness and health status; their measurements can help in cardiac diseases detection. In this thesis, we first developed two reliable and valid wearable exercise monitoring systems by using TI e Z430-Chronos watch as well as iPhone App, which can control the exercise intensity through audio stimulations and audio command to improve cardiovascular fitness of various exercisers. Various exercises including treadmill exercise and stair climbing were performed under the monitoring and controlling of the developed wearable devices together with the portable gas analyzer, K4b². Based on experimental data, we applied the non-parametric model to investigate the dynamics of Heart Rate (HR) response to stairs exercise status. The self-designed application provides a reliable technique to record HR data and to present safe and understandable exercise instructions. The protocol of the experiment guarantees a continuously monitoring of HR. The identification result of different period numbers are compared, and the models, which includes three types of parametric models and one nonparametric model, are also presented. In conclusion, the developed portable monitoring systems, exercise protocols, and HR models have great potential to accurately predict and regulate the dynamic cardiorespiratory response to moderate strength exercise, promote safer exercise and guide the cardiac patient’s during the outpatient cardiac rehabilitation phase.

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http://hdl.handle.net/10453/140158