A Study on Model estimation for health monitoring and rehabilitation systems

Wang, Li

A Study on Model estimation for health monitoring and rehabilitation systems

Wang, Li

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Publication Type:: Thesis
Issue Date:: 2022

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Field	Value	Language
dc.contributor.author	Wang, Li
dc.date.accessioned	2022-11-28T00:25:04Z
dc.date.available	2022-11-28T00:25:04Z
dc.date.issued	2022
dc.identifier.uri	http://hdl.handle.net/10453/163765
dc.description	University of Technology Sydney. Faculty of Engineering and Information Technology.	en_US.UTF-8
dc.description.abstract	Electronic trainers (e-trainers) are fitness guidance systems consisting of motion signal sensor(s), a user interface, and a control system. Owing to the widespread popularity of fitness and personal training, e-trainers have found numerous applications across many fields. However, the design of e-trainers is challenging because of their requirement for miniaturisation and problems with discrepancies, drift, lack of data, and limited resources. The primary aim of this thesis is to design an improved e-trainer with a focus on the initial measurement unit calibration algorithm and the practical implementation of pattern recognition algorithms. Several problems in the field are considered, including kernel-based heart rate regulation, practical considerations for the calibration of efficient wearable devices, and model compression using the pruning method.	en_US.UTF-8
dc.format	Thesis (PhD)
dc.language.iso	en_US	en_US.UTF-8
dc.relation	https://opus.lib.uts.edu.au/bitstream/10453/163765/2/02whole.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	A Study on Model estimation for health monitoring and rehabilitation systems	en_US.UTF-8
dc.type	Thesis
utslib.copyright.status	open_access	*

Abstract:

Electronic trainers (e-trainers) are fitness guidance systems consisting of motion signal sensor(s), a user interface, and a control system. Owing to the widespread popularity of fitness and personal training, e-trainers have found numerous applications across many fields. However, the design of e-trainers is challenging because of their requirement for miniaturisation and problems with discrepancies, drift, lack of data, and limited resources. The primary aim of this thesis is to design an improved e-trainer with a focus on the initial measurement unit calibration algorithm and the practical implementation of pattern recognition algorithms. Several problems in the field are considered, including kernel-based heart rate regulation, practical considerations for the calibration of efficient wearable devices, and model compression using the pruning method.

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http://hdl.handle.net/10453/163765