Gonzalez Sanchez, Victor (2016) Development of a dexterity assessment method. PhD thesis, University of Sheffield.
Abstract
This research was aimed at contributing to the understanding of dexterity through a scientific analysis of some of its more important features, as well as the development of viable methods to quantify these characteristics. The methods and procedures developed during this research were applied to evaluate traditional dexterity assessment methods, comparing dexterity features among tests and hand daily living tasks in order to characterise their reliability and robustness. The study makes use of visual, mathematical, and experimental methods to obtain, process, and analyse a series of hand function parameters that account for some of the main features that affect dexterity in modern daily living.
Furthermore, the designed methods and analysis techniques provide fundamental insights into our understanding of the relationships between motor coordination, movement, and hand function. More importantly, the data and conclusions derived from this research have the potential to aid in the development of improved health care practice, assistive technologies, and quality of life research, by providing practitioners and researchers with updated knowledge on human movement analysis, hand function, and dexterity.
The overall conclusion of this research is that the broad range of movements and patterns of the human hand, along with the infinite number of possible coordination strategies result in the need for the identification of movement patterns in order to accurately assess dexterity and hand function. Furthermore, although timed tests are time-efficient and cost-effective methods to measure dexterity, a truly objective and robust measurement of dexterity most cover all the factors and parameters that play a role in this phenomenon.
Metadata
Supervisors: | Rowson, Jennifer |
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Awarding institution: | University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) The University of Sheffield > Faculty of Engineering (Sheffield) > Mechanical Engineering (Sheffield) |
Identification Number/EthosID: | uk.bl.ethos.698302 |
Depositing User: | Mr Victor Gonzalez Sanchez |
Date Deposited: | 25 Nov 2016 13:50 |
Last Modified: | 12 Oct 2018 09:31 |
Open Archives Initiative ID (OAI ID): | oai:etheses.whiterose.ac.uk:15609 |
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PhD Thesis
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