Iuppariello, Luigi (2015) MODELLING AND PERFORMANCE ASSESSMENT OF HUMAN REACHING MOVEMENTS FOR DISEASE CLASSIFICATION. [Tesi di dottorato]

[img]
Preview
Text
Iuppariello.pdf

Download (2MB) | Preview
[error in script] [error in script]
Item Type: Tesi di dottorato
Lingua: English
Title: MODELLING AND PERFORMANCE ASSESSMENT OF HUMAN REACHING MOVEMENTS FOR DISEASE CLASSIFICATION
Creators:
CreatorsEmail
Iuppariello, Luigiluigi.iuppariello@unina.it
Date: 31 March 2015
Number of Pages: 116
Institution: Università degli Studi di Napoli Federico II
Department: Ingegneria Elettrica e delle Tecnologie dell'Informazione
Scuola di dottorato: Ingegneria dell'informazione
Dottorato: Ingegneria elettronica e delle telecomunicazioni
Ciclo di dottorato: 27
Coordinatore del Corso di dottorato:
nomeemail
Riccio, Danieledariccio@unina.it
Tutor:
nomeemail
Paura, LuigiUNSPECIFIED
Cesarelli, MarioUNSPECIFIED
Date: 31 March 2015
Number of Pages: 116
Uncontrolled Keywords: Submovements, reaching, gaussian, smoothness, peak-phase
Settori scientifico-disciplinari del MIUR: Area 09 - Ingegneria industriale e dell'informazione > ING-INF/06 - Bioingegneria elettronica e informatica
Aree tematiche (7° programma Quadro): SALUTE e TUTELA DEL CONSUMATORE > Biotecnologie, strumenti e tecnologie generiche per la salute umana
Date Deposited: 07 Apr 2015 11:06
Last Modified: 17 Apr 2016 01:00
URI: http://www.fedoa.unina.it/id/eprint/10336
DOI: 10.6092/UNINA/FEDOA/10336

Abstract

Human arm motor control has been object of great investigation for several decades, during which some issues have been identified as themes of high interest. There is a wide number of studies on human motor control supporting the theory that reaching and pointing movements are the result of sequences of discrete motion units, called sub-movements. Evidence for the existence of discrete sub-movements underlying continuous human movement has motivated many attempts to "extract" them. Moreover, to analyze the strategy of the reaching movements, gained a great appeal in the rehabilitation field. In fact, understanding movement deficits following central nervous system lesions and the relationships between these deficits and functional ability, is fundamental to the development of successful rehabilitation therapies. The goal of sub-movement extraction is to infer the sub-movement composition of a movement from kinematic data. In the tangential velocity domain, a sub-movement is represented as a uni-modal, bell-shaped function. Determining the number, relative timing, and amplitude of sub-movements that most closely reproduce the original tangential velocity data is a non-linear optimization problem difficult to solve. The experimental observations suggest that sub-movements are ubiquitous but proof of their existence and detailed quantification of their form have been elusive. Although several sub-movement extraction algorithms have been proposed previously, all of them are subject to finding local, rather than global, minima and to producing spurious decomposition results. The first section of this thesis, propose a review on the decomposition methods developed until now and the several methodologies used to extract them. Furthermore, an hybrid sub-movement decomposition method is proposed, based on a robust expectation maximization (EM) constrained algorithm and a scale-space approach capable to overcome the limitations of the EM algorithm, which is a local maximum seeker. This representation allowed to explore whether the movements are built up of elementary kinematic units by decomposing each surface into a weighted combination of Gaussian functions. Finally, is proposed a new kinematic and electromyographic assessment of robot assisted upper arm reaching in hemiparetic subjects applying successfully the sub-movement decomposition method implemented to carefully analyze their motor and muscle strategy.

Actions (login required)

View Item View Item