Please use this identifier to cite or link to this item:
Title: An experimentally confirmed statistical model on arm movement
Authors: Chan, MF
Giddings, DR
Chandler, CS
Craggs, C
Plant, RD
Day, MC
Keywords: Arm movement
Non-linear regression
Parkinson's disease
Statistical modelling
Issue Date: 2004
Publisher: North-Holland
Source: Human movement science, 2004, v. 22, no. 6, p. 631-648 How to cite?
Journal: Human movement science 
Abstract: The purpose of this research work was to develop a methodology to model arm movement in normal subjects and neurologically impaired individuals through the application of a statistical modelling method. Thirteen subjects with Parkinson's disease and 29 normal controls were recruited to participate in an arm motor task. An infrared optoelectronic kinematic movement analysis system was employed to record arm movement at 50 times per second. This study identified the modified extended Freundlich model as one that could be used to describe this task. Results showed that this model fit the data well and that it has a good correspondence between the observed and the predicted data. However, verification of the model showed that the residuals contained a sizeable autocorrelation factor. The Cochrane and Orcutt method was applied to remove this factor, which improved the fit of the model. Results showed that Parkinson's disease subjects had a higher autocorrelation coefficient than the normal subjects for this task. A positive correlation (rs=0.72, p<0.01) was found between the Langton-Hewer stage and the autocorrelation coefficient of PD subjects. This finding suggests that if autocorrelation is positively correlated with disease progression, clinicians in their clinical practice might use the autocorrelation value as a useful indicator to quantify the progression of a subjects' disease. Significant differences in model parameters were seen between normal and Parkinson's disease subjects. The use of such a model to represent and quantify movement patterns provides an important base for future study.
ISSN: 0167-9457
DOI: 10.1016/j.humov.2004.02.002
Appears in Collections:Journal/Magazine Article

View full-text via PolyU eLinks SFX Query
Show full item record


Last Week
Last month
Citations as of Nov 3, 2017


Last Week
Last month
Citations as of Sep 28, 2017

Page view(s)

Last Week
Last month
Checked on Nov 13, 2017

Google ScholarTM



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.