Document Detail


Multidimensional signal exploration using multiple correspondence analysis. An example of a load lifting study.
MedLine Citation:
PMID:  14518795     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Most empirical studies concerning rehabilitation yield numerous multidimensional signals (dozens of time variables are obtained for dozens of empirical situations). The purpose of this paper is to suggest a statistical analysis procedure based on: 1) space-time fuzzy windowing; 2) signal behavior characterization within the windows using membership value averages (MVA); and 3) MVA analysis using the multiple correspondence analysis (MCA). A load lifting study provided an example of 78 multidimensional signals including 89 time variables (forces, energy indicators, linear and angular positions, speeds, and accelerations). The main goal of MCA was to compare and contrast biomechanical signals from two lifting modes: "free" and "isokinetic." In the first mode, three loads were tested--light, medium, and heavy. In the second, three speeds were tested--slow, medium, and fast. Thirteen male individuals without disabilities participated in this study. The MCA showed that most of the free load-lifting strategies cannot be used in isokinetic lifting because the constraints of the subject and the environment are different. In addition, as the level of difficulty increases, free lifting became more economical while isokinetic lifting became less economical. These results would appear to indicate that movement strategies used for free lifting cannot be learned using an isokinetic machine during rehabilitation sessions for chronic low back pain. MCA was also suggested as a tool for comparing patients with control individuals. To achieve this aim, the notion of "supplementary data" was introduced.
Authors:
Pierre Loslever; Stéphane Bouilland
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Publication Detail:
Type:  Clinical Trial; Comparative Study; Controlled Clinical Trial; Evaluation Studies; Journal Article; Research Support, Non-U.S. Gov't    
Journal Detail:
Title:  IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society     Volume:  11     ISSN:  1534-4320     ISO Abbreviation:  IEEE Trans Neural Syst Rehabil Eng     Publication Date:  2003 Sep 
Date Detail:
Created Date:  2003-10-01     Completed Date:  2003-10-30     Revised Date:  2007-11-15    
Medline Journal Info:
Nlm Unique ID:  101097023     Medline TA:  IEEE Trans Neural Syst Rehabil Eng     Country:  United States    
Other Details:
Languages:  eng     Pagination:  301-10     Citation Subset:  IM    
Affiliation:
Laboratoire d'Automatique et de MOcanique Industrielle et Humaines, University of Valenciennes, 59313 Valenciennes Cedex 9, France. Pierre.Loslever@univ-valenciennes.fr
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MeSH Terms
Descriptor/Qualifier:
Adult
Algorithms*
Humans
Low Back Pain / diagnosis,  physiopathology,  rehabilitation
Male
Models, Biological*
Models, Statistical*
Movement / physiology*
Reproducibility of Results
Sensitivity and Specificity
Signal Processing, Computer-Assisted
Statistics as Topic
Torque
Weight-Bearing / physiology*

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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