Document Detail


A new classification of diabetic gait pattern based on cluster analysis of biomechanical data.
MedLine Citation:
PMID:  20920432     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
BACKGROUND: The diabetic foot, one of the most serious complications of diabetes mellitus and a major risk factor for plantar ulceration, is determined mainly by peripheral neuropathy. Neuropathic patients exhibit decreased stability while standing as well as during dynamic conditions. A new methodology for diabetic gait pattern classification based on cluster analysis has been proposed that aims to identify groups of subjects with similar patterns of gait and verify if three-dimensional gait data are able to distinguish diabetic gait patterns from one of the control subjects.
METHOD: The gait of 20 nondiabetic individuals and 46 diabetes patients with and without peripheral neuropathy was analyzed [mean age 59.0 (2.9) and 61.1(4.4) years, mean body mass index (BMI) 24.0 (2.8), and 26.3 (2.0)]. K-means cluster analysis was applied to classify the subjects' gait patterns through the analysis of their ground reaction forces, joints and segments (trunk, hip, knee, ankle) angles, and moments.
RESULTS: Cluster analysis classification led to definition of four well-separated clusters: one aggregating just neuropathic subjects, one aggregating both neuropathics and non-neuropathics, one including only diabetes patients, and one including either controls or diabetic and neuropathic subjects.
CONCLUSIONS: Cluster analysis was useful in grouping subjects with similar gait patterns and provided evidence that there were subgroups that might otherwise not be observed if a group ensemble was presented for any specific variable. In particular, we observed the presence of neuropathic subjects with a gait similar to the controls and diabetes patients with a long disease duration with a gait as altered as the neuropathic one.
Authors:
Zimi Sawacha; Gabriella Guarneri; Angelo Avogaro; Claudio Cobelli
Publication Detail:
Type:  Journal Article     Date:  2010-09-01
Journal Detail:
Title:  Journal of diabetes science and technology     Volume:  4     ISSN:  1932-2968     ISO Abbreviation:  J Diabetes Sci Technol     Publication Date:  2010 Sep 
Date Detail:
Created Date:  2010-10-05     Completed Date:  2011-02-10     Revised Date:  2011-09-13    
Medline Journal Info:
Nlm Unique ID:  101306166     Medline TA:  J Diabetes Sci Technol     Country:  United States    
Other Details:
Languages:  eng     Pagination:  1127-38     Citation Subset:  IM    
Copyright Information:
© 2010 Diabetes Technology Society.
Affiliation:
Department of Information Engineering, University of Padova, Padova, Italy.
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MeSH Terms
Descriptor/Qualifier:
Aged
Ankle Joint / physiopathology
Biomechanics
Case-Control Studies
Cluster Analysis
Diabetic Neuropathies / complications*
Female
Gait Disorders, Neurologic / classification*,  etiology*,  physiopathology
Hip Joint / physiopathology
Humans
Knee Joint / physiopathology
Male
Middle Aged
Photogrammetry
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