Comparative Clustering of Plantar Pressure Distributions in Diabetics with Polyneuropathy May Be Applied to Reveal Inappropriate Biomechanical Stress
In diabetic patients, excessive peak plantar pressure has been identified as major risk factor for ulceration. Analyzing plantar pressure distributions potentially improves the identification of patients with a high risk for foot ulceration development. The goal of this study was to classify regiona...
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creator | Niemann, Uli Spiliopoulou, Myra Szczepanski, Thorsten Samland, Fred Grützner, Jens Senk, Dominik Ming, Antao Kellersmann, Juliane Malanowski, Jan Klose, Silke Mertens, Peter R |
description | In diabetic patients, excessive peak plantar pressure has been identified as major risk factor for ulceration. Analyzing plantar pressure distributions potentially improves the identification of patients with a high risk for foot ulceration development. The goal of this study was to classify regional plantar pressure distributions. By means of a sensor-equipped insole, pressure recordings of healthy controls (n = 18) and diabetics with severe polyneuropathy (n = 25) were captured across eight foot regions. The study involved a controlled experimental protocol with multiple sessions, where a session contained several cycles of pressure exposure. Clustering was used to identify subgroups of study participants that are characterized by similar pressure distributions. For both analyzed groups, the number of clusters to best describe the pressure profiles was four. When both groups were combined, analysis again led to four distinct clusters. While three clusters did not separate between healthy and diabetic volunteers the fourth cluster was only represented by diabetics. Here the pressure distribution pattern is characterized by a focal point of pressure application on the forefoot and low pressure on the lateral region. Our data suggest that pressure clustering is a feasible means to identify inappropriate biomechanical plantar stress. |
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Analyzing plantar pressure distributions potentially improves the identification of patients with a high risk for foot ulceration development. The goal of this study was to classify regional plantar pressure distributions. By means of a sensor-equipped insole, pressure recordings of healthy controls (n = 18) and diabetics with severe polyneuropathy (n = 25) were captured across eight foot regions. The study involved a controlled experimental protocol with multiple sessions, where a session contained several cycles of pressure exposure. Clustering was used to identify subgroups of study participants that are characterized by similar pressure distributions. For both analyzed groups, the number of clusters to best describe the pressure profiles was four. When both groups were combined, analysis again led to four distinct clusters. While three clusters did not separate between healthy and diabetic volunteers the fourth cluster was only represented by diabetics. Here the pressure distribution pattern is characterized by a focal point of pressure application on the forefoot and low pressure on the lateral region. Our data suggest that pressure clustering is a feasible means to identify inappropriate biomechanical plantar stress.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0161326</identifier><identifier>PMID: 27529421</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Amputation ; Analysis ; Biology and Life Sciences ; Biomechanical Phenomena ; Biomechanics ; Care and treatment ; Case-Control Studies ; Classification ; Cluster Analysis ; Clustering ; Complications and side effects ; Computer science ; Data processing ; Diabetes ; Diabetes mellitus ; Diabetic foot ; Diabetic Neuropathies - physiopathology ; Endocrinology ; Experiments ; Feet ; Female ; Foot - physiopathology ; Foot diseases ; Heart failure ; Humans ; Hypertension ; Leg ulcers ; Low pressure ; Male ; Medical research ; Medicine and Health Sciences ; Middle Aged ; Nephrology ; Patients ; Physical Sciences ; Plantar pressure ; Polyneuropathies ; Polyneuropathy ; Pressure ; Pressure distribution ; Pressure profiles ; Quality of life ; Regional development ; Research and Analysis Methods ; Risk analysis ; Risk factors ; Sensors ; Stress concentration ; Stress, Mechanical ; Studies ; Subgroups ; Surgery</subject><ispartof>PloS one, 2016-08, Vol.11 (8), p.e0161326-e0161326</ispartof><rights>COPYRIGHT 2016 Public Library of Science</rights><rights>2016 Niemann et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. 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Analyzing plantar pressure distributions potentially improves the identification of patients with a high risk for foot ulceration development. The goal of this study was to classify regional plantar pressure distributions. By means of a sensor-equipped insole, pressure recordings of healthy controls (n = 18) and diabetics with severe polyneuropathy (n = 25) were captured across eight foot regions. The study involved a controlled experimental protocol with multiple sessions, where a session contained several cycles of pressure exposure. Clustering was used to identify subgroups of study participants that are characterized by similar pressure distributions. For both analyzed groups, the number of clusters to best describe the pressure profiles was four. When both groups were combined, analysis again led to four distinct clusters. While three clusters did not separate between healthy and diabetic volunteers the fourth cluster was only represented by diabetics. Here the pressure distribution pattern is characterized by a focal point of pressure application on the forefoot and low pressure on the lateral region. Our data suggest that pressure clustering is a feasible means to identify inappropriate biomechanical plantar stress.</description><subject>Amputation</subject><subject>Analysis</subject><subject>Biology and Life Sciences</subject><subject>Biomechanical Phenomena</subject><subject>Biomechanics</subject><subject>Care and treatment</subject><subject>Case-Control Studies</subject><subject>Classification</subject><subject>Cluster Analysis</subject><subject>Clustering</subject><subject>Complications and side effects</subject><subject>Computer science</subject><subject>Data processing</subject><subject>Diabetes</subject><subject>Diabetes mellitus</subject><subject>Diabetic foot</subject><subject>Diabetic Neuropathies - physiopathology</subject><subject>Endocrinology</subject><subject>Experiments</subject><subject>Feet</subject><subject>Female</subject><subject>Foot - physiopathology</subject><subject>Foot diseases</subject><subject>Heart 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Clustering of Plantar Pressure Distributions in Diabetics with Polyneuropathy May Be Applied to Reveal Inappropriate Biomechanical Stress</title><author>Niemann, Uli ; Spiliopoulou, Myra ; Szczepanski, Thorsten ; Samland, Fred ; Grützner, Jens ; Senk, Dominik ; Ming, Antao ; Kellersmann, Juliane ; Malanowski, Jan ; Klose, Silke ; Mertens, Peter R</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c725t-56f960f48cb048807d65b19432155c1d0de46721ff359ea28779ec905ec74db83</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Amputation</topic><topic>Analysis</topic><topic>Biology and Life Sciences</topic><topic>Biomechanical Phenomena</topic><topic>Biomechanics</topic><topic>Care and treatment</topic><topic>Case-Control Studies</topic><topic>Classification</topic><topic>Cluster Analysis</topic><topic>Clustering</topic><topic>Complications and side effects</topic><topic>Computer 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Clustering of Plantar Pressure Distributions in Diabetics with Polyneuropathy May Be Applied to Reveal Inappropriate Biomechanical Stress</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2016-08-16</date><risdate>2016</risdate><volume>11</volume><issue>8</issue><spage>e0161326</spage><epage>e0161326</epage><pages>e0161326-e0161326</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>In diabetic patients, excessive peak plantar pressure has been identified as major risk factor for ulceration. Analyzing plantar pressure distributions potentially improves the identification of patients with a high risk for foot ulceration development. The goal of this study was to classify regional plantar pressure distributions. By means of a sensor-equipped insole, pressure recordings of healthy controls (n = 18) and diabetics with severe polyneuropathy (n = 25) were captured across eight foot regions. The study involved a controlled experimental protocol with multiple sessions, where a session contained several cycles of pressure exposure. Clustering was used to identify subgroups of study participants that are characterized by similar pressure distributions. For both analyzed groups, the number of clusters to best describe the pressure profiles was four. When both groups were combined, analysis again led to four distinct clusters. While three clusters did not separate between healthy and diabetic volunteers the fourth cluster was only represented by diabetics. Here the pressure distribution pattern is characterized by a focal point of pressure application on the forefoot and low pressure on the lateral region. Our data suggest that pressure clustering is a feasible means to identify inappropriate biomechanical plantar stress.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>27529421</pmid><doi>10.1371/journal.pone.0161326</doi><tpages>e0161326</tpages><oa>free_for_read</oa></addata></record> |
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source | MEDLINE; DOAJ Directory of Open Access Journals; Public Library of Science (PLoS) Journals Open Access; EZB-FREE-00999 freely available EZB journals; PubMed Central; Free Full-Text Journals in Chemistry |
subjects | Amputation Analysis Biology and Life Sciences Biomechanical Phenomena Biomechanics Care and treatment Case-Control Studies Classification Cluster Analysis Clustering Complications and side effects Computer science Data processing Diabetes Diabetes mellitus Diabetic foot Diabetic Neuropathies - physiopathology Endocrinology Experiments Feet Female Foot - physiopathology Foot diseases Heart failure Humans Hypertension Leg ulcers Low pressure Male Medical research Medicine and Health Sciences Middle Aged Nephrology Patients Physical Sciences Plantar pressure Polyneuropathies Polyneuropathy Pressure Pressure distribution Pressure profiles Quality of life Regional development Research and Analysis Methods Risk analysis Risk factors Sensors Stress concentration Stress, Mechanical Studies Subgroups Surgery |
title | Comparative Clustering of Plantar Pressure Distributions in Diabetics with Polyneuropathy May Be Applied to Reveal Inappropriate Biomechanical Stress |
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