Comparative Clustering of Plantar Pressure Distributions in Diabetics with Polyneuropathy May Be Applied to Reveal Inappropriate Biomechanical Stress

• Published in: PloS one Vol. 11; no. 8; p. e0161326
• Main Authors: Niemann, Uli, Spiliopoulou, Myra, Szczepanski, Thorsten, Samland, Fred, Grützner, Jens, Senk, Dominik, Ming, Antao, Kellersmann, Juliane, Malanowski, Jan, Klose, Silke, Mertens, Peter R
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 16.08.2016; Public Library of Science (PLoS)
• 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
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0161326

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.