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Journal of Medical Systems
Published in: Journal of Medical Systems 1/2008

01-02-2008 | Original Paper

Automated Identification of Diabetic Type 2 Subjects with and without Neuropathy Using Wavelet Transform on Pedobarograph

Authors: Rajendra Acharya U, Peck Ha Tan, Tavintharan Subramaniam, Toshiyo Tamura, Kuang Chua Chua, Seach Chyr Ernest Goh, Choo Min Lim, Shu Yi Diana Goh, Kang Rui Conrad Chung, Chelsea Law

Published in: Journal of Medical Systems | Issue 1/2008

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Abstract

Diabetes is a disorder of metabolism—the way our bodies use digested food for growth and energy. The most common form of diabetes is Type 2 diabetes. Abnormal plantar pressures are considered to play a major role in the pathologies of neuropathic ulcers in the diabetic foot. The purpose of this study was to examine the plantar pressure distribution in normal, diabetic Type 2 with and without neuropathy subjects. Foot scans were obtained using the F-scan (Tekscan USA) pressure measurement system. Various discrete wavelet coefficients were evaluated from the foot images. These extracted parameters were extracted using the discrete wavelet transform (DWT) and presented to the Gaussian mixture model (GMM) and a four-layer feed forward neural network for classification. We demonstrated a sensitivity of 100% and a specificity of more than 85% for the classifiers.
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Metadata
Title
Automated Identification of Diabetic Type 2 Subjects with and without Neuropathy Using Wavelet Transform on Pedobarograph
Authors
Rajendra Acharya U
Peck Ha Tan
Tavintharan Subramaniam
Toshiyo Tamura
Kuang Chua Chua
Seach Chyr Ernest Goh
Choo Min Lim
Shu Yi Diana Goh
Kang Rui Conrad Chung
Chelsea Law
Publication date
01-02-2008
Publisher
Springer US
Published in
Journal of Medical Systems / Issue 1/2008
Print ISSN: 0148-5598
Electronic ISSN: 1573-689X
DOI
https://doi.org/10.1007/s10916-007-9103-y

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