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Computer-Based Identification of Type 2 Diabetic Subjects with and Without Neuropathy Using Dynamic Planter Pressure and Principal Component Analysis

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Abstract

Diabetes is a chronic disease that is characterized by an increased blood glucose level due to insulin resistance. Type 2 diabetes is common in middle aged and old people. In this work, we present a technique to analyze dynamic foot pressures images and classify them into normal, diabetes type 2 with and without neuropathy classes. Plantar pressure images were obtained using the F-Scan (Tekscan, USA) in-shoe measurement system. We used Principal Component Analysis (PCA) and extracted the eigenvalues from different regions of the foot image. The features extracted from region 1 of the foot pressure image, which were found to be clinically significant, were fed into the Fuzzy classifier (Sugeno model) for automatic classification. Our results show that the proposed method is able to identify the unknown class with an accuracy of 93.7%, sensitivity of 100%, and specificity of 83.3%. Moreover, in this work, we have proposed an integrated index using the eigenvalues to differentiate the normal subjects from diabetes with and without neuropathy subjects using just one number. This index will help the clinicians in easy and objective daily screening, and it can also be used as an adjunct tool to cross check their diagnosis.

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Acknowledgements

The authors thank the Tote-Fund, Singapore, for supporting this project. They also thank Cheong Mun Siong Aaron and Heng Kyne Ian for helping in the development of the software.

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Authors and Affiliations

  1. Electronic & Computer Engineering Division, Ngee Ann Polytechnic, 535 Clementi Road, Singapore, 599489, Singapore

    U. Rajendra Acharya, Chua Kuang Chua & Tan Peck Ha

  2. Podiatry Department, Singapore General Hospital, Outram Road, Singapore, 169608, Singapore

    Jasper Tong

  3. School of Mechanical and Aerospace Engineering, College of Engineering, Nanyang Technological University, 50, Nanyang Avenue, Singapore, 639798, Singapore

    Vinitha Sree Subbhuraam

  4. Framingham State College, Massachusetts, 01701, USA

    Dhanjoo N. Ghista

  5. School of Computing, Department of Computer Science and Engineering, National Institute of Science and Technology, Orissa, India

    Subhagata Chattopadhyay

  6. Department of Biomedical Imaging, University of Malaya, Kuala Lumpur, Malaysia

    Kwan-Hoong Ng

  7. Fellow AIMBE, Biomedical Technologies Inc., Denver, CO, USA

    Jasjit S. Suri

  8. Idaho State University, Pocatello, ID, USA

    Jasjit S. Suri

Authors
  1. U. Rajendra Acharya
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  2. Jasper Tong
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  3. Vinitha Sree Subbhuraam
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  4. Chua Kuang Chua
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  5. Tan Peck Ha
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  6. Dhanjoo N. Ghista
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  7. Subhagata Chattopadhyay
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  8. Kwan-Hoong Ng
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  9. Jasjit S. Suri
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Correspondence to U. Rajendra Acharya.

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Acharya, U.R., Tong, J., Subbhuraam, V.S. et al. Computer-Based Identification of Type 2 Diabetic Subjects with and Without Neuropathy Using Dynamic Planter Pressure and Principal Component Analysis. J Med Syst 36, 2483–2491 (2012). https://doi.org/10.1007/s10916-011-9715-0

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  • DOI: https://doi.org/10.1007/s10916-011-9715-0

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