Automated identification of diabetic type 2 subjects with and without neuropathy using wavelet transform on pedobarograph.
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.
Acharya
Rajendra
R
Electronic and Computer Engineering Division, Ngee Ann Polytechnic, 535 Clementi Rd, Clementi, Singapore. aru@np.edu.sg
Tan
Peck Ha
PH
Subramaniam
Tavintharan
T
Tamura
Toshiyo
T
Chua
Kuang Chua
KC
Goh
Seach Chyr Ernest
SC
Lim
Choo Min
CM
Goh
Shu Yi Diana
SY
Chung
Kang Rui Conrad
KR
Law
Chelsea
C
D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D003924:Diabetes Mellitus, Type 2 / Q000175:diagnosis*; D017719:Diabetic Foot; D003929:Diabetic Neuropathies; D005260:Female; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D008297:Male; D008875:Middle Aged; D016571:Neural Networks, Computer; D016011:Normal Distribution; D011312:Pressure