Automated identification of diabetic type 2 subjects with and without neuropathy using wavelet transform on pedobarograph.
J Med Syst
; 32(1): 21-9, 2008 Feb.
Article
en En
| MEDLINE
| ID: mdl-18333402
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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Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Interpretación de Imagen Asistida por Computador
/
Pie Diabético
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Diabetes Mellitus Tipo 2
/
Neuropatías Diabéticas
Tipo de estudio:
Diagnostic_studies
/
Prognostic_studies
Límite:
Adolescent
/
Adult
/
Aged
/
Aged80
/
Female
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Humans
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Male
/
Middle aged
Idioma:
En
Revista:
J Med Syst
Año:
2008
Tipo del documento:
Article
País de afiliación:
Singapur