A Quantitative Method for the Detection of Temperature Differences on the Sole of the Foot in Diabetic Patients
| Autor: | Christian Daul, L. Leija Salas, R. Bayareh Mancilla, A. Vera Hernandez, Didier Wolf, J. Gutierrez Martinez |
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| Přispěvatelé: | Maquin, Didier, Centro de Investigacion y de Estudios Avanzados del Instituto Politécnico Nacional (CINVESTAV), Centre de Recherche en Automatique de Nancy (CRAN), Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), Instituto Nacional de Rehabilitacion |
| Rok vydání: | 2021 |
| Předmět: |
Ir thermography
Pediatrics medicine.medical_specialty business.industry Early detection 030209 endocrinology & metabolism Radiometric data medicine.disease 01 natural sciences Diabetic foot [SPI.AUTO]Engineering Sciences [physics]/Automatic 3. Good health 010309 optics Medical services 03 medical and health sciences [SPI.AUTO] Engineering Sciences [physics]/Automatic 0302 clinical medicine Diabetes mellitus 0103 physical sciences medicine International diabetes federation business ComputingMilieux_MISCELLANEOUS Foot (unit) |
| Zdroj: | Global Medical Engineering Physics Exchanges (GMEPE) & Pan American Health Care Exchanges (PAHCE), GMEPE/PAHCE 2021 Global Medical Engineering Physics Exchanges (GMEPE) & Pan American Health Care Exchanges (PAHCE), GMEPE/PAHCE 2021, Mar 2021, Seville, Spain |
| DOI: | 10.1109/gmepe/pahce50215.2021.9434852 |
| Popis: | Diabetes Mellitus is one of the most common diseases worldwide, considered a major health issue. The International Diabetes Federation has reported that approximately four million people decease each year and ten million more experience terminal complications, such as the diabetic foot. Early detection remains a challenge, since several factors may contribute to prone injuries on the foot. Thus, this paper presents a method to retrieve temperature differences between the sole and regions with abnormal temperature patterns, based on IR thermography and image processing. The database was integrated of 12 patients diagnosed with diabetes mellitus without diabetic foot background. The samples were capture by a cooled IR sensor, characterized to measure human skin temperature. The average temperature was estimated for each segmented region and compared to the sole temperature. Although the temperature differences for the positive cases were less than 1°C, the algorithm prove to retrieve automatically the temperature differences once abnormal patterns were detected and segmented. The contribution lies in the analysis of early detection of the diabetic foot with a quantitative radiometric data processing, that could support the anticipated diagnosis and treatment of the diabetic foot. |
| Databáze: | OpenAIRE |
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