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Applied Sciences
Volume 15
Issue 11
10.3390/app15115886
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This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

Advanced AI-Driven Thermographic Analysis for Diagnosing Diabetic Peripheral Neuropathy and Peripheral Arterial Disease

by
Albert Siré Langa
1,
Jose Luis Lázaro-Martínez
2,*,
Aroa Tardáguila-García
2,
Irene Sanz-Corbalán
2,
Sergi Grau-Carrión
1,
Ibon Uribe-Elorrieta
2,
Arià Jaimejuan-Comes
2 and
Ramon Reig-Bolaño
1
1
Faculty of Science Technology and Engineering (FCTE), Universitat de Vic–Universitat Central de Catalunya, 08500 Vic, Spain
2
Diabetic Foot Unit, Facultad de Medicina, Universidad Complutense de Madrid, Instituto de Investigacion Sanitaria del Hospital Clínico San Carlos, 28040 Madrid, Spain
*
Author to whom correspondence should be addressed.
Appl. Sci. 2025, 15(11), 5886; https://doi.org/10.3390/app15115886
Submission received: 28 April 2025 / Revised: 19 May 2025 / Accepted: 22 May 2025 / Published: 23 May 2025
(This article belongs to the Special Issue Applications of Sensors in Biomechanics and Biomedicine)
Versions Notes

Abstract

This study explores the integration of advanced artificial intelligence (AI) techniques with infrared thermography for diagnosing diabetic peripheral neuropathy (DPN) and peripheral arterial disease (PAD). Diabetes-related foot complications, including DPN and PAD, are leading causes of morbidity and disability worldwide. Traditional diagnostic methods, such as the monofilament test for DPN and ankle–brachial pressure index for PAD, have limitations in sensitivity, highlighting the need for improved solutions. Thermographic imaging, a non-invasive, cost-effective, and reliable tool, captures temperature distributions of the patient plantar surface, enabling the detection of physiological changes linked to these conditions. This study collected thermographic data from diabetic patients and employed convolutional neural networks (CNNs) and vision transformers (ViTs) to classify individuals as healthy or affected by DPN or PAD (not healthy). These neural networks demonstrated superior diagnostic performance, compared to traditional methods (an accuracy of 95.00%, a sensitivity of 100.00%, and a specificity of 90% in the case of the ResNet-50 network). The results underscored the potential of combining thermography with AI to provide scalable, accurate, and patient-friendly diagnostics for diabetic foot care. Future work should focus on expanding datasets and integrating explainability techniques to enhance clinical trust and adoption.
Keywords: artificial intelligence; visual transformers; CNN; diabetic foot; diabetic peripheral neuropathy; peripheral arterial disease; thermography artificial intelligence; visual transformers; CNN; diabetic foot; diabetic peripheral neuropathy; peripheral arterial disease; thermography

Share and Cite

MDPI and ACS Style

Siré Langa, A.; Lázaro-Martínez, J.L.; Tardáguila-García, A.; Sanz-Corbalán, I.; Grau-Carrión, S.; Uribe-Elorrieta, I.; Jaimejuan-Comes, A.; Reig-Bolaño, R. Advanced AI-Driven Thermographic Analysis for Diagnosing Diabetic Peripheral Neuropathy and Peripheral Arterial Disease. Appl. Sci. 2025, 15, 5886. https://doi.org/10.3390/app15115886

AMA Style

Siré Langa A, Lázaro-Martínez JL, Tardáguila-García A, Sanz-Corbalán I, Grau-Carrión S, Uribe-Elorrieta I, Jaimejuan-Comes A, Reig-Bolaño R. Advanced AI-Driven Thermographic Analysis for Diagnosing Diabetic Peripheral Neuropathy and Peripheral Arterial Disease. Applied Sciences. 2025; 15(11):5886. https://doi.org/10.3390/app15115886

Chicago/Turabian Style

Siré Langa, Albert, Jose Luis Lázaro-Martínez, Aroa Tardáguila-García, Irene Sanz-Corbalán, Sergi Grau-Carrión, Ibon Uribe-Elorrieta, Arià Jaimejuan-Comes, and Ramon Reig-Bolaño. 2025. "Advanced AI-Driven Thermographic Analysis for Diagnosing Diabetic Peripheral Neuropathy and Peripheral Arterial Disease" Applied Sciences 15, no. 11: 5886. https://doi.org/10.3390/app15115886

APA Style

Siré Langa, A., Lázaro-Martínez, J. L., Tardáguila-García, A., Sanz-Corbalán, I., Grau-Carrión, S., Uribe-Elorrieta, I., Jaimejuan-Comes, A., & Reig-Bolaño, R. (2025). Advanced AI-Driven Thermographic Analysis for Diagnosing Diabetic Peripheral Neuropathy and Peripheral Arterial Disease. Applied Sciences, 15(11), 5886. https://doi.org/10.3390/app15115886

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