Computer-Based Diagnosis of Early Signs of Diabetic Peripheral Neuropathy in Thermal Videos of the Plantar Foot
- Resource Type
- Conference
- Authors
- Soliz, Peter; Wigdahl, Jeff; Soliz, Sarah; Saint-Lot, Sheraz; Bhandarkar, Adhitya; Bhatia, Sooraj; Duran-Valdez, Elizabeth; Schade, David S.
- Source
- 2024 IEEE Southwest Symposium on Image Analysis and Interpretation (SSIAI) Image Analysis and Interpretation (SSIAI), 2024 IEEE Southwest Symposium on. :25-28 Mar, 2024
- Subject
- Bioengineering
Components, Circuits, Devices and Systems
Computing and Processing
Robotics and Control Systems
Signal Processing and Analysis
Support vector machines
Temperature sensors
Vibrations
Temperature measurement
Optical fiber sensors
Vectors
Diabetes
diabetes
diabetic peripheral neuropathy
diabetic foot
support vector machines
thermal imaging
- Language
- ISSN
- 2473-3598
Diabetic peripheral neuropathy (DPN) is a complication of diabetes that causes severe foot pain and frequently leads to amputation. Early detection is critical to saving patients from foot ulcers and amputation. This paper presents an automatic system to identify thermal biomarkers associated with DPN. Research Design and Methods: 141 subjects diagnosed with diabetes mellitus (DM) were enrolled in the study. Subjects were categorized as those with DM but without DPN, those with DPN based on a positive nerve conduction study, and those without DPN. A support vector machine (SVM) was used to classify the subjects having DPN based on thermal parameters related to temperature recovery after a cold provocation. Results: The classifier produced a sensitivity/specificity of 0.78/0.89 in identifying DPN. Conclusions: The SVM classifier can identify patients with the large fiber form of DPN. A different reference standard had to be used to detect small fiber neuropathy.