One of the most common and severe complications of diabetes mellitus is diabetic foot, making early detection a public health priority. Infrared thermography is a promising noninvasive technique for identifying abnormal thermal patterns associated with inflammation, neuropathy, angiopathy, and tissue damage. This technique involves acquiring infrared radiation emitted by the skin and processing it to generate thermal maps that reflect underlying physiological changes. However, the reliability of thermographic assessments depends on strict technical conditions, including sensor performance, environmental control, and reproducible measurements. Despite its advantages, the clinical adoption of thermography is limited by the absence of standardized acquisition protocols and the influence of external and physiological factors on temperature measurements. Addressing these challenges is essential to ensure the accurate interpretation and validation of results. Recent advances, such as the incorporation of artificial intelligence algorithms and the development of portable, low-cost devices, offer new opportunities to enhance thermography’s applicability in clinical settings and home monitoring.

A diabetic foot is a serious complication of Diabetes Mellitus (DM) and a leading cause of non-traumatic lower-limb amputations. Infrared thermography has been suggested as a low-cost, noninvasive tool for the early detection of thermal alterations associated with this condition. This study evaluates the performance of a thermal imaging system based on the FLIR Lepton 3.1R module through technical characterization under predefined acquisition conditions. A blackbody source was used as the thermal reference within a temperature range of 31 to 40 °C, and measurements were acquired at predefined distances. Thermal measurements obtained with the FLIR Lepton 3.1R were compared with those acquired using an FLIR C5 thermal camera, which was used as a comparison device in the experimental evaluation. The FLIR Lepton 3.1R measurements showed an average deviation of 1 to 2 °C relative to the blackbody reference values, indicating stable performance under the evaluated acquisition conditions. Overall, the results support the potential of the FLIR Lepton 3.1R module as a low-cost platform for the analysis of spatial thermal patterns, representing a preliminary step toward future clinical validation studies aimed at diabetic foot assessment.