Skin temperature measurement for diagnosing leprosy in Nepal
Automatically measuring localized changes in temperature in the hand using IR-RGB thermography
D.C. Posthumus (TU Delft - Electrical Engineering, Mathematics and Computer Science)
Jan C. Van Gemert – Mentor (TU Delft - Pattern Recognition and Bioinformatics)
T.C. Markhorst – Mentor (TU Delft - Pattern Recognition and Bioinformatics)
Z.Y. Lin – Mentor (TU Delft - Pattern Recognition and Bioinformatics)
Katai Liang – Graduation committee member (TU Delft - Cyber Security)
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Abstract
This study investigates sensor technologies for di- agnosing leprosy in Nepal, focussing on skin tem- perature in the hands using contact and non-contact sensors. Leprosy affects the peripheral nervous system, causing thermoregulatory dysfunction de- tectable via localized skin temperature changes. A systematised comparative review compares contact thermometry, infrared (IR) thermography, and IR- RGB thermography based on measurement quality, usability, and cost. Next to the systematised re- view, an experimental method is proposed to com- bine RGB and IR imaging to enhance the spatial accuracy of automatic region of interest (ROI) de- tection using MediaPipe Hand Landmarker. The study introduces a multimodal dataset of 45 sets of annotated IR-RGB images and validates a geomet- rical image registration model, achieving 93.2% keypoint detection accuracy—significantly outper- forming IR-only sensors. Results show IR-RGB thermography as a cost-effective, flexible, and ac- curate tool for early leprosy diagnosis in resource- limited settings.