HandDx-200: Multimodal RGB and Thermal Hand Images Paired with Clinical Biomarkers

HandDx-200 is a multimodal dataset comprising RGB and thermal images of palmar and dorsal views of both hands, paired with clinical and laboratory biomarkers from 198 adult participants (73 male, 125 female; age 39.7 ± 11.7 years). Images were acquired under a standardized protocol using a Nikon D3200 RGB camera and a Mastfuyi FY12 infrared thermal imager, with controlled ambient temperature and humidity. Clinical data include age, sex, blood pressure, fasting blood glucose (measured after a minimum 8-hour fast), height, weight, and BMI. Laboratory biomarkers include complete blood count (CBC), lipid profile (total cholesterol, triglycerides, HDL, LDL, VLDL), and HbA1c. All RGB images underwent a fully deterministic preprocessing pipeline (white-balance correction, hand segmentation, orientation normalization, and cropping), with per-image JSON logs documenting every processing step. Segmentation accuracy was quantitatively validated against 48 manually annotated images (mean Dice = 0.994 ± 0.005, IoU = 0.988 ± 0.009). Ethics approval: Medical Research Ethics Committee, National Research Centre, Egypt (Preliminary approval 25 June 2025; Final approval 25 February 2026, No. 15120226). OSF preregistration: https://doi.org/10.17605/OSF.IO/4QUGB. Zenodo DOI: https://doi.org/10.5281/zenodo.19962462. Thermal images are exported as 8-bit pseudocolor BMP files (Rain palette) representing relative spatial thermal patterns; they are not radiometrically calibrated and are suitable for within-image gradient and texture analysis only. All participants fall within the Dark ITA category (ITA < -30 degrees; mean -52.1° ± 3.9°), consistent with the Egyptian recruitment context.