Personalised 3D models of patients' bodies constitute an effective approach for rapidly and accurately evaluating burned and total skin surfaces in constrained burn care settings. This study aims to develop an automatic method for generating 3D models of human subjects with accurate body shapes from accessible data (gender, age, height, weight). We developed a statistical model to infer three body composition parameters from the body mass index (BMI) to adjust the weight, muscle and micro ratios in MakeHuman, defining the subject's global and local morphologies. The proposed approach improves body surface area estimation, with a mean percentage error of 2.10%, outperforming the results of traditional anthropometric formulas and parametric modelling methods used in clinical settings. Across the population, it provides a continuous representation of human morphology, covering a wide range of body shapes and providing a valuable tool for burn assessment and personalised care applications, particularly for obese individuals.
Thibault et al. (Thu,) studied this question.