About the project
Objective
This project aims to establish an AI-based online platform for automated, and robust personalization and positioning of HBMs, focusing on infant HBMs. By developing a family of infant HBMs equipped with efficient personalization and a novel AI-based positioning pipeline, the project facilities rapid and subject-specific model generation that can foster industrial and clinical innovations relating to infant safety.
Background
Finite element human body models (HBMs) are digitalized representations of the human body and have become essential tools in both industrial innovation and clinical applications. These models often are a baseline and in a specified position, and before the use of the HBMs, personalization and positioning of HBMs are needed. Despite continuous active development, HBM positioning remains challenging and tedious; further comparing with existing adult HBMs, infant and child HBMs are underdeveloped.
This project builds on, and further develops, the results from the Research Pair project: “AI-based Positioning and Personalization Platform for Human Body Models (HBMs)“.
Crossdisciplinary collaboration
This project combines expertise within mechanical and biomechanical modeling (from KTH School of Engineering Sciences in Chemistry, Biotechnology and Health) with expertise in artificial intelligence (from the Department of Industrial Systems at RISE).
