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AI-based Positioning and Personalization Platform for Human Body Models (HBMs)

Project period
January 2024 – December 2025

Objective
This project aims to establish an AI-based online platform for automated, and robust personalization and positioning of HBMs, focusing on baby HBMs. By this we eliminate the need for users to tackle personalization and positioning which is often challenging and tedious, thus the platform could be an tranformative tool for driving innovations relating to HBMs.

Background
Finite element HBMs are digitalized representations of the human body and have emerged as significant tools for driving 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.

Crossdisciplinary collaboration
This project brings expertise within biomechanical modeling and artificial intelligence involving researchers from KTH School of Electrical Engineering and Computer Science and Applied AI at the Department of Industrial Systems at Research Institutes of Sweden (RISE).

Former project name: Virtual Baby Plattform

Contacts

Xiaogai Li

Associate Professor, CBH School at KTH, Co-PI: AI-based Positioning and Personalization Platform for Human Body Models (HBMs), Former Co-PI: Seed funding for large grant proposals, Digital Futures Faculty

xiaogai@kth.se