Title: A statistical shape modelling framework and software for predicting skull and muscle networks from head

Authors: Tan-Nhu Nguyen; Phong-Phu Vo; Vi-Do Tran; Ngoc-Bich Le; Nu-Vuong Nguyen-Tran; Truong-Minh Thuong; Tien-Tuan Dao

Addresses: School of Biomedical Engineering, International University, Quarter 33, Linh Xuan Ward, Ho Chi Minh City, Vietnam; Vietnam National University Ho Chi Minh City, Linh Xuan Ward, Ho Chi Minh City, Vietnam ' Ho Chi Minh City University of Technology and Education, No. 1, Vo Van Ngan Street, Thu Duc Ward, Ho Chi Minh City, Vietnam ' Ho Chi Minh City University of Technology and Education, No. 1, Vo Van Ngan Street, Thu Duc Ward, Ho Chi Minh City, Vietnam ' School of Biomedical Engineering, International University, Quarter 33, Linh Xuan Ward, Ho Chi Minh City, Vietnam; Vietnam National University Ho Chi Minh City, Linh Xuan Ward, Ho Chi Minh City, Vietnam ' Military Hospital 175, 786 Nguyễn Kiệm Street, Hạnh Thông Ward, Ho Chi Minh City, Vietnam ' Military Hospital 175, 786 Nguyễn Kiệm Street, Hạnh Thông Ward, Ho Chi Minh City, Vietnam ' University Lille, CNRS, Centrale Lille, UMR 9013-LaMcube-Laboratoire de Mécanique, Multiphysique, Multiéchelle, Lille, F-59000, France

Abstract: Real-time biomechanical head simulation is necessary for providing bio-feedbacks for facial paralysis grading. This process is challenging and needs enhancement in both dataset and personalising procedure. We introduced a statistical framework for dataset generation, skull prediction, and muscle strain computation. The head-to-skull shape relation was trained through their shape parameters. After a ten-fold cross-validation, the mean testing error was 1.86 mm with 6.17s ± 0.05s for each fold. The personalised muscle network could be animated by interacting with the system interface for computing the muscle strains. This study has three contributions: a system for personalising and analysing biomechanical head; a procedure for head region cutting and sampling; head-and-skull shapes with their topological features. In perspective, this framework will be used to enhance the accuracy of the head-to-skull prediction. Moreover, we will use the system to generate the standard muscle strains for facial paralysis diagnosing. The dataset is available upon reasonable requests.

Keywords: head-to-skull prediction; biomechanical head simulation; statistical shape modelling; facial paralysis grading; facial mimic rehabilitation.

DOI: 10.1504/IJBET.2026.151949

International Journal of Biomedical Engineering and Technology, 2026 Vol.50 No.2, pp.132 - 157

Received: 13 Jan 2025
Accepted: 16 Mar 2025
Published online: 27 Feb 2026 *

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