AUTHOR=Killen Bryce A. , Van Rossom Sam , Burg Fien , Vander Sloten Jos , Jonkers Ilse 

TITLE=In-silico techniques to inform and improve the personalized prescription of shoe insoles

JOURNAL=Frontiers in Bioengineering and Biotechnology

VOLUME=12

YEAR=2024

URL=https://www.frontiersin.org/journals/bioengineering-and-biotechnology/articles/10.3389/fbioe.2024.1351403

DOI=10.3389/fbioe.2024.1351403

ISSN=2296-4185

ABSTRACT=<p><bold>Background:</bold> Corrective shoe insoles are prescribed for a range of foot deformities and are typically designed based on a subjective assessment limiting personalization and potentially leading to sub optimal treatment outcomes. The incorporation of <italic>in silico</italic> techniques in the design and customization of insoles may improve personalized correction and hence insole efficiency.</p><p><bold>Methods:</bold> We developed an <italic>in silico</italic> workflow for insole design and customization using a combination of measured motion capture, inverse musculoskeletal modelling as well as forward simulation approaches to predict the kinematic response to specific insole designs. The developed workflow was tested on twenty-seven participants containing a combination of healthy participants (7) and patients with flatfoot deformity (20).</p><p><bold>Results:</bold> Average error between measured and simulated kinematics were 4.7 ± 3.1, 4.5 ± 3.1, 2.3 ± 2.3, and 2.3 ± 2.7° for the chopart obliquity, chopart anterior-posterior axis, tarsometatarsal first ray, and tarsometatarsal fifth ray joints respectively.</p><p><bold>Discussion</bold>: The developed workflow offers distinct advantages to previous modeling workflows such as speed of use, use of more accessible data, use of only open-source software, and is highly automated. It provides a solid basis for future work on improving predictive accuracy by adapting the currently implemented insole model and incorporating additional data such as plantar pressure.</p>