Abstract
Current manual therapy pedagogical tools do not enable instructors to objectively assess the precision of hand movements. Methods for capturing the pressure applied to specific regions of the human body are lacking. Instructors of applied manual therapy techniques will benefit from a tool that streamlines their teaching process, thereby enabling their students to be trained accurately and precisely through comparisons of their learned techniques to the instructor’s mastered techniques. This project seeks to accomplish this by providing manual therapy instructors a scalable research platform that models instructor and student manual therapy data provided by a Studio 1 Labs pressure sensing fabric. The combination of the pressure sensing fabric and real-time data visualizations will enable instructors to provide immediate feedback to students to improve the quality of the therapy they provide. This paper will show the evolution of this physical therapy research platform, its development life cycle, current state, plans for future research and development, and a potential implementation of the tool in academic institutions.
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Rimaldi, T.V., Grossmann, D.R., Schwartz, D.R. (2021). Developing a Scalable Platform and Analytics Dashboard for Manual Physical Therapy Practices Using Pressure Sensing Fabric. In: Arabnia, H.R., Deligiannidis, L., Tinetti, F.G., Tran, QN. (eds) Advances in Software Engineering, Education, and e-Learning. Transactions on Computational Science and Computational Intelligence. Springer, Cham. https://doi.org/10.1007/978-3-030-70873-3_19
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