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Thermal-Comfort Design Of Personalized Casts

ACM UIST 2017
Xiaoting Zhang, Guoxin Fang, Chengkai Dai, Jouke Verlinden, Jun Wu, Emily Whiting, Charlie C.L. Wang

Abstract

This paper introduces a novel method for designing personalized orthopedic casts which are aware of thermal-comfort while satisfying mechanical requirements. Our pipeline starts from thermal images taken by an infrared camera, by which the distribution of thermal-comfort sensitivity is generated on the surface of a 3D scanned model. We formulate a hollowed Voronoi tessellation pattern to represent the covered region for a web-like cast design. The pattern is further optimized according to the thermal-comfort sensitivity calculated from thermal images. Working together with a thickness variation method, we generate a solid model for a personalized cast maximizing both thermal comfort and mechanical stiffness. To demonstrate the effectiveness of our approach, 3D printed models of personalized casts are tested on body parts of different individuals.

This video presents our recent work published in the following paper: Xiaoting Zhang, Guoxin Fang, Chengkai Dai, Jouke Verlinden, Jun Wu, Emily Whiting, and Charlie C.L. Wang, "Thermal-comfort design of personalized casts", ACM Symposium on User Interface Software and Technology (UIST), Quebec City, Canada, October 22-25, 2017.

Bibtex

@inproceedings{Zhang2017, author = {Xiaoting Zhang and Guoxin Fang and Chengkai Dai and Jouke Verlinden and Jun Wu and Emily Whiting and Charlie C.L. Wang}, title = {Thermal-Comfort Design of Personalized Casts}, booktitle = {Proceedings of the 30th Annual ACM Symposium on User Interface Software and Technology}, series = {UIST '17}, year = {2017}, pages = {243--254}, numpages = {12}, publisher = {ACM}, }

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