Lugoda, Pasindu, Garcia-Garcia, Leonardo A, Richoz, Sebastian, Munzenrieder, Niko and Roggen, Daniel (2019) ShapeSense3D - textile-sensing and reconstruction of body geometries. UbiComp '19: The 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing, London, UK, 09-13 September 2019. Published in: Adjunct Proceedings of the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2019 ACM International Symposium on Wearable Computers. 133-136. ACM ISBN 9781450368698
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Abstract
We present an implementation of a textile sensing sleeve with attached strain sensors to capture the shape of body parts. A shape reconstruction algorithm was developed to reconstruct a geometrical model of the deformed sleeve using the elongation measurements obtained from the sensors and an optimisation process. The current system achieves a 0.44 mm error when reconstructing the radius of a conical shape. We discuss future improvements required to form a more reliable 3D shape sensing device. After further development, this sleeve could be utilised for health care application such as muscle density measurements, movement tracking or to replace plaster or thermoplastic casting in the fabrication of orthoses and prostheses.
Item Type: | Conference Proceedings |
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Schools and Departments: | School of Engineering and Informatics > Engineering and Design |
Research Centres and Groups: | Sensor Technology Research Centre |
Subjects: | T Technology T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800 Electronics T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800 Electronics > TK7874 Microelectronics. Integrated circuits > TK7878 Electronic measurements |
Related URLs: | |
Depositing User: | Don Pasindu Lugoda |
Date Deposited: | 09 Jul 2019 13:30 |
Last Modified: | 22 Jul 2022 13:59 |
URI: | http://sro.sussex.ac.uk/id/eprint/84755 |
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📧 Request an updateProject Name | Sussex Project Number | Funder | Funder Ref |
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SmartSensOtics | Unset | EPSRC, GCRF and NIHR | EP/R013837/1 |