Abstract
Utilising MEMS technology motion sensors and algorithms for motion data processing, a prototype device is proposed as a viable solution for movement diagnostics during sports or rehabilitation activities, based on the documented in the medical journals benefits of eccentric resistive training with full range of motion. The proposed device evaluates the quality of the movement by measuring the range of motion and both eccentric and concentric phases of the movement.
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Acknowledgements
This work was supported by European Regional Development Fund and the Operational Program “Science and Education for Smart Growth” under contract UNITe- BG05M2OP001-1.001-0004-01 (2018–2023). The authors of this study would like to thank Michel Aflak and Kristian Lauszus. The base application “Bluetooth-Terminal”, developed by Michel and the Kalman filter algorithm and blog post about the algorithm, developed and written by Kristian, proved to be of great use throughout the development of the device. The authors of this study would like also to thank the associate professors of the faculty of Telecommunications at Technical University of Sofia, Bulgaria for their recommendations, review and feedback, during the writing of this research paper.
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© 2019 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Lalov, V., Manolova, A. (2019). A Novel Portable Tracking Device with Kalman Filter for Hand and Arm Rehabilitation Applications. In: Poulkov, V. (eds) Future Access Enablers for Ubiquitous and Intelligent Infrastructures. FABULOUS 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 283. Springer, Cham. https://doi.org/10.1007/978-3-030-23976-3_7
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DOI: https://doi.org/10.1007/978-3-030-23976-3_7
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