Two kinematic data-based approaches for cane event detection
Author:
Funder
Fundação para a Ciência e a Tecnologia
Publisher
Springer Science and Business Media LLC
Subject
General Computer Science
Link
https://link.springer.com/content/pdf/10.1007/s12652-021-03313-7.pdf
Reference41 articles.
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3. Aung MSH, Thies SB, Kenney LPJ, Howard D, Selles RW, Findlow AH, Goulermas JY (2013) Automated detection of instantaneous gait events using time frequency analysis and manifold embedding. IEEE Trans Neural Syst Rehabil Eng 21(6):908–916. https://doi.org/10.1109/TNSRE.2013.2239313
4. Barth J, Oberndorfer C, Pasluosta C, Schülein S, Gassner H, Reinfelder S, Kugler P, Schuldhaus D, Winkler J, Klucken J, Eskofier BM (2015) Stride segmentation during free walk movements using multi-dimensional subsequence dynamic time warping on inertial sensor data. Sensors 15(3):6419–6440. https://doi.org/10.3390/s150306419
5. Bianchi F, Redmond SJ, Narayanan MR, Cerutti S, Lovell NH (2010) Barometric pressure and triaxial accelerometry-based falls event detection. IEEE Trans Neural Syst Rehabil Eng 18(6):619–627. https://doi.org/10.1109/TNSRE.2010.2070807
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