A combined Adaptive Neuro-Fuzzy and Bayesian strategy for recognition and prediction of gait events using wearable sensors

Martinez-Hernandez, U., Rubio-Solis, A., Panoutsos, G. et al. (1 more author) (2017) A combined Adaptive Neuro-Fuzzy and Bayesian strategy for recognition and prediction of gait events using wearable sensors. In: Proceedings of the IEEE International Conference on Fuzzy Systems 2017. 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 9-12 July 2017, Naples, Italy. IEEE . ISBN 9781509060344

Abstract

Metadata

Authors/Creators:
  • Martinez-Hernandez, U.
  • Rubio-Solis, A.
  • Panoutsos, G.
  • Dehghani-Sanij, A.A.
Copyright, Publisher and Additional Information: © 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. Reproduced in accordance with the publisher's self-archiving policy.
Keywords: Legged locomotion; Bayes methods; Robot sensing systems; Adaptive systems; Angular velocity; Wearable sensors; Robustness
Dates:
  • Published: 24 August 2017
  • Published (online): 24 August 2017
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield)
Depositing User: Symplectic Sheffield
Date Deposited: 03 Nov 2017 14:34
Last Modified: 26 Mar 2018 05:34
Published Version: https://doi.org/10.1109/FUZZ-IEEE.2017.8015447
Status: Published
Publisher: IEEE
Refereed: Yes
Identification Number: https://doi.org/10.1109/FUZZ-IEEE.2017.8015447

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