Continuous Gait Phase Recognition and Prediction Using LSTM Network Across Walking Speeds and Inclinations
Author:
Affiliation:
1. Wuhan University,School of Power and Mechanical Engineering,Wuhan,China,430072
2. The University of Queensland,School of Information Technology and Electrical Engineering,QLD,Australia,4072
Funder
National Natural Science Foundation of China
Research and Development
Natural Science Foundation of Hubei Province
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9959088/9959097/09959678.pdf?arnumber=9959678
Reference20 articles.
1. Multi-target human gait classification using LSTM recurrent neural networks applied to micro-Doppler
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4. Long Short-Term Memory
5. Real-Time continuous gait phase and speed estimation from a single sensor
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