Topological Nonlinear Analysis of Dynamical Systems in Wearable Sensor-Based Human Physical Activity Inference
Author:
Affiliation:
1. Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
2. School of Biological Science and Medical Engineering, Southeast University, Nanjing, China
Funder
National Key Research and Development Program of China
Science, Technology and Innovation Commission of Shenzhen Municipality
International Exchange Program of Chinese Academy of Science
Bulgarian Academy of Sciences
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Artificial Intelligence,Computer Networks and Communications,Computer Science Applications,Human-Computer Interaction,Signal Processing,Control and Systems Engineering,Human Factors and Ergonomics
Link
http://xplorestaging.ieee.org/ielx7/6221037/10197479/10145473.pdf?arnumber=10145473
Reference43 articles.
1. Control entropy identifies differential changes in complexity of walking and running gait patterns with increasing speed in highly trained runners
2. Deep Learning Models for Real-time Human Activity Recognition with Smartphones
3. A scoping review of non-linear analysis approaches measuring variability in gait due to lower body injury or dysfunction
4. Creating and benchmarking a new dataset for physical activity monitoring
5. An analysis of cooperative coevolutionary algorithms;wiegand,2003
Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Topological Data Analysis for Robust Gait Biometrics Based on Wearable Sensors;IEEE Transactions on Consumer Electronics;2024-05
2. Persistence Landscape-based Topological Data Analysis for Personalized Arrhythmia Classification;2023 IEEE 19th International Conference on Body Sensor Networks (BSN);2023-10-09
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