Using Transparent Neural Networks and Wearable Inertial Sensors to Generate Physiologically-Relevant Insights for Gait
Author:
Affiliation:
1. Hasso Plattner Institute, University of Potsdam,Digital Health - Connected Healthcare,Potsdam,Germany
2. University of Potsdam,Division of Training and Movement Sciences,Potsdam,Germany
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10068862/10068777/10069491.pdf?arnumber=10069491
Reference29 articles.
1. Classifying Lower Extremity Muscle Fatigue During Walking Using Machine Learning and Inertial Sensors
2. Smartphone-based human fatigue level detection using machine learning approaches
3. Explaining Machine Learning Models for Clinical Gait Analysis
4. Explaining the unique nature of individual gait patterns with deep learning
5. Deep Learning to Predict Falls in Older Adults Based on Daily-Life Trunk Accelerometry
Cited by 1 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. DUO-GAIT: A gait dataset for walking under dual-task and fatigue conditions with inertial measurement units;Scientific Data;2023-08-21
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