A Heterogeneous Ensemble Learning Voting Method for Fatigue Detection in Daily Activities
- 20 January 2018
- journal article
- research article
- Published by Fuji Technology Press Ltd. in Journal of Advanced Computational Intelligence and Intelligent Informatics
- Vol. 22 (1), 88-96
- https://doi.org/10.20965/jaciii.2018.p0088
Abstract
Title: A Heterogeneous Ensemble Learning Voting Method for Fatigue Detection in Daily Activities | Keywords: lower extremity fatigue, gait data, heterogeneous voting method | Author: Lulu Wang, Zhiwu Huang, Shuai Hao, Yijun Cheng, and Yingze YangKeywords
This publication has 15 references indexed in Scilit:
- High-Accuracy Detection of Early Parkinson's Disease through Multimodal Features and Machine LearningInternational Journal of Medical Informatics, 2016
- Differential effects of fatigue on movement variabilityGait & Posture, 2014
- Gait Analysis Methods: An Overview of Wearable and Non-Wearable Systems, Highlighting Clinical ApplicationsSensors, 2014
- An Efficient and Robust Fall Detection System Using Wireless Gait Analysis Sensor with Artificial Neural Network (ANN) and Support Vector Machine (SVM) AlgorithmsOpen Journal of Applied Biosensor, 2014
- Classifying Lower Extremity Muscle Fatigue During Walking Using Machine Learning and Inertial SensorsAnnals of Biomedical Engineering, 2013
- On Discovering the Correlated Relationship between Static and Dynamic Data in Clinical Gait AnalysisLecture Notes in Computer Science, 2013
- Computerized Analysis of Classification of Lung Nodules and Comparison between Homogeneous and Heterogeneous Ensemble of Classifier ModelPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2011
- Velocity Loss as an Indicator of Neuromuscular Fatigue during Resistance TrainingMedicine & Science in Sports & Exercise, 2011
- Mental fatigue impairs physical performance in humansJournal of Applied Physiology, 2009
- Ensemble Methods in Machine LearningLecture Notes in Computer Science, 2000