Computer-aided identification of degenerative neuromuscular diseases based on gait dynamics and ensemble decision tree classifiers
出版年份 2021 全文链接
标题
Computer-aided identification of degenerative neuromuscular diseases based on gait dynamics and ensemble decision tree classifiers
作者
关键词
Gait analysis, Statistical signal processing, Decision trees, Parkinson disease, Machine learning, Amyotrophic lateral sclerosis, Huntington disease, Support vector machines
出版物
PLoS One
Volume 16, Issue 6, Pages e0252380
出版商
Public Library of Science (PLoS)
发表日期
2021-06-05
DOI
10.1371/journal.pone.0252380
参考文献
相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。- A robust, cost-effective and non-invasive computer-aided method for diagnosis three types of neurodegenerative diseases with gait signal analysis
- (2020) Seyede Marziyeh Ghoreshi Beyrami et al. MEASUREMENT
- Automated cognitive health assessment in smart homes using machine learning
- (2020) Abdul Rehman Javed et al. Sustainable Cities and Society
- Texture Classification and Visualization of Time Series of Gait Dynamics in Patients With Neuro-Degenerative Diseases
- (2018) Tuan D. Pham IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING
- Classification of gait signals into different neurodegenerative diseases using statistical analysis and recurrence quantification analysis
- (2018) Pooja Prabhu et al. PATTERN RECOGNITION LETTERS
- Comparison of Random Subspace and Voting Ensemble Machine Learning Methods for Face Recognition
- (2018) Mehmet Yaman et al. Symmetry-Basel
- Guidelines for Assessment of Gait and Reference Values for Spatiotemporal Gait Parameters in Older Adults: The Biomathics and Canadian Gait Consortiums Initiative
- (2017) Olivier Beauchet et al. Frontiers in Human Neuroscience
- Therapeutic opportunities and challenges of induced pluripotent stem cells-derived motor neurons for treatment of amyotrophic lateral sclerosis and motor neuron disease
- (2017) ManojKumar Jaiswal Neural Regeneration Research
- Sensor-Based Gait Parameter Extraction With Deep Convolutional Neural Networks
- (2017) Julius Hannink et al. IEEE Journal of Biomedical and Health Informatics
- The aging neuromuscular system and motor performance
- (2016) Sandra K. Hunter et al. JOURNAL OF APPLIED PHYSIOLOGY
- Error-Correcting Output Codes in Classification of Human Induced Pluripotent Stem Cell Colony Images
- (2016) Henry Joutsijoki et al. Biomed Research International
- Classification of gait rhythm signals between patients with neuro-degenerative diseases and normal subjects: Experiments with statistical features and different classification models
- (2015) Yi Xia et al. Biomedical Signal Processing and Control
- A Review on Ensembles for the Class Imbalance Problem: Bagging-, Boosting-, and Hybrid-Based Approaches
- (2011) M. Galar et al. IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART C-APPLICATIONS AND RE
- Statistical Analysis of Gait Rhythm in Patients With Parkinson's Disease
- (2009) Yunfeng Wu et al. IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING
- RUSBoost: A Hybrid Approach to Alleviating Class Imbalance
- (2009) Chris Seiffert et al. IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART A-SYSTEMS AND HUMANS
- Decrease in Hurst exponent of human gait with aging and neurodegenerative diseases
- (2008) Zhuang Jian-Jun et al. Chinese Physics B
Become a Peeref-certified reviewer
The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.
Get StartedAsk a Question. Answer a Question.
Quickly pose questions to the entire community. Debate answers and get clarity on the most important issues facing researchers.
Get Started