Alzheimer’s Disease Detection Using Comprehensive Analysis of Timed Up and Go Test via Kinect V.2 Camera and Machine Learning

Author:

Seifallahi Mahmoud1ORCID,Mehraban Afsoon Hasani2,Galvin James E.3,Ghoraani Behnaz1ORCID

Affiliation:

1. Department of Computer and Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, FL, USA

2. Department of Occupational Therapy, Faculty of Rehabilitation Sciences, Iran University of Medical Sciences and Health Sciences, Tehran, Iran

3. Department of Neurology, Comprehensive Center for Brain Health, University of Miami, Miami, FL, USA

Funder

National Science Foundation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Biomedical Engineering,General Neuroscience,Internal Medicine,Rehabilitation

Cited by 8 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. OBGESS: Automating Original Bender Gestalt Test Based on One Stage Deep Learning;International Journal of Computational Intelligence Systems;2023-11-13

2. Indoor Human Action Recognition Based on Dual Kinect V2 and Improved Ensemble Learning Method;Sensors;2023-11-02

3. Tackling the class imbalanced dermoscopic image classification using data augmentation and GAN;Multimedia Tools and Applications;2023-10-27

4. Deep Ensemble of Classifiers for Alzheimer’s Disease Detection with Optimal Feature Set;International Journal of Image and Graphics;2023-09-25

5. sMRI Classification of Alzheimer's Disease Using Genetic Algorithm and Multi-Instance Learning (GA+MIL);2023 International Conference on Electrical, Electronics, Communication and Computers (ELEXCOM);2023-08-26

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