Elderly Fall Detection: A Lightweight Kinect Based Deep Learning Approach

Author:

Fayad Moustafa1,Hachani Mohamed-Yacine1,Mostefaoui Ahmed2,Chouali Samir2,Yahiaoui Réda1

Affiliation:

1. University of Bourgogne Franche-Comté, Besançon, France

2. University of Bourgogne Franche-Comté, Montbéliard, France

Funder

European regional development fund

Publisher

ACM

Reference31 articles.

1. 2020. Les personnes âgées. https://www.un.org/fr/sections/issues-depth/ageing/index.html [Online ; accessed 8. May 2022 ]. 2020. Les personnes âgées. https://www.un.org/fr/sections/issues-depth/ageing/index.html [Online; accessed 8. May 2022].

2. Ahmed Abobakr , Mohammed Hossny , Hala Abdelkader , and Saeid Nahavandi . 2018. Rgb-d fall detection via deep residual convolutional lstm networks. In 2018 Digital Image Computing: Techniques and Applications (DICTA) . IEEE , 1--7. Ahmed Abobakr, Mohammed Hossny, Hala Abdelkader, and Saeid Nahavandi. 2018. Rgb-d fall detection via deep residual convolutional lstm networks. In 2018 Digital Image Computing: Techniques and Applications (DICTA). IEEE, 1--7.

3. Automated Detection of Parkinson’s Disease Based on Multiple Types of Sustained Phonations Using Linear Discriminant Analysis and Genetically Optimized Neural Network

4. Coarse-Fine Convolutional Deep-Learning Strategy for Human Activity Recognition

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1. Deep learning for computer vision based activity recognition and fall detection of the elderly: a systematic review;Applied Intelligence;2024-07-08

2. Fall Detection for Elderly People using LiDAR Sensor;2024 3rd International Conference on Artificial Intelligence For Internet of Things (AIIoT);2024-05-03

3. Transfer Learning for Efficiency in Elderly Fall Detection with Limited Data Samples;Information Systems Engineering and Management;2024

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