A Fall Posture Classification and Recognition ...
Document type :
Article dans une revue scientifique: Article original
DOI :
Permalink :
Title :
A Fall Posture Classification and Recognition Method Based on Wavelet Packet Transform and Support Vector Machine
Author(s) :
Zhang, Q. Y. [Auteur]
Tao, J. [Auteur]
Sun, Q. L. [Auteur]
Zeng, Xianyi [Auteur]
École nationale supérieure des arts et industries textiles [ENSAIT]
Génie des Matériaux Textiles - ULR 2461 [GEMTEX]
Dehmer, M. [Auteur]
Zhou, Q. [Auteur]
Tao, J. [Auteur]
Sun, Q. L. [Auteur]
Zeng, Xianyi [Auteur]
École nationale supérieure des arts et industries textiles [ENSAIT]
Génie des Matériaux Textiles - ULR 2461 [GEMTEX]
Dehmer, M. [Auteur]
Zhou, Q. [Auteur]
Journal title :
Applied Sciences
Abbreviated title :
Appl. Sci.-Basel
Volume number :
11
Pages :
-
Publication date :
2021-06-18
ISSN :
2076-3417
English keyword(s) :
random forest
support vector machine
wavelet packet transform
recognition
classification
falling posture
support vector machine
wavelet packet transform
recognition
classification
falling posture
HAL domain(s) :
Sciences de l'ingénieur [physics]
English abstract : [en]
An accidental fall seriously threatens the health and safety of the elderly. The injuries caused by a fall have a lot to do with the different postures during the fall. Therefore, recognizing the posture of falling is ...
Show more >An accidental fall seriously threatens the health and safety of the elderly. The injuries caused by a fall have a lot to do with the different postures during the fall. Therefore, recognizing the posture of falling is essential for the rescue and care of the elderly. In this paper, a novel method was proposed to improve the classification and recognition accuracy of fall postures. Firstly, the wavelet packet transform was used to extract multiple features from sample data. Secondly, random forest was used to evaluate the importance of the extracted features and obtain effective features through screening. Finally, the support vector machine classifier based on the linear kernel function was used to realize the falling posture recognition. The experiment results on “Simulated Falls and Daily Living Activities Data Set” show that the proposed method can distinguish different types of fall postures and achieve 99% classification accuracy.Show less >
Show more >An accidental fall seriously threatens the health and safety of the elderly. The injuries caused by a fall have a lot to do with the different postures during the fall. Therefore, recognizing the posture of falling is essential for the rescue and care of the elderly. In this paper, a novel method was proposed to improve the classification and recognition accuracy of fall postures. Firstly, the wavelet packet transform was used to extract multiple features from sample data. Secondly, random forest was used to evaluate the importance of the extracted features and obtain effective features through screening. Finally, the support vector machine classifier based on the linear kernel function was used to realize the falling posture recognition. The experiment results on “Simulated Falls and Daily Living Activities Data Set” show that the proposed method can distinguish different types of fall postures and achieve 99% classification accuracy.Show less >
Language :
Anglais
Peer reviewed article :
Oui
Audience :
Internationale
Popular science :
Non
Administrative institution(s) :
Université de Lille
ENSAIT
Junia HEI
ENSAIT
Junia HEI
Collections :
Submission date :
2023-06-20T11:48:11Z
2024-03-21T09:11:40Z
2024-03-21T09:11:40Z
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