Fall Detection Algorithm of the Elderly Based on BP Neural Network

被引：0
|
作者：
Xiong, Qiushi [1 ]
Chen, Danhong [1 ]
Zhang, Ying [1 ]
Gong, Zhen [1 ]
机构：
[1] Shenyang Aerosp Univ, Coll Econ & Management, Shenyang 110136, Peoples R China
来源：
PROCEEDINGS OF THE 33RD CHINESE CONTROL AND DECISION CONFERENCE (CCDC 2021) | 2021年
关键词：
Fall detection; BP neural network; Acceleration sensor; The elderly;
D O I：
10.1109/CCDC52312.2021.9602683
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
With the rapid development of population aging, falling is a very serious problem for the elderly. Real-time detection of whether the elderly has fallen can minimize the damage caused by falling. Therefore, this paper proposes a fall detection method based on BP neural network. The algorithm uses a three-layer BP reverse neural network to collect human motion data by wearing a three-axis acceleration sensor (MMA7660FC). After feature extraction of the data, network training is carried out, and the neuron weight and learning rate are adjusted to the training process so that it can realize the function of fall detection. Experimental results show that the algorithm can identify falls well, and its accuracy rate can reach 99.44%.
引用
收藏
页码：7505 / 7508
页数：4
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