Construction of intelligent fall warning model for the elderly based on plantar pressure
10.3760/cma.j.cn211501-20230105-00035
- VernacularTitle:基于足底压力的老年人跌倒智能预警模型的构建
- Author:
Xin LIU
1
;
Haozhe ZHANG
;
Yongqin HE
;
Wenhua GU
;
Yumei ZHANG
Author Information
1. 中国人民解放军陆军军医大学第二附属医院骨科，重庆 400037
- Keywords:
Accidental falls;
Primary prevention;
Deep learning;
Early warning model
- From:
Chinese Journal of Practical Nursing
2023;39(29):2251-2256
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To realize the accurate prediction of the fall risk of the elderly by a convolutional neural network prediction model.Methods:Stratified random cluster sampling was used from June 2019 to February 2020, Python′s Matlabplot library and Opencv library were used to perform data preprocessing on the plantar pressure data of 1 093 subjects who had come from medical institutionsand community or elderly care institutions of Chongqing and Nanjing, such as data visualization, compression and clipping, grayscale, Gaussian blur, etc., and then the data were divided into training set (983 cases) and verification set (110 cases), the training set data were used to train the convolutional neural network model, the verification set was used to verify the model, and the ReLU function was used to suppress overfitting to obtain the final prediction model.Results:The sensitivity of the fall warning model to the validation set for predicting falls was 91.2%, the specificity was 81.4%, the accuracy was 91.5%, and the AUC was 0.865.Conclusions:The fall prediction model can predict the fall risk of the elderly in a specific scenario. In the subsequent improvement, the software and hardware construction should be comprehensively improved to further improve the prediction accuracy.
