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A back-propagation neural network model for prediction of loss of balance

机译:用于预测平衡损失的后传播神经网络模型

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Two neural network models were developed for the prediction of postural sway response due to exposure to risk factors including environmental lighting, job-tasks, standing surface firmness, surface oiliness, work load, peripheral vision conditions, age and gender. Variables used to measure the loss of balance were index of proximity to stability boundary and sway length. Tests showed that job-task is the main risk factor that changes the output while there is some impact by age or gender on the outcome of the model. The results from these models can be used to find risk factors that have great impact on loss of balance and therefore can help in designing intervention programs.
机译:由于暴露于危险因素,包括环境照明,工作任务,站立表面固件,表面含油,工作负荷,外周视觉条件,年龄和性别,因此开发了两个神经网络模型的姿势摇摆反应预测。用于测量平衡损失的变量是对稳定边界和摇摆长度的接近索引。测试表明,工作任务是改变输出的主要风险因素,而在模型的结果上受到年龄或性别的影响。这些模型的结果可用于找到对余额损失产生很大影响的风险因素,因此可以帮助设计干预计划。

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