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Heart Rate Prediction Model Based on Physical Activities Using Evolutionary Neural Network

机译:基于体育活动的进化神经网络心率预测模型

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Physical activity (PA) can influence heart rate(HR). But the relationship between HR and PA is hard to describe. In our previous works, HR prediction models based on PA were designed. However, the prediction time length and accuracy are usually hard to compromise. In this study, a new HR prediction method is proposed. The predicted HR is used as the input in the next prediction step. Only HR at the initial time step and PA signals are needed in a long prediction time length. Evolutionary neural network is used as the mathematic basic of the predictor to ensure the prediction accuracy. The results show the predicted HR can trace the actual HR well.
机译:体力活动(PA)会影响心率(HR)。但是,HR和PA之间的关系很难描述。在我们以前的工作中,设计了基于PA的人力资源预测模型。但是,预测时间长度和准确性通常很难妥协。在这项研究中,提出了一种新的人力资源预测方法。预测的HR用作下一个预测步骤的输入。在较长的预测时间长度内,仅需要初始时间步长的HR和PA信号。进化神经网络被用作预测器的数学基础,以确保预测的准确性。结果表明,预测的HR可以很好地跟踪实际HR。

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