首先，神经网络算法被利用实验获取的睡眠分期标签而设计出。随后，HRV和

First of all, the neural network algorithm is designed using the sleep staging labels obtained from experiments. Subsequently, HRV and body movement feature values ​​are extracted according to the central shock signal and body movement signal of the sleep process, and the network training is combined with genetic algorithm. Finally, the trained network is used to stage sleep and compare with actual detection results.

First, neural network algorithms are designed using experimental sleep stage labels. Subsequently, HRV and motion characteristic values are extracted according to the shock signal and movement signal of the sleep process center, and network training is combined with genetic algorithms. Finally, well-trained networks are used to stage sleep and compare it with actual test results.

First of all, the neural network algorithm is designed by using the sleep stage tags obtained from experiments. Then, HRV and body motion eigenvalues are extracted according to the central shock signal and body motion signal during sleep process, and the network training is combined with genetic algorithm. Finally, the trained network is used to stage sleep and compare with the actual detection results.<br>