基于RBF神经网络的睡眠分期方法研究与应用

Research and Application of Sleep Staging Method Based on RBF Neural Network

中文关键词: 睡眠分期  心率变异性  小波变换  径向基函数神经网络  智能唤醒

英文关键词: sleep staging  heart rate variability  wavelet transform  radial basis function neural network  intelligent wake-up

中文摘要:

      目的 提出一种基于径向基函数(Radial Basis Function，RBF)神经网络的睡眠分期方法，设计一套能够根据用户身心恢复状态调节唤醒时间的智能唤醒系统，以优化用户睡眠时长，减轻醒后不适感。方法 基于心率变异性和睡眠分期等相关理论知识，通过低功耗心率带采集人体心电信号，选取最优小波变换对采集到的心电信号精准去噪，对径向基函数神经网络进行反复训练后，筛选出10个关键的特征向量，以构建睡眠分期模型。睡眠分期信息通过STM32处理器传输到手机客户端，系统根据预先设计的优化唤醒机制在用户身心恢复到最佳状态时将其唤醒。结果 基于睡眠分期模型的算法平均识别准确率可达88.9%，卡帕(Kappa)系数为0.839，相较于其他算法，该算法具有较高的准确率。结论 该智能唤醒系统的采集成本较低，算法简便高效，其唤醒机制科学合理，可以使用户舒适醒来，对改善用户醒后状态具有重要意义。

英文摘要:

      The work aims to propose a sleep staging method based on a radial basis function (RBF) neural network and use it to design an intelligent wake-up system that can adjust the wake-up time according to the user's recovery state, in order to optimize the user's sleep duration and reduce their discomfort after waking up. Based on theoretical knowledge of heart rate variability and sleep staging, the electrocardiogram (ECG) signal was collected from the human body through a low-power heart rate band, and the optimal wavelet transform was selected to precisely denoise the collected ECG signal. The radial basis function (RBF) neural network was trained repeatedly to filter out 10 key feature vectors, so as to build a model of sleep staging. The sleep staging information was transmitted to the mobile phone client via a STM32 processor, and the system woke up the user according to designed optimized wake-up mechanism when the user's body and mind recovered to the optimal state. The results showed that the algorithm based on the sleep staging model had an average accuracy of 88.9% with a Kappa coefficient of 0.839, which was higher than that of other algorithms. The intelligent wake-up system has a lower collection cost, a simpler and more efficient algorithm, and a scientific and reasonable wake-up mechanism, which enables the user to wake up comfortably and is of great significance in improving the user's state after awakening.