Design and Implementation of Machine Learning-based Assisted Sleep System

摘要：

　　With the acceleration of the rhythm of life in todays society,peoples life pressure is increasing day by day,and the quality of sleep is also getting lower and lower.In order to help people improve sleep quality effectively,an assistant sleep system based on machine learning is designed.The system consists of three parts: wearing terminal,cloud platform and APP.The wearing terminal collects EEG signal and assists the sleep of the users; the cloud platform runs the EEG processing algorithm based on wavelet transform and the sleep staging algorithm based on convolutional neural network to get the real-time sleep state; APP performs user feature information input,wake-up time setting and sleep status checking.This design combines signal processing algorithm and machine learning to realize an intelligent and effective assistant sleep system.The experimental results show that the system has high.accuracy for sleep staging of users.

关键词： Signal and information processing EEG signal Wavelet transform Convolutional neural network Assisted sleep Sleep staging

作者: Jianhao Yang Yike Xu Shaocong Guo Huawei Zhang Shiyuan Liu Fanfan Zheng

作者单位: School of Information Engineering,Electronic Information Engineering,Wuhan University of Technology, School of Information Engineering,Wuhan University of Technology,Wuhan City,Hubei Province,430000 School of Safety Science and Emergency Management,Department of Public Safety and Emergency Manageme

会议类型: 国际会议

会议名称: 2019年第二届智能系统研究与机电工程国际会议(ISRME 2019) 2019 2nd International Conference on Intelligent Systems Research and Mechatronics Engineering

会议地点: 太原

会议语种:英文

页码: 36-42

在线出版日期: 2019-06-29（万方平台首次上网日期，不代表论文的发表时间）