An Ubiquitous Sleep Quality Monitoring and Evaluation

In this paper, we propose a distance monitoring and evaluation model for sleep quality, which allows a doctor to be able to know users' sleep status of all night from their own home. The model focuses on a sleep-staging program running on an internet-based sleep-staging program running automatically on a remote server, in which we use the method of combining linear and non-linear parameters to extract feature from sleep EEG signals in the calculating modules and classify each 30 sleep fragments as different sleep stages by supervised learning in a BP neutral network in the classifying module. Our experiment shows that the sleep quality monitoring and evaluation scheme is effective.

並列關鍵字

Sleep stages ； EEG signal ； Feature extraction ； BP neural network

國際替代計量

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