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Sleep state detecting method and system based on single-channel EEG signals

A sleep state and detection method technology, applied in the field of deep learning, can solve the problems of low feature extraction, labor-intensive, weak generalization ability, etc., and achieve the effect of saving labor cost and time cost, high accuracy, and high feature dimension.

Active Publication Date: 2018-09-18
CHANGSHA UNIVERSITY
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Problems solved by technology

[0005] Aiming at the above defects or improvement needs of the prior art, the present invention provides a sleep state detection method and system based on a single-channel EEG signal. The resulting technical problems are labor-intensive, low-dimensional feature extraction, and weak generalization ability due to over-fitting

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  • Sleep state detecting method and system based on single-channel EEG signals
  • Sleep state detecting method and system based on single-channel EEG signals
  • Sleep state detecting method and system based on single-channel EEG signals

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[0034] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not constitute a conflict with each other.

[0035] like figure 1 As shown, the sleep state detection method based on the single-channel EEG signal of the present invention comprises the following steps:

[0036] (1) Collect single-channel EEG (Electroencephalograph, EEG for short) signals in real time, and perform down-sampling processing on the single-channel EEG signals;

[0037] Specifically, the EEG signal in this step is the Fpz-Cz...

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Abstract

The invention discloses a sleep state detecting method based on single-channel EEG signals. The method comprises the steps of collecting single-channel EEG signals in real time, performing downsampling processing on the single-channel EEG signals, and inputting the single-channel EEG signals obtained after downsampling processing to a classifier model to obtain the corresponding sleep state. The technical problems that according to an existing sleep state detecting method, by arranging multiple collecting electrodes, manpower is wasted, the extraction feature dimension is low, and the generalization is low due to over-fitting can be solved.

Description

technical field [0001] The invention belongs to the technical field of deep learning, and more specifically, relates to a sleep state detection method and system based on a single-channel electroencephalogram (Electroencephalograph, EEG for short). Background technique [0002] Sleep state detection technology has been widely used at present to monitor people's sleep state in real time. [0003] There are two main methods for existing sleep state detection methods. The first is to manually extract the frequency domain, time domain and statistical features of the multi-channel EEG signal for threshold discrimination, thereby obtaining the user's sleep state. The two-way convolutional neural network extracts features and inputs them to the Long Short-Term Memory (LSTM) network to obtain the sleep state. [0004] However, there are some defects in the above two sleep state detection methods: for the first method, the acquisition of multi-channel EEG signals needs to set up mul...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): A61B5/0476A61B5/00
CPCA61B5/4809A61B5/4812A61B5/4815A61B5/7267A61B5/369
Inventor 李方敏翁同峰刘新华旷海兰杨志邦栾悉道
Owner CHANGSHA UNIVERSITY
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