Single lead electroencephalogram sleep automatic staging method based on Stacking

A single-lead, sleep technology, applied in medical science, sensors, diagnostic recording/measurement, etc., can solve problems such as lack of unity, and achieve the effect of improving the signal-to-noise ratio

Pending Publication Date: 2018-11-06
CHONGQING UNIV OF POSTS & TELECOMM
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AI Technical Summary

Problems solved by technology

At present, there is no unified principle for the selection of feature parameters when the signal is a sleep EEG signal

Method used

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  • Single lead electroencephalogram sleep automatic staging method based on Stacking
  • Single lead electroencephalogram sleep automatic staging method based on Stacking
  • Single lead electroencephalogram sleep automatic staging method based on Stacking

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Embodiment Construction

[0044] The preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0045] figure 1 It is the main flowchart of the present invention, the technical problem solved:

[0046] (1) Preprocessing of EEG signals

[0047] EEG signals are characterized by high randomness, high imbalance, and high nonlinearity. The noise reduction processing of EEG signals is the key to EEG signal processing. It is necessary to compare the traditional Butterworth filter with the current popular wavelet noise reduction algorithm, and at the same time compare different wavelet basis functions, wavelet threshold functions, wavelet layers, and wavelet threshold values. A new EEG noise reduction algorithm suitable for sleep was developed.

[0048] The filtering method combined with the wavelet function and the IIR filtering function of the adaptive threshold is used to reduce the noise of the EEG signal and effectively improve the si...

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Abstract

The invention relates to a single lead electroencephalogram sleep automatic staging method based on Stacking, and belongs to the field of machine learning algorithms. The method comprises the steps that S1: sleep electroencephalograms are preprocessed; S2: multi-feature extraction and screening are carried out on the sleep electroencephalograms; S3: machine learning classification is carried out;S4: sleep automatic staging is carried out. The method can acquire a filtering method combining a wavelet function of a self-adaption threshold value and an IIR filtering function to conduct noise reduction processing on the electroencephalograms and effectively improve the signal to noise ratio of the electroencephalograms; a feature algorithm can be optimized and screened to acquire a new feature parameter set so as to take the new feature parameter set as a feature of sleep staging; a new multi-feature and integrated learning algorithm composition with high accuracy can be acquired and taken as the sleep staging method.

Description

technical field [0001] The invention belongs to the field of machine learning algorithms, and relates to an automatic staging method based on Stacking single-lead EEG sleep. Background technique [0002] Sleep research is of great significance to people's physical and mental health and daily work. Sleep staging is the key to understanding sleep status and sleep quality evaluation, and the sleep score based on sleep staging is also the most important diagnostic method in psychiatry and neurology. [0003] Rechtschaffen and Kates proposed R&K staging based on factors such as changes in eye movement and muscle tension in EEG (Eletroencephalogram, EEG), electrooculogram (EOG), and electromyography (EMG) during human sleep. According to the standard, sleep is divided into wakefulness, non-rapid eye movement sleep (NREM) and rapid eye movement sleep (REM), of which NREM can be divided into sleep stage I, sleep stage II, sleep stage III and sleep stage IV . In 2007, the AASM Ass...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): A61B5/00A61B5/04A61B5/0476
CPCA61B5/4812A61B5/316A61B5/369
Inventor 王强强赵德春王怡李舒粤
Owner CHONGQING UNIV OF POSTS & TELECOMM
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