Supervising-type stage identification method by using mixed sleep electroencephalogram signals and electrooculogram signals

A technology of sleep staging and mixed signals, applied in medical science, sensors, diagnostic recording/measurement, etc., can solve problems such as low sleep staging recognition rate, epoch misreading, and epoch characteristic parameters are not obvious, and achieve high sleep staging recognition rate , the effect of improving utilization efficiency

Active Publication Date: 2017-11-21
浙江纽若思医疗科技有限公司
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Problems solved by technology

[0003] In the existing sleep stage interpretation method, the recording of the epoch of the sleep EEG mixed signal segment is limited by the noise collected by the hardware equipment, which affects the sleep signal discrimination results, and the characteristic parameters of some epochs are not obvious, so the independent use o

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  • Supervising-type stage identification method by using mixed sleep electroencephalogram signals and electrooculogram signals
  • Supervising-type stage identification method by using mixed sleep electroencephalogram signals and electrooculogram signals
  • Supervising-type stage identification method by using mixed sleep electroencephalogram signals and electrooculogram signals

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Embodiment Construction

[0026] The core of the present invention is to provide a supervised sleep EEG and EOG mixed signal stage interpretation method, so as to improve the recognition rate of sleep stage.

[0027] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be described clearly and completely with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only It is a part of the embodiments of the present invention, not all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative work shall fall within the protection scope of the present invention.

[0028] The terms are explained as follows:

[0029] Sleep EEG and ocular signals: FP1FP2 lead EEG and ocular signals and muscle electrical signals with a sampling ra...

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Abstract

The invention discloses a supervising-type stage identification method by using mixed sleep electroencephalogram signals and electrooculogram signals. The supervising-type stage identification method includes: subjecting multiple epochs of the mixed sleep electroencephalogram signals and electrooculogram signals to stage marking; filtering the epochs to remove interferences, and subjecting the the filtered epochs to characteristic parameter extraction so as to obtain characteristic parameters; subjecting the characteristic parameters to statistical processing, and establishing a decision-making tree; acquiring unmarked overnight sleep signals, and identifying sleep stages according to the decision-making tree to obtain an intermediate sleep stage result; revising the intermediate sleep stage result to obtain a sleep stage result. The supervising-type stage identification method by using the mixed sleep electroencephalogram signals and electrooculogram signals is capable of increasing sleep stage identification rate.

Description

Technical field [0001] The present invention relates to the technical field of sleep staging and interpretation, and in particular to a supervised sleep EEG and mixed signal stage interpretation method. Background technique [0002] Currently, in the paper "Virkkala J, Velin R, Himanen SL, et al. Automatic sleepstage classification using two facial electrodes[J]. Conf Proc IEEE Eng MedBiol Soc, 2008, 2008: 1643-1646" the sleep stage interpretation method is adopted FP1 and FP2 lead EEG signals of EEG, without using EOG signal and mandibular muscle electrical EMG signal. The algorithm uses the differential signal of the FP1 and FP2 lead signals to perform FFT transformation to obtain the total energy of each frequency band, and obtain the total energy of delta frequency band, total energy of theta frequency band, total energy of alpha frequency band, total energy of sigma frequency band, and total energy of beta frequency band. Energy, total energy of muscle electric frequency ba...

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Application Information

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IPC IPC(8): A61B5/00A61B5/0476A61B5/0496
CPCA61B5/4812A61B5/7203A61B5/7235A61B5/7253A61B5/7257A61B5/316A61B5/369A61B5/398
Inventor 张铁军
Owner 浙江纽若思医疗科技有限公司
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