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Method for automatically identifying and extracting K complex waves in sleep brain waves

A K-complex wave and automatic recognition technology, applied in the field of EEG signals, can solve problems such as algorithm versatility, poor robustness, K-complex wave recognition error, poor detection effect, etc., and achieve simple algorithm and strong anti-interference ability Effect

Active Publication Date: 2014-10-01
XI AN JIAOTONG UNIV
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Problems solved by technology

[0005] However, because the Teager energy operator is a method suitable for single-component signal analysis, it is easily affected by noise and interference; and digital filtering technology cannot completely remove low-frequency noise and interference, resulting in the combination of filtering and energy operator The method has a large error in the identification of the K complex wave in the clinical actual signal, which eventually leads to poor overall detection effect, and the generality and robustness of the algorithm are poor.

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  • Method for automatically identifying and extracting K complex waves in sleep brain waves
  • Method for automatically identifying and extracting K complex waves in sleep brain waves
  • Method for automatically identifying and extracting K complex waves in sleep brain waves

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Embodiment Construction

[0030] The present invention will be further described below in conjunction with the accompanying drawings.

[0031] A method for automatically identifying and extracting K-complex waves in sleep EEG, the specific implementation steps of which can be referred to figure 1 :

[0032] Step 1. Read the sleep EEG and segment it. Since the sleep stage generally takes 30s as a period, the segment length is 30s. According to the frequency domain characteristics of the K complex wave: its frequency is generally 0.5-2Hz, Therefore, the db5 wavelet is selected for the eight-layer wavelet decomposition, and the low-frequency coefficients of the seventh and eighth layers are selected for reconstruction. figure 2 It is the original signal and the wavelet reconstructed signal.

[0033] Step 2. The amplitude of the K complex wave is very large, generally between 100-400v, so calculate the absolute value of the difference between the maximum value and the minimum value of the reconstructed ...

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Abstract

A method for automatically identifying and extracting K complex waves in sleep brain waves comprises the following steps of performing wavelet decomposition and reconstruction on brain wave signals; performing Teager energy operator calculation on reconstructed data and obtaining absolute values; smoothing and performing 0 / 1 coarse graining on an obtained Teager energy curve; performing threshold detection on the data which is performed on coarse graining; performing morphology detection on reconstructed signals satisfying the threshold values, enabling the signals at positions which satisfying a morphology condition to be the K complex waves and recording starting and final positions and wave crest and wave trough values and positions. The method for automatically identifying and extracting the K complex waves in the sleep brain waves has the advantages of analyzing the signals which is performed on the wavelet decomposition and the reconstruction through the Teager energy operator, extracting an absolute value sequence of the Teager energy operator and performing smoothness and coarse graining processes, being easy to achieve and high in anti-noise capacity, accurately confirming K complex wave positions and the wave crest and trough values and positions and establishing foundation for identification of a non-rem second period in sleep stage and research of the K complex waves.

Description

technical field [0001] The invention relates to the technical field of EEG signals, in particular to a method for automatically identifying and extracting K-complex waves in sleep EEG. Background technique [0002] Sufficient sleep is the three health standards recognized by the international community, but with the advancement of science and technology, the acceleration of the pace of life and the increasing pressure from all aspects, more and more human beings are suffering from various sleep-related diseases , such as: insomnia, lethargy, etc. The decline in sleep quality not only affects people's physical health but also endangers people's mental health, because the decline in sleep quality is often accompanied by the occurrence of some mental diseases, such as: anxiety, depression, chronic pain, fear of insomnia and other symptoms. In addition to mental diseases, the relationship between other diseases and sleep has also been extensively studied. Through the detection ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): A61B5/0452
Inventor 徐进魏妍吴舒婷
Owner XI AN JIAOTONG UNIV
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