Method for detecting EEG (electroencephalogram) alertness based on continuous wavelet transform

An EEG signal and wavelet transform technology, applied in the field of signal processing, can solve problems such as insufficient extraction of subtle changes in EEG rhythm activity, achieving high accuracy and reducing computing time.

Inactive Publication Date: 2011-05-18
SHANGHAI JIAO TONG UNIV
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Problems solved by technology

Some studies are based on synchronous brain-computer interface experiments, which require subjects to complete some specified actions or tasks within a specified period of time. However, when the brain-computer interface experiment is asynchronous, or even

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Embodiment Construction

[0019] The embodiments of the present invention are described in detail below. This embodiment is implemented on the premise of the technical solution of the present invention, and detailed implementation methods and specific operating procedures are provided, but the protection scope of the present invention is not limited to the following implementation example.

[0020] This embodiment includes the following steps:

[0021] In the first step, a 64-conductor EEG signal sequence with a sampling rate of 100 was manually observed, and the 4-lead electrode signals that were severely damaged by interference were first removed, and several time periods mixed with artifacts were removed. After being filtered by a finite impulse response filter with a bandwidth of 1Hz-40Hz, the EEG signal is a 60*T matrix, where T is the number of remaining time points of the EEG signal;

[0022] In the second step, the EEG signal sequence is divided into several segments with a length of 5 seconds...

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Abstract

The invention relates to a method for detecting the EEG (electroencephalogram) alertness based on continuous wavelet transform in the technical field of signal processing, which comprises the following steps of: obtaining characteristic values of wavelet coefficients of EEG (electroencephalogram) sequences as a characteristic set by using a wavelet function; and sorting and simplifying the characteristic set through a random forest method, training a support vector machine by using a sample, and detecting the EEG (electroencephalogram) alertness by using the support vector machine obtained by training. The method for detecting the EEG (electroencephalogram) alertness based on the continuous wavelet transform realizes the processing and the analysis of EEG (electroencephalogram) to distinguish different alertness levels of people through the continuous wavelet transform processing of the EEG (electroencephalogram), calculation and characteristic extraction based on wavelet coefficients, characteristic sorting and selection based on a random forest, and the training and the classification of the support vector machine.

Description

technical field [0001] The invention relates to a method in the technical field of signal processing, in particular to an electroencephalogram signal (EEG) processing and alertness analysis method based on continuous wavelet transform. Background technique [0002] Vigilance refers to the level of attention or vigilance of a person when performing a task. In daily life, there are many jobs that require staff to maintain a high degree of alertness, such as drivers, pilots, etc. For the staff, a drop in alertness is likely to lead to very serious consequences. However, past research has shown that it is nearly impossible for workers to maintain a high level of alertness for extended periods of time in tasks such as those described above. Therefore, how to conduct quantitative, accurate and real-time analysis of human alertness has become an urgent problem to be solved, and using machines and automated methods or equipment to achieve this goal is an important route to solve th...

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Application Information

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IPC IPC(8): A61B5/16A61B5/00A61B5/0476
Inventor 欧阳甜卢宏涛任庆生
Owner SHANGHAI JIAO TONG UNIV
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