Method for extracting and fusing time, frequency and space domain multi-parameter electroencephalogram characters

A technology of feature extraction and fusion method, which is applied in medical science, sensors, diagnostic recording/measurement, etc., and can solve the problems that the fused feature information cannot be fully utilized, and multi-domain feature information cannot be fully extracted and effectively selected.

Active Publication Date: 2015-05-06
秦皇岛市惠斯安普医学系统股份有限公司 +1
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Problems solved by technology

[0008] Aiming at the above problems, the present invention designs a time, frequency, and spatial multi-parameter EEG feature extraction and fusion method, which can effectively solve the pro

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  • Method for extracting and fusing time, frequency and space domain multi-parameter electroencephalogram characters
  • Method for extracting and fusing time, frequency and space domain multi-parameter electroencephalogram characters
  • Method for extracting and fusing time, frequency and space domain multi-parameter electroencephalogram characters

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Embodiment Construction

[0024] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.

[0025] The first step: EEG signal acquisition

[0026] The EEG signal acquisition equipment uses two ADS1299 cascades, and the two ADS1299s can be connected in a daisy chain to realize a 16-conductor amplifier. The electrodes were placed according to the international standard lead 10-20 electrode system, and 16 leads (Fp1, Fp2, F3, F4, C3, C4, P3, P4, O1, O2, F7, F8, T3, T4, T5, T6) Scalp EEG signal, Cz as the reference electrode, the forehead as the reference ground, and the sampling rate is 250Hz. Very low input reference noise: 1.0uVPP (70Hz BW ), the common mode rejection ratio is -110dB. The resting state EEG was collected for 10 minutes, and the collection environment was the same as the conventional EEG collection environment.

[0027] Step 2: EEG data preprocessing

[0028] (1) After the EEG signal is stable, the EEG signal is inte...

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Abstract

The invention relates to a method for extracting and fusing time, frequency and space domain multi-parameter electroencephalogram characters, which comprises the following steps: 1) collecting an electroencephalogram signal; 2) performing data pre-processing on the electroencephalogram signal; 3) extracting Kc complexity, approximate entropy and wavelet entropy from the pre-processed data; 4) on the basis of AMUSE algorithm, acquiring an electroencephalogram singular value decomposition matrix parameter; 5) performing character selection on the time, frequency and space domain character parameters for the extracted Kc complexity, approximate entropy, wavelet entropy and electroencephalogram singular value decomposition matrix parameters; 6) utilizing a SVM classifier to fuse and classify the four parameters of the time, frequency and space domains after the character selection. According to the method provided by the invention, the Kc complexity, the approximate entropy, the wavelet entropy and the electroencephalogram singular value decomposition matrix parameter can be selected for comprehensively presenting electroencephalogram character information, and then subsequent effective fusion is performed, so that effective support and help can be supplied to early diagnosis assessment for the brain functional disordered diseases, such as, Alzheimer disease, mild cognitive impairment, and the like.

Description

technical field [0001] The invention belongs to the technical field of EEG signal feature extraction and fusion, in particular to a method for time, frequency, and spatial multi-parameter EEG feature extraction and fusion. Background technique [0002] EEG can comprehensively reflect the overall effect and functional state of the electrophysiological activities of the brain nervous system. Among the many detection and evaluation methods for cognitive impairment, the evaluation method based on EEG signal features is more and more widely used in cognitive impairment due to its unique advantages of non-invasiveness, high temporal resolution, and emphasis on temporal information transmission and processing. know the field of research. As a special bioelectrical signal, EEG signal contains rich physiological and pathological information, which provides an effective means for the diagnosis of clinical brain diseases, especially early diagnosis. [0003] In the EEG signal analysi...

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Application Information

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IPC IPC(8): A61B5/0476
CPCA61B5/4088A61B5/7264A61B5/316A61B5/369
Inventor 侯永捷李昕
Owner 秦皇岛市惠斯安普医学系统股份有限公司
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