EEG signal preprocessing method and system in sleep state analysis

Abstract

The invention relates to a method and a system for electroencephalogram signal preprocessing in sleep state analysis. The method comprises the steps of collecting original electroencephalogram signals generated by a user in a sleep process; according to a preset median filtering window length, performing median filtering on the original electroencephalogram signals to filter baseline drift; performing self-adaptive adjustment on the median filtering window length according to the post-filtering electroencephalogram signal frequencies and amplitudes until the energy in a set frequency band of the filtered electroencephalogram signals subjected to wavelet decomposition is maximal and the absolute value of the mean value of the electroencephalogram signal amplitudes is minimal; outputting the electroencephalogram signals with the baseline drift filtered. According to the invention, on the basis that baseline drift is filtered through median filtering and useful information of electroencephalogram signals is retained, through self-adaptive adjustment of median filtering window length, the post-filtering signal frequency can better meet the clinical requirements and the mean value is minimal, so that the type of electroencephalogram signals can be judged accurately.

Description

technical field [0001] The invention relates to the technical field of sleep aids, in particular to a method and system for preprocessing EEG signals in sleep state analysis. Background technique [0002] During sleep, the human body undergoes a process of self-relaxation and recovery, so good sleep is a basic condition for maintaining good health; however, due to work pressure, irregular life schedule and other reasons, some people have poor sleep quality , manifested as insomnia, waking up in the middle of the night, etc. [0003] There are already some devices on the market to help people fall asleep and improve the quality of sleep. For example, in a specific sleep state, manual intervention such as sound and light signals can be used to avoid waking up the user in a deep sleep state. For devices that assist sleep, in order to really achieve the purpose of improving the user's sleep quality, it is very important to correctly identify the user's sleep state. [0004] T...

AI Technical Summary

Problems solved by technology

However, the detrending / de-meaning method has no obvious effect on the processing of EEG signals; the frequency domain-based method, because the frequency of the baseline is usually very low and overlaps with the frequency band of the EEG, the processed signal is prone to appear Distortion, does not meet clinical needs

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