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An Adaptive Method for Detecting and Removing EEG Noise / 中国医疗器械杂志
Chinese Journal of Medical Instrumentation ; (6): 248-253, 2022.
Article in Chinese | WPRIM | ID: wpr-928898
ABSTRACT
To solve the problem of real-time detection and removal of EEG signal noise in anesthesia depth monitoring, we proposed an adaptive EEG signal noise detection and removal method. This method uses discrete wavelet transform to extract the low-frequency energy and high-frequency energy of a segment of EEG signals, and sets two sets of thresholds for the low-frequency band and high-frequency band of the EEG signal. These two sets of thresholds can be updated adaptively according to the energy situation of the most recent EEG signal. Finally, we judge the level of signal interference according to the range of low-frequency energy and high-frequency energy, and perform corresponding denoising processing. The results show that the method can more accurately detect and remove the noise interference in the EEG signal, and improve the stability of the calculated characteristic parameters.
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Full text: Available Index: WPRIM (Western Pacific) Main subject: Algorithms / Signal Processing, Computer-Assisted / Electroencephalography / Wavelet Analysis / Signal-To-Noise Ratio Language: Chinese Journal: Chinese Journal of Medical Instrumentation Year: 2022 Type: Article

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Full text: Available Index: WPRIM (Western Pacific) Main subject: Algorithms / Signal Processing, Computer-Assisted / Electroencephalography / Wavelet Analysis / Signal-To-Noise Ratio Language: Chinese Journal: Chinese Journal of Medical Instrumentation Year: 2022 Type: Article