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高级生物电信号处理方法：过去、现在和未来方法-第二部分：脑信号。

Advanced Bioelectrical Signal Processing Methods: Past, Present and Future Approach-Part II: Brain Signals.

机构信息

Department of Cybernetics and Biomedical Engineering, VSB-Technical University Ostrava-FEECS, 708 00 Ostrava-Poruba, Czech Republic.

College of Engineering, The University of Texas in Arlington, Arlington, TX 76019, USA.

出版信息

Sensors (Basel). 2021 Sep 23;21(19):6343. doi: 10.3390/s21196343.

DOI:10.3390/s21196343
PMID:34640663
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8512967/
Abstract

As it was mentioned in the previous part of this work (Part I)-the advanced signal processing methods are one of the quickest and the most dynamically developing scientific areas of biomedical engineering with their increasing usage in current clinical practice. In this paper, which is a Part II work-various innovative methods for the analysis of brain bioelectrical signals were presented and compared. It also describes both classical and advanced approaches for noise contamination removal such as among the others digital adaptive and non-adaptive filtering, signal decomposition methods based on blind source separation, and wavelet transform.

摘要

如本工作的上一部分（第一部分）所述——先进的信号处理方法是生物医学工程中发展最快、最具活力的科学领域之一，其在当前临床实践中的应用日益广泛。在本文的第二部分，介绍了各种用于分析脑生物电信号的创新方法并对其进行了比较。此外，还描述了经典和先进的去噪方法，如数字自适应和非自适应滤波、基于盲源分离的信号分解方法以及小波变换等。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6046/8512967/b556fd010ffb/sensors-21-06343-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6046/8512967/247d937b5000/sensors-21-06343-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6046/8512967/9085cdf625dc/sensors-21-06343-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6046/8512967/d9618e0b21bf/sensors-21-06343-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6046/8512967/7c14f1c19002/sensors-21-06343-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6046/8512967/75b20b5bcd45/sensors-21-06343-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6046/8512967/299c68737281/sensors-21-06343-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6046/8512967/6695344bbec9/sensors-21-06343-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6046/8512967/37733725a251/sensors-21-06343-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6046/8512967/b556fd010ffb/sensors-21-06343-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6046/8512967/247d937b5000/sensors-21-06343-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6046/8512967/9085cdf625dc/sensors-21-06343-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6046/8512967/d9618e0b21bf/sensors-21-06343-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6046/8512967/7c14f1c19002/sensors-21-06343-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6046/8512967/75b20b5bcd45/sensors-21-06343-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6046/8512967/299c68737281/sensors-21-06343-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6046/8512967/6695344bbec9/sensors-21-06343-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6046/8512967/37733725a251/sensors-21-06343-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6046/8512967/b556fd010ffb/sensors-21-06343-g009.jpg

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