EEG Signal Processing Techniques and Applications
Electroencephalography (EEG) is a well-established non-invasive tool used to record brain electrophysiological activity. It is economical, portable, easy to administer, and widely available in most hospitals. Compared with other neuroimaging techniques that provide information about the anatomical s...
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| Jazyk: | angličtina |
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MDPI - Multidisciplinary Digital Publishing Institute
2025
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| On-line přístup: | ONIX_20250812T110751_9783725836079_95 |
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| collection | Directory of Open Access Books |
| description | Electroencephalography (EEG) is a well-established non-invasive tool used to record brain electrophysiological activity. It is economical, portable, easy to administer, and widely available in most hospitals. Compared with other neuroimaging techniques that provide information about the anatomical structure (e.g., MRI, CT, and fMRI), EEG offers ultra-high time resolution, which is critical in understanding brain function. Empirical interpretation of EEG is largely based on recognizing abnormal frequencies in specific biological states, the spatial–temporal and morphological characteristics of paroxysmal or persistent discharges, reactivity to external stimuli and activation procedures, or intermittent photic stimulation. Despite being useful in many instances, these practical approaches to interpreting EEGs can leave important dynamic and nonlinear interactions between various brain network anatomical constituents undetected within the recordings, as such interactions are far beyond the observational capabilities of any specially trained physician in this field. This reprint provides a collection of original high-quality research in EEG signal pre-processing, modelling, analysis, and applications in the time, space, frequency, or time–frequency domains, particularly in applications of artificial intelligence and machine learning approaches. |
| format | Online |
| id | doab-20.500.12854ir-165339 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2025 |
| publishDateRange | 2025 |
| publishDateSort | 2025 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-1653392025-08-12T09:22:30Z EEG Signal Processing Techniques and Applications Zhao, Yifan He, Fei Guo, Yuzhu electroencephalography EEG signal processing brain connectivity EEG data analysis machine learning thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology Electroencephalography (EEG) is a well-established non-invasive tool used to record brain electrophysiological activity. It is economical, portable, easy to administer, and widely available in most hospitals. Compared with other neuroimaging techniques that provide information about the anatomical structure (e.g., MRI, CT, and fMRI), EEG offers ultra-high time resolution, which is critical in understanding brain function. Empirical interpretation of EEG is largely based on recognizing abnormal frequencies in specific biological states, the spatial–temporal and morphological characteristics of paroxysmal or persistent discharges, reactivity to external stimuli and activation procedures, or intermittent photic stimulation. Despite being useful in many instances, these practical approaches to interpreting EEGs can leave important dynamic and nonlinear interactions between various brain network anatomical constituents undetected within the recordings, as such interactions are far beyond the observational capabilities of any specially trained physician in this field. This reprint provides a collection of original high-quality research in EEG signal pre-processing, modelling, analysis, and applications in the time, space, frequency, or time–frequency domains, particularly in applications of artificial intelligence and machine learning approaches. 2025-08-12T09:22:28Z 2025-08-12T09:22:28Z 2025 book ONIX_20250812T110751_9783725836079_95 9783725836079 9783725836086 https://directory.doabooks.org/handle/20.500.12854/165339 eng image/jpeg Attribution 4.0 International https://mdpi.com/books https://mdpi.com/books/pdfview/book/10908 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-7258-3608-6 10.3390/books978-3-7258-3608-6 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783725836079 9783725836086 372 open access |
| spellingShingle | electroencephalography EEG signal processing brain connectivity EEG data analysis machine learning thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology EEG Signal Processing Techniques and Applications |
| title | EEG Signal Processing Techniques and Applications |
| title_full | EEG Signal Processing Techniques and Applications |
| title_fullStr | EEG Signal Processing Techniques and Applications |
| title_full_unstemmed | EEG Signal Processing Techniques and Applications |
| title_short | EEG Signal Processing Techniques and Applications |
| title_sort | eeg signal processing techniques and applications |
| topic | electroencephalography EEG signal processing brain connectivity EEG data analysis machine learning thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology |
| topic_facet | electroencephalography EEG signal processing brain connectivity EEG data analysis machine learning thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology |
| url | ONIX_20250812T110751_9783725836079_95 |