Application of Electroencephalography (EEG) Signal Analysis in Disease Diagnosis
Over the years, the development of several brain imaging techniques has provided new tools for capturing information about the structure and functions of the brain, which have proven useful in different fields, such as neurosurgery, neurology, and cognitive science. In particular, electroencephalogr...
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MDPI - Multidisciplinary Digital Publishing Institute
2025
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| Διαθέσιμο Online: | ONIX_20250220_9783725829118_486 |
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| description | Over the years, the development of several brain imaging techniques has provided new tools for capturing information about the structure and functions of the brain, which have proven useful in different fields, such as neurosurgery, neurology, and cognitive science. In particular, electroencephalography (EEG) has become a powerful instrument successfully employed in both clinical applications and cognitive neuroscience, since it is a non-invasive, easy-to-use, portable, and relatively low-cost tool. EEG is used for detecting and classifying a spectrum of neurological disorders, including epilepsy, sleep disorders, traumatic brain injuries, psychiatric conditions, and neurodegenerative diseases like Alzheimer's and Parkinson's. In summary, the processing and analyzing of EEG signals can be conveniently exploited to detect abnormalities in the case of a pathological state and improve the early diagnosis of brain diseases. This reprint contains studies regarding the application of EEG signal analysis in disease diagnosis, covering different processing methods and several neurological disorders (Parkinson’s disease, stroke, epilepsy, and sleep disorders). |
| format | Online |
| id | doab-20.500.12854ir-153122 |
| 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-1531222025-02-20T13:35:31Z Application of Electroencephalography (EEG) Signal Analysis in Disease Diagnosis Dattola, Serena La Foresta, Fabio EEG electroencephalography auditory feedback DIVA model feedback perturbation vocal compensation migraine luteal phase absolute power ERPs BCI Shadowing Tasks freezing of gait Parkinson&rsquo s disease voluntary stopping convolutional neural network EEGNet Shallow ConvNet Deep ConvNet carotid stenosis brain electrical activity postoperative cognitive dysfunction coronary artery bypass grafting carotid endarterectomy postoperative delirium spinal surgery wearable device emotions facial perception power spectral density coherence detrended moving average DMA Emotiv EPOC brainvision reliability accuracy arousal valence mental load consumer-grade EEG research-grade EEG stroke conduction aphasia high-density EEG brain functional connectivity rehabilitation diagnostics dual-tree complex wavelet transform (DTCWT) epilepsy LightGBM seizure type classification Alzheimer&rsquo s disease (AD) EEG signals power spectrum FIR filtering supervised machine learning fast Fourier transformation (FFT) phase synchronization acute stress disorder electroencephalogram (EEG) footshock information theory sleep epileptic seizure entropy spectral power random forest gradient-boosting decision tree support vector machine k-nearest neighbors quantitative electroencephalogram (qEEG) neurometrics neurology psychiatry disease health phenotype brain mind cognitive vulnerability depression self-referential processing emotion processing language event-related brain potentials thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues thema EDItEUR::M Medicine and Nursing::MJ Clinical and internal medicine::MJC Diseases and disorders::MJCL Oncology Over the years, the development of several brain imaging techniques has provided new tools for capturing information about the structure and functions of the brain, which have proven useful in different fields, such as neurosurgery, neurology, and cognitive science. In particular, electroencephalography (EEG) has become a powerful instrument successfully employed in both clinical applications and cognitive neuroscience, since it is a non-invasive, easy-to-use, portable, and relatively low-cost tool. EEG is used for detecting and classifying a spectrum of neurological disorders, including epilepsy, sleep disorders, traumatic brain injuries, psychiatric conditions, and neurodegenerative diseases like Alzheimer's and Parkinson's. In summary, the processing and analyzing of EEG signals can be conveniently exploited to detect abnormalities in the case of a pathological state and improve the early diagnosis of brain diseases. This reprint contains studies regarding the application of EEG signal analysis in disease diagnosis, covering different processing methods and several neurological disorders (Parkinson’s disease, stroke, epilepsy, and sleep disorders). 2025-02-20T13:35:28Z 2025-02-20T13:35:28Z 2024 book ONIX_20250220_9783725829118_486 9783725829118 9783725829125 https://directory.doabooks.org/handle/20.500.12854/153122 eng application/octet-stream Attribution 4.0 International https://mdpi.com/books/pdfview/book/10372 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-7258-2912-5 10.3390/books978-3-7258-2912-5 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783725829118 9783725829125 288 Basel open access |
| spellingShingle | EEG electroencephalography auditory feedback DIVA model feedback perturbation vocal compensation migraine luteal phase absolute power ERPs BCI Shadowing Tasks freezing of gait Parkinson&rsquo s disease voluntary stopping convolutional neural network EEGNet Shallow ConvNet Deep ConvNet carotid stenosis brain electrical activity postoperative cognitive dysfunction coronary artery bypass grafting carotid endarterectomy postoperative delirium spinal surgery wearable device emotions facial perception power spectral density coherence detrended moving average DMA Emotiv EPOC brainvision reliability accuracy arousal valence mental load consumer-grade EEG research-grade EEG stroke conduction aphasia high-density EEG brain functional connectivity rehabilitation diagnostics dual-tree complex wavelet transform (DTCWT) epilepsy LightGBM seizure type classification Alzheimer&rsquo s disease (AD) EEG signals power spectrum FIR filtering supervised machine learning fast Fourier transformation (FFT) phase synchronization acute stress disorder electroencephalogram (EEG) footshock information theory sleep epileptic seizure entropy spectral power random forest gradient-boosting decision tree support vector machine k-nearest neighbors quantitative electroencephalogram (qEEG) neurometrics neurology psychiatry disease health phenotype brain mind cognitive vulnerability depression self-referential processing emotion processing language event-related brain potentials thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues thema EDItEUR::M Medicine and Nursing::MJ Clinical and internal medicine::MJC Diseases and disorders::MJCL Oncology Application of Electroencephalography (EEG) Signal Analysis in Disease Diagnosis |
| title | Application of Electroencephalography (EEG) Signal Analysis in Disease Diagnosis |
| title_full | Application of Electroencephalography (EEG) Signal Analysis in Disease Diagnosis |
| title_fullStr | Application of Electroencephalography (EEG) Signal Analysis in Disease Diagnosis |
| title_full_unstemmed | Application of Electroencephalography (EEG) Signal Analysis in Disease Diagnosis |
| title_short | Application of Electroencephalography (EEG) Signal Analysis in Disease Diagnosis |
| title_sort | application of electroencephalography eeg signal analysis in disease diagnosis |
| topic | EEG electroencephalography auditory feedback DIVA model feedback perturbation vocal compensation migraine luteal phase absolute power ERPs BCI Shadowing Tasks freezing of gait Parkinson&rsquo s disease voluntary stopping convolutional neural network EEGNet Shallow ConvNet Deep ConvNet carotid stenosis brain electrical activity postoperative cognitive dysfunction coronary artery bypass grafting carotid endarterectomy postoperative delirium spinal surgery wearable device emotions facial perception power spectral density coherence detrended moving average DMA Emotiv EPOC brainvision reliability accuracy arousal valence mental load consumer-grade EEG research-grade EEG stroke conduction aphasia high-density EEG brain functional connectivity rehabilitation diagnostics dual-tree complex wavelet transform (DTCWT) epilepsy LightGBM seizure type classification Alzheimer&rsquo s disease (AD) EEG signals power spectrum FIR filtering supervised machine learning fast Fourier transformation (FFT) phase synchronization acute stress disorder electroencephalogram (EEG) footshock information theory sleep epileptic seizure entropy spectral power random forest gradient-boosting decision tree support vector machine k-nearest neighbors quantitative electroencephalogram (qEEG) neurometrics neurology psychiatry disease health phenotype brain mind cognitive vulnerability depression self-referential processing emotion processing language event-related brain potentials thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues thema EDItEUR::M Medicine and Nursing::MJ Clinical and internal medicine::MJC Diseases and disorders::MJCL Oncology |
| topic_facet | EEG electroencephalography auditory feedback DIVA model feedback perturbation vocal compensation migraine luteal phase absolute power ERPs BCI Shadowing Tasks freezing of gait Parkinson&rsquo s disease voluntary stopping convolutional neural network EEGNet Shallow ConvNet Deep ConvNet carotid stenosis brain electrical activity postoperative cognitive dysfunction coronary artery bypass grafting carotid endarterectomy postoperative delirium spinal surgery wearable device emotions facial perception power spectral density coherence detrended moving average DMA Emotiv EPOC brainvision reliability accuracy arousal valence mental load consumer-grade EEG research-grade EEG stroke conduction aphasia high-density EEG brain functional connectivity rehabilitation diagnostics dual-tree complex wavelet transform (DTCWT) epilepsy LightGBM seizure type classification Alzheimer&rsquo s disease (AD) EEG signals power spectrum FIR filtering supervised machine learning fast Fourier transformation (FFT) phase synchronization acute stress disorder electroencephalogram (EEG) footshock information theory sleep epileptic seizure entropy spectral power random forest gradient-boosting decision tree support vector machine k-nearest neighbors quantitative electroencephalogram (qEEG) neurometrics neurology psychiatry disease health phenotype brain mind cognitive vulnerability depression self-referential processing emotion processing language event-related brain potentials thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues thema EDItEUR::M Medicine and Nursing::MJ Clinical and internal medicine::MJC Diseases and disorders::MJCL Oncology |
| url | ONIX_20250220_9783725829118_486 |