Intelligent Biosignal Analysis Methods
This book describes recent efforts in improving intelligent systems for automatic biosignal analysis. It focuses on machine learning and deep learning methods used for classification of different organism states and disorders based on biomedical signals such as EEG, ECG, HRV, and others.
Zapisane w:
| Format: | Online |
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| Język: | angielski |
| Wydane: |
MDPI - Multidisciplinary Digital Publishing Institute
2022
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| Hasła przedmiotowe: | |
| Dostęp online: | ONIX_20220111_9783036516929_488 |
| Etykiety: |
Nie ma etykietki, Dołącz pierwszą etykiete!
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| _version_ | 1869527852530008064 |
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| collection | Directory of Open Access Books |
| description | This book describes recent efforts in improving intelligent systems for automatic biosignal analysis. It focuses on machine learning and deep learning methods used for classification of different organism states and disorders based on biomedical signals such as EEG, ECG, HRV, and others. |
| format | Online |
| id | doab-20.500.12854ir-76753 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2022 |
| publishDateRange | 2022 |
| publishDateSort | 2022 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-767532024-03-30T12:51:15Z Intelligent Biosignal Analysis Methods Jović, Alan sleep stage scoring neural network-based refinement residual attention T-end annotation signal quality index tSQI optimal shrinkage emotion EEG DEAP CNN surgery image disgust autonomic nervous system electrocardiogram galvanic skin response olfactory training psychophysics smell wearable sensors wine sensory analysis accuracy convolution neural network (CNN) classifiers electrocardiography k-fold validation myocardial infarction sensitivity sleep staging electroencephalography (EEG) brain functional connectivity frequency band fusion phase-locked value (PLV) wearable device emotional state mental workload stress heart rate eye blinks rate skin conductance level emotion recognition electroencephalogram (EEG) photoplethysmography (PPG) machine learning feature extraction feature selection deep learning non-stationarity individual differences inter-subject variability covariate shift cross-participant inter-participant drowsiness detection EEG features drowsiness classification fatigue detection residual network Mish spatial transformer networks non-local attention mechanism Alzheimer’s disease fall detection event-centered data segmentation accelerometer window duration n/a thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries This book describes recent efforts in improving intelligent systems for automatic biosignal analysis. It focuses on machine learning and deep learning methods used for classification of different organism states and disorders based on biomedical signals such as EEG, ECG, HRV, and others. 2022-01-11T13:41:01Z 2022-01-11T13:41:01Z 2021 book ONIX_20220111_9783036516929_488 9783036516929 9783036516912 https://directory.doabooks.org/handle/20.500.12854/76753 eng image/jpeg Attribution 4.0 International https://mdpi.com/books/pdfview/book/4202 https://mdpi.com/books/pdfview/book/4202 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-0365-1691-2 10.3390/books978-3-0365-1691-2 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783036516929 9783036516912 256 Basel, Switzerland open access |
| spellingShingle | sleep stage scoring neural network-based refinement residual attention T-end annotation signal quality index tSQI optimal shrinkage emotion EEG DEAP CNN surgery image disgust autonomic nervous system electrocardiogram galvanic skin response olfactory training psychophysics smell wearable sensors wine sensory analysis accuracy convolution neural network (CNN) classifiers electrocardiography k-fold validation myocardial infarction sensitivity sleep staging electroencephalography (EEG) brain functional connectivity frequency band fusion phase-locked value (PLV) wearable device emotional state mental workload stress heart rate eye blinks rate skin conductance level emotion recognition electroencephalogram (EEG) photoplethysmography (PPG) machine learning feature extraction feature selection deep learning non-stationarity individual differences inter-subject variability covariate shift cross-participant inter-participant drowsiness detection EEG features drowsiness classification fatigue detection residual network Mish spatial transformer networks non-local attention mechanism Alzheimer’s disease fall detection event-centered data segmentation accelerometer window duration n/a thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries Intelligent Biosignal Analysis Methods |
| title | Intelligent Biosignal Analysis Methods |
| title_full | Intelligent Biosignal Analysis Methods |
| title_fullStr | Intelligent Biosignal Analysis Methods |
| title_full_unstemmed | Intelligent Biosignal Analysis Methods |
| title_short | Intelligent Biosignal Analysis Methods |
| title_sort | intelligent biosignal analysis methods |
| topic | sleep stage scoring neural network-based refinement residual attention T-end annotation signal quality index tSQI optimal shrinkage emotion EEG DEAP CNN surgery image disgust autonomic nervous system electrocardiogram galvanic skin response olfactory training psychophysics smell wearable sensors wine sensory analysis accuracy convolution neural network (CNN) classifiers electrocardiography k-fold validation myocardial infarction sensitivity sleep staging electroencephalography (EEG) brain functional connectivity frequency band fusion phase-locked value (PLV) wearable device emotional state mental workload stress heart rate eye blinks rate skin conductance level emotion recognition electroencephalogram (EEG) photoplethysmography (PPG) machine learning feature extraction feature selection deep learning non-stationarity individual differences inter-subject variability covariate shift cross-participant inter-participant drowsiness detection EEG features drowsiness classification fatigue detection residual network Mish spatial transformer networks non-local attention mechanism Alzheimer’s disease fall detection event-centered data segmentation accelerometer window duration n/a thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries |
| topic_facet | sleep stage scoring neural network-based refinement residual attention T-end annotation signal quality index tSQI optimal shrinkage emotion EEG DEAP CNN surgery image disgust autonomic nervous system electrocardiogram galvanic skin response olfactory training psychophysics smell wearable sensors wine sensory analysis accuracy convolution neural network (CNN) classifiers electrocardiography k-fold validation myocardial infarction sensitivity sleep staging electroencephalography (EEG) brain functional connectivity frequency band fusion phase-locked value (PLV) wearable device emotional state mental workload stress heart rate eye blinks rate skin conductance level emotion recognition electroencephalogram (EEG) photoplethysmography (PPG) machine learning feature extraction feature selection deep learning non-stationarity individual differences inter-subject variability covariate shift cross-participant inter-participant drowsiness detection EEG features drowsiness classification fatigue detection residual network Mish spatial transformer networks non-local attention mechanism Alzheimer’s disease fall detection event-centered data segmentation accelerometer window duration n/a thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNT Media, entertainment, information and communication industries::KNTX Information technology industries |
| url | ONIX_20220111_9783036516929_488 |