TY  - GEN
AU  - Jović,Alan
AU  - Jović,Alan
TI  - Intelligent Biosignal Analysis Methods
SN  - books978-3-0365-1691-2
PY  - 2021///
CY  - Basel, Switzerland
PB  - MDPI - Multidisciplinary Digital Publishing Institute
KW  - Information technology industries
KW  - bicssc
KW  - sleep stage scoring
KW  - neural network-based refinement
KW  - residual attention
KW  - T-end annotation
KW  - signal quality index
KW  - tSQI
KW  - optimal shrinkage
KW  - emotion
KW  - EEG
KW  - DEAP
KW  - CNN
KW  - surgery image
KW  - disgust
KW  - autonomic nervous system
KW  - electrocardiogram
KW  - galvanic skin response
KW  - olfactory training
KW  - psychophysics
KW  - smell
KW  - wearable sensors
KW  - wine sensory analysis
KW  - accuracy
KW  - convolution neural network (CNN)
KW  - classifiers
KW  - electrocardiography
KW  - k-fold validation
KW  - myocardial infarction
KW  - sensitivity
KW  - sleep staging
KW  - electroencephalography (EEG)
KW  - brain functional connectivity
KW  - frequency band fusion
KW  - phase-locked value (PLV)
KW  - wearable device
KW  - emotional state
KW  - mental workload
KW  - stress
KW  - heart rate
KW  - eye blinks rate
KW  - skin conductance level
KW  - emotion recognition
KW  - electroencephalogram (EEG)
KW  - photoplethysmography (PPG)
KW  - machine learning
KW  - feature extraction
KW  - feature selection
KW  - deep learning
KW  - non-stationarity
KW  - individual differences
KW  - inter-subject variability
KW  - covariate shift
KW  - cross-participant
KW  - inter-participant
KW  - drowsiness detection
KW  - EEG features
KW  - drowsiness classification
KW  - fatigue detection
KW  - residual network
KW  - Mish
KW  - spatial transformer networks
KW  - non-local attention mechanism
KW  - Alzheimer’s disease
KW  - fall detection
KW  - event-centered data segmentation
KW  - accelerometer
KW  - window duration
KW  - n/a
N1  - Open Access
N2  - 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
UR  - https://mdpi.com/books/pdfview/book/4202
UR  - https://directory.doabooks.org/handle/20.500.12854/76753
ER  -