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Palabras clave – provistas por la editorial

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