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Palabras clave – provistas por la editorial

movement intention; brain–computer interface; movement-related cortical potential; neurorehabilitation; phonocardiogram; machine learning; empirical mode decomposition; feature extraction; mel-frequency cepstral coefficients; support vector machines; computer aided diagnosis; congenital heart disease; statistical analysis; convolutional neural network (CNN); long short-term memory (LSTM); emotion recognition; EEG; ECG; GSR; deep neural network; physiological signals; electroencephalography; Brain-Computer Interface; multiscale principal component analysis; successive decomposition index; motor imagery; mental imagery; classification; hybrid brain-computer interface (BCI); home automation; electroencephalogram (EEG); steady-state visually evoked potential (SSVEP); eye blink; short-time Fourier transform (STFT); convolution neural network (CNN); human machine interface (HMI); rehabilitation; wheelchair; quadriplegia; Raspberry Pi; image gradient; AMR voice; Open-CV; image processing; acoustic; startle; reaction; response; reflex; blink; mobile; sound; stroke; EMG; brain-computer interface; myoelectric control; pattern recognition; functional near-infrared spectroscopy; z-score method; channel selection; region of interest; channel of interest; respiratory rate (RR); Electrocardiogram (ECG); ECG derived respiration (EDR); auscultation sites; pulse plethysmograph; biomedical signal processing; feature selection and reduction; discrete wavelet transform; hypertension