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Assessing Complexity in Physiological Systems through Biomedical Signals Analysis

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Palabras clave – provistas por la editorial

autonomic nervous function; heart rate variability (HRV); baroreflex sensitivity (BRS); photo-plethysmo-graphy (PPG); digital volume pulse (DVP); percussion entropy index (PEI); heart rate variability; posture; entropy; complexity; cognitive task; sample entropy; brain functional networks; dynamic functional connectivity; static functional connectivity; K-means clustering algorithm; fragmentation; aging in human population; factor analysis; support vector machines classification; Sampen; cross-entropy; autonomic nervous system; heart rate; blood pressure; hypobaric hypoxia; rehabilitation medicine; labor; fetal heart rate; data compression; complexity analysis; nonlinear analysis; preterm; Alzheimer’s disease; brain signals; single-channel analysis; biomarker; refined composite multiscale entropy; central autonomic network; interconnectivity; ECG; ectopic beat; baroreflex; self-organized criticality; vasovagal syncope; Zipf’s law; multifractality; multiscale complexity; detrended fluctuation analysis; self-similarity; sEMG; approximate entropy; fuzzy entropy; fractal dimension; recurrence quantification analysis; correlation dimension; largest Lyapunov exponent; time series analysis; relative consistency; event-related de/synchronization; motor imagery; vector quantization; information dynamics; partial information decomposition; conditional transfer entropy; network physiology; multivariate time series analysis; State–space models; vector autoregressive model; penalized regression techniques; linear prediction; fNIRS; brain dynamics; mental arithmetics; multiscale; cardiovascular system; brain; information flow

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Información

Tipo de recurso:

libros

ISBN electrónico

978-3-03943-369-8

País de edición

Suiza