Learn More
Many bioelectric signals result from the electrical response of physiological systems to an impulse that can be internal (ECG signals) or external (evoked potentials). In this paper an adaptive impulse correlated filter (AICF) for event-related signals that are time-locked to a stimulus is presented. This filter estimates the deterministic component of the(More)
The objective of the present work was to detect and analyze wheezes by means of a highly sensitive time-frequency algorithm. Automatic measurements were compared with clinical auscultation for forced exhalation segments from 1.2 to 0 liters/second (l/s). Sensitivities between 100% and 71%, as a function of flow level related to wheezing segments detection,(More)
Snoring, a symptom which may indicate the presence of the obstructive sleep apnoea syndrome (OSA), is also common in the general population. Recent studies have suggested that the acoustic characteristics of snoring sound may differ between simple snorers and OSA patients. We have studied a small number of patients with simple snoring and OSA, analysing the(More)
The study of the amplitude of respiratory muscle mechanomyographic (MMG) signals could be useful in clinical practice as an alternative non-invasive technique to assess respiratory muscle strength. The MMG signal is stochastic in nature, and its amplitude is usually estimated by means of the average rectified value (ARV) or the root mean square (RMS) of the(More)
One of the most frequent reasons for instituting mechanical ventilation is to decrease patient's work of breathing. Many attempts have been made to increase the effectiveness of the evaluation of the respiratory pattern with the analysis of the respiratory signals. This work proposes a method for the study of the differences in respiratory pattern(More)
This study analyses the location of patterns of brain activity in the signal space while a human subject is trained to operate a brain-computer interface. This evaluation plays an important role in the understanding of the underlying system, and it gives valuable information about the translation algorithms. The relative position and morphology of the(More)
Instantaneous frequency (IF) calculated by empirical mode decomposition (EMD) provides a novel approach to analyze respiratory sounds (RS). Traditionally, RS have been analyzed using classical time-frequency distributions, such as short-time Fourier transform (STFT) or wavelet transform (WT). However, EMD has become a powerful tool for nonlinear and(More)
This study proposes a method for the characterization of respiratory patterns in chronic heart failure (CHF) patients with periodic breathing (PB) and nonperiodic breathing (nPB), using the flow signal. Autoregressive modeling of the envelope of the respiratory flow signal is the starting point for the pattern characterization. Spectral parameters extracted(More)
Estimation of time-varying changes in evoked potentials (EP's) has important applications, such as monitoring high-risk neurosurgical procedures. We test the hypothesis that injury related changes in EP signals may be modeled by orthonormal basis functions. We evaluate two models of time-varying EP signals: the Fourier series model (FSM) and the Walsh(More)