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The surface electrogastrogram (EGG) records the electrical slow wave of the stomach noninvasively, whose frequency is a useful clinical indicator of the state of gastric motility. Estimators based on the periodogram method are widely adopted to obtain this parameter. But they are with a poor frequency domain resolution when the data window is short in time-frequency analysis, and have not taken full...
Research in time-frequency distributions (TFDs) is limited in terms of their use of the available spatial domains and in their target applications. Most of the work up till now has been concentrated mainly on the t-f domain space. This work presents a detailed study about the ambiguity domain (AD), their resemblance in the t-f space and the significance of using such a representation. Further, a novel...
Movement-related changes such as event-related desynchronizationcan (ERD) and event-related synchronization (ERS) can be found in human subthalamic nucleus (STN) with analysis on local field potentials (LFP) recorded from Parkinson's disease (PD) patients. Besides traditional time-frequency (TF) analysis, we introduced nonlinear analysis, bispectral and approximate entropy (ApEn), to measure the signal...
We present an advanced denoising method for non-stationary biomechanical signals with the aim of accurately estimating their second derivative (acceleration). The proposed algorithm is based on the short-time Fourier transform (STFT) representation of the signal and its subsequent modification by means of a suitable time-varying filtering function. The application of the method to experimentally acquired...
Statistical analysis, power spectral density, and Lempel Ziv complexity, are used in a multi-parameter approach to analyze four temporal series obtained from the Electrocardiographic and Respiratory Flow signals of 126 patients on weaning trials. In which, 88 patients belong to successful group (SG), and 38 patients belong to failure group (FG), i.e. failed to maintain spontaneous breathing during...
Brain injury, such as hypoxic-ischemia produced in brain after cardiac arrest, is known to alter somatosensory evoked potential (SSEP) signals, thus serving a diagnostic role. This study explores the high-frequency oscillation (HFO) in SSEP recorded in a rat model of asphyxial cardiac arrest. To best characterize this complex oscillatory activity, several time-frequency representation strategies are...
This paper presents a methodology for Obstructive Sleep Apnea (OSA) detection based on the HRV analysis, where as a measure of relevance PLS is used. Besides, two different combining approaches for the selection of the best set of contours are studied. Attained results can be oriented in research focused on finding alternative methods minimizing the HRV-derived parameters used for OSA diagnosing,...
Proportional strategies for artificial ventilation are the most recent form of synchronized partial ventilatory assistance and intra-breath control techniques available in clinical practice. Currently, the majority of commercial ventilators allowing proportional ventilation uses proportional valves to generate the flow rate pattern. This paper proposes on-off solenoid valves for proportional ventilation...
Time-variant (tv) phase-locking and synchronization characteristics of and between low-frequency (≤1.5 Hz) and high-frequency EEG oscillations (≥3.5 Hz) of the tracé alternant (TA) pattern in full-term newborns have been quantified to explore the origin of quadratic phase coupling (QPC, as non-linear phase coupling measure) between the frequency ranges 1 - 1.5 Hz ⇔ 3.5 - 4.5 Hz, which characterize...
It has been observed that heart rate variability (HRV) diminishes during anesthesia, but the exact mechanisms causing it are not completely understood. The aim of this paper was to study the dynamics of HRV during low dose propofol (N=9) and dexmedetomidine (N=8) anesthesia by using state-of-the-art time-varying methods, and thereby ultimately try to improve the safety of anesthesia. The time-varying...
The brain is a biological system with dynamic interactions between its sub-systems. The complexity of this system poses a challenge for identifying functional networks underlying observed neural activity. Current imaging approaches index local neural activity very well, but there is an increasing need for methods that quantify the interaction between regional activations. In this paper, we focus on...
We here studied the efficacy of wide-band frequency spectra (WBFS) features using multi-taper (MT) spectral analysis in application to motor imagery based Brain Computer Interfaces. We acquired motor imagery task related human scalp electroencephalography (EEG) signals for left vs. right hand movements using 3 different pairs of visual arrow cues. Left vs. right movement imagery discrimination was...
Our aim was to explore time-varying coherence values versus spacing and referencing of electrode contacts in thalamic level from human encephalographic (EEG) data. Data has been acquired during induction of propofol anesthesia until burst-suppression level in scalp EEG. Results are shown from coherence analysis applied to EEG signals from selected depth electrode contacts pair-wise of three subjects...
Studies of obesity and eating disorders need objective tools of Monitoring of Ingestive Behavior (MIB) that can detect and characterize food intake. In this paper we describe detection of food intake by a Support Vector Machine classifier trained on time history of chews and swallows. The training was performed on data collected from 18 subjects in 72 experiments involving eating and other activities...
Dimensionality reduction and feature selection is an important aspect of electroencephalography based event related potential detection systems such as brain computer interfaces. In our study, a predefined sequence of letters was presented to subjects in a Rapid Serial Visual Presentation (RSVP) paradigm. EEG data were collected and analyzed offline. A linear discriminant analysis (LDA) classifier...
The Empirical Mode Decomposition (EMD) is a method to decompose non linear, non stationary time series into a sum of different modes, named Intrinsical Mode Functions each one having a characteristic frequency. In the present work we used the EMD to investigate the properties of the recorded sounds from the Arteriovenous fistula on hemodialysis patients. Phonoangiographic signals coming from two different...
Respiratory sinus arrhythmia (RSA) is largely mediated by the autonomic nervous system through its modulating influence on the heartbeat. We propose an algorithm for quantifying instantaneous RSA as applied to heart beat interval and respiratory recordings under dynamic respiration conditions. The blood volume pressure derived heart beat series (pulse intervals, PI) are modeled as an inverse gaussian...
In this study we propose a method to continuously assess the changes of spontaneous baroreflex sensitivity (BRS). Systolic arterial pressure and RR intervals are analyzed by time-frequency analysis to estimate their instantaneous powers as well as the time-course of their spectral coherence. The BRS estimated in classical frequency bands is compared to the BRS estimated in dynamic frequency bands...
Frequency domain analyses of changes in electromyographic (EMG) signals over time are frequently used to assess muscle fatigue. Fourier based approaches are typically used in these analyses, yet Fourier analysis assumes signal stationarity, which is unlikely during dynamic contractions. Wavelet based methods of signal analysis do not assume stationarity and may be more appropriate for joint time-frequency...
In this present paper, we showed that wavelet analysis (WA) has the potential for extracting specific features from measured arterial diameter and pressure waveforms. The fifth detail of the Daubechies 4 (Db4) wavelet appears to be the most appropriate level for application, in order to analyze artery waveforms and was used to characterized arterial de-endothelization (DE). Raises in smooth muscle...
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