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Entropy, as a measure of randomness in time-varying signals, is widely used in areas such as thermodynamics, statistical mechanics and information theory. This paper investigates the use of two commonly employed entropy measures, namely Wavelet Entropy and Approximate Entropy, as a predictor of tremor reappearance in Essential Tremor patients; the predictor input is a raw surface-electromyographic...
Steady-state visual evoked potential (SSVEP)-based Brain-Computer Interface (BCI) works on the basis that an attended stimulus shows an enhanced visual evoked response. By examining EEG power at the frequency of the dominant evoked response, we are able to determine which stimulus the subject is attending. However, due to the limited processing capability of human visual system, when presented with...
Cardiac auscultation has proven to be an excellent diagnostic tool. Heart sound processing algorithms are not completely robust in the presence of noise, requiring clean segments of heart sounds to extract reliable diagnostic features. This paper presents a new approach to detect transient noises mixed with heart sound. The algorithm explores a single channel source separation algorithm and evaluates...
Neural oscillations are important features in a working central nervous system, facilitating efficient communication across large networks of neurons. To better study the role of these oscillations in various cognitive processes, and to be able to build clinical applications around them, accurate and precise estimations of the instantaneous frequency and phase are required. Here, we present methodology...
Measuring the variation of the respiratory rate makes it possible to analyze the structure of sleep. The variation is high when awake or in REM sleep, and decreases in deep sleep. With sleep apnea, the respiratory variation is disturbed. We present a novel method for extracting respiratory rate variation from indirect measurements of respiration. The method is particularly suitable for force sensor...
In this paper Heart Rate Variability (HRV) and Blood Pressure Variability (BPV) were analyzed before the onset of cardiac arrhythmia in order to derive markers for short-term forecasting. The (a) coherence between systolic blood pressure (SBP) and cardiac oscillations in low-frequency (LF) and high-frequency (HF) band; (b) fluctuations of phase; (c) HRV and BPV as a LF power and HF power in frequency...
Many stochastic systems show certain trends which in turn govern their underlying non-stationary time varying behavior. In order to facilitate efficient quantification of such signals, their analysis necessitates the use of robust tools for discerning between different classes of data. Research show that, use of time-frequency techniques offer intelligible representations for non-stationary signals,...
Cognitive control of emotion plays an important role in maintaining emotional stability in people's daily life. However, the neural mechanism remains unclear. This study examined the induced gamma activity in response to emotional expressions which was associated with the cognitive regulation. Electroencephalogram (EEG) was recorded in fifteen normal subjects when detecting emotional expressions....
A new suction detection algorithm for rotary Left Ventricular Assist Devices (LVAD) is presented. The algorithm is based on a Lagrangian Support Vector Machine (LSVM) model. Six suction indices are derived from the LVAD pump flow signal and form the inputs to the LSVM classifier. The LSVM classifier is trained and tested to classify pump flow patterns into three states: No Suction, Approaching Suction,...
Clinical assessment scales to evaluate motor abilities in stroke survivors could be used to individualize rehabilitation interventions thus maximizing motor gains. Unfortunately, these scales are not widely utilized in clinical practice because their administration is excessively time-consuming. Wearable sensors could be relied upon to address this issue. Sensor data could be unobtrusively gathered...
Coherence analysis characterizes frequency-dependent covariance between signals, and is useful for multivariate oscillatory data often encountered in neuroscience. The global coherence provides a summary of coherent behavior in high-dimensional multivariate data by quantifying the concentration of variance in the first mode of an eigenvalue decomposition of the cross-spectral matrix. Practical application...
This paper presents a computationally simple and effective methodology based on empirical mode decomposition (EMD) for classification of telephone quality normal and pathological speech signals. EMD is used to decompose continuous normal and pathological speech signals into intrinsic mode functions, which are analyzed to extract physically meaningful and unique temporal and spectral features. Using...
Here, we combine magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) to detect the dynamic brain responses to 3D-SFM. We manipulated the coherence of randomly moving dots to create different levels of 3D perception and investigated the associated changes in brain activity. Results of the fMRI analysis were used to impose plausible constraints on the MEG inverse calculation...
In this paper cross time-frequency (TF) analysis is used to estimate the phase differences and the phase locking between cardiovascular signals. Phase differences give a measure of the changes in the synchronization between two oscillations, while phase locking measures the degree of similarity of these changes across subjects. The methodology is based on the smoothed pseudo Wigner-Ville distribution...
Spectral analysis of Heart Rate Variability (HRV) is used for the assessment of cardiovascular autonomic control. In this study Continuous Wavelet Transform (CWT) has been used to evaluate the effect of local anesthesia on HRV parameters in a group of fourteen patients undergoing axillary brachial plexus block. A new method which takes signal characteristics into account has been presented for the...
The goal of this study was to evaluate the changes in heart rate variability (HRV) parameters due to a specific physical, mental or combined load. More specifically, the difference in effect between mental load and physical activity is studied. In addition, the effect of the combined physical and mental demand on the HRV parameters was examined and compared with the changes during the single task...
We have used two algorithms, wavelet phase coherence (WPC) and modulation index (MI) analysis to study frequency interactions in the human epileptic brain. Quantitative analyses were performed on intracranial electroencephalographic (iEEG) segments from three patients with neocortical epilepsy. Interelectrode coherence was measured using WPC and intraelectrode frequency interactions were analyzed...
Monitoring fetal wellbeing is a compelling problem in modern obstetrics. Clinicians have become increasingly aware of the link between fetal activity (movement), well-being, and later developmental outcome. We have recently developed an ambulatory accelerometer-based fetal activity monitor (AFAM) to record 24-hour fetal movement. Using this system, we aim at developing signal processing methods to...
An efficient way to investigate the neural basis of nociceptive responses is the event-related brain potentials (ERPs). One component belonging to this family of ERPs is the mismatch negativity (MMN). It reflects pre-attentive detection of changes in the incoming stimulus by comparing the new stimulus with sensory memory traces. In this work, single trials of ERP taken from EEG signal recorded under...
The purpose of this study was to describe the changes in high-frequency QRS (HF-QRS) components due to myocardial ischemia provoked by prolonged artery occlusion during percutaneous coronary interventions (PCI). Signal-averaged ECGs from 69 patients were obtained during PCI procedures and comparison of high-frequency components of the QRS at different temporal regions and frequency bandwidth were...
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