A5052426139- ECG Monitoring and Analysis
- Cardiac electrophysiology and arrhythmias
- Atrial Fibrillation Management and Outcomes
- Heart Rate Variability and Autonomic Control
- Cardiac Arrhythmias and Treatments
- Non-Invasive Vital Sign Monitoring
- EEG and Brain-Computer Interfaces
- Blind Source Separation Techniques
- Hemodynamic Monitoring and Therapy
- Fault Detection and Control Systems
- Cardiac Imaging and Diagnostics
- Analog and Mixed-Signal Circuit Design
- Phonocardiography and Auscultation Techniques
- Advanced Adaptive Filtering Techniques
- Healthcare Technology and Patient Monitoring
- Hearing, Cochlea, Tinnitus, Genetics
- Muscle activation and electromyography studies
- Noise Effects and Management
- Hearing Loss and Rehabilitation
- Speech and Audio Processing
- Image and Signal Denoising Methods
- Spectroscopy and Chemometric Analyses
- Advanced Chemical Sensor Technologies
- Cardiovascular Function and Risk Factors
- Cardiovascular and exercise physiology
Lund University
2015-2024
Signal Processing (United States)
1995-2018
Politecnico di Milano
2011
Informa (Sweden)
2009-2010
Vanderbilt University
2009
Leipzig University
2009
University of Liverpool
2005
Blackpool Victoria Hospital
2005
Philips (United States)
2004
Brigham and Women's Hospital
2004
An integrated method for clustering of QRS complexes is presented which includes basis function representation and self-organizing neural networks (NN's). Each complex decomposed into Hermite functions the resulting coefficients width parameter are used to represent complex. By means this representation, unsupervised NNs employed cluster data 25 groups. Using MIT-BIH arrhythmia database, clusters found exhibit a very low degree misclassification (1.5%). The outperforms, on both published...
This paper reviews the current status of principal component analysis in area ECG signal processing. The fundamentals PCA are briefly described and relationship between Karhunen-Loève transform is explained. Aspects on related to data with temporal spatial correlations considered as adaptive estimation components is. Several applications reviewed where techniques have been successfully employed, including compression, ST-T segment for detection myocardial ischemia abnormalities ventricular...
A robust method is presented for electrocardiogram (ECG)-based estimation of the respiratory frequency during stress testing. Such ECGs contain highly nonstationary noise and exhibit changes in QRS morphology which, when combined with dynamic nature frequency, make most existing methods break down. The present exploits oscillatory pattern rotation angles heart's electrical axis as induced by respiration. series angles, obtained from least-squares loop alignment, subject to power spectral...
Cardiorespiratory monitoring is crucial for the diagnosis and management of multiple conditions such as stress sleep disorders. Therefore, development ambulatory systems providing continuous, comfortable, inexpensive means represents an important research topic. Several techniques have been proposed in literature to derive respiratory information from ECG signal. Ten methods compute single-lead ECG-derived respiration (EDR) were compared under conditions, including different recording...
Time-frequency analysis is considered for characterizing atrial fibrillation in the surface electrocardiogram (ECG). Variations fundamental frequency of fibrillatory waves are tracked by using different time-frequency distributions which appropriate to short- and long-term variations. The cross Wigner-Ville distribution found be particularly useful short-term due its ability handle poor signal-to-noise ratios. In patients with chronic fibrillation, substantial variations exist up 2.5 Hz can...
Automated classification of ECG patterns is facilitated by careful selection waveform features. This paper presents a method for evaluating the properties features that describe shape QRS complex. By examining distances in feature space class nearly similar complexes, transitions which are poorly described under investigation can be readily identified. To obtain continuous range waveforms, required method, mathematical model used to simulate complexes.
In this study, the upward I(US) and downward I(DS) slopes of QRS complex are proposed as indices for quantifying ischemia-induced electrocardiogram (ECG) changes. Using ECG recordings acquired before during percutaneous transluminal coronary angioplasty (PTCA), it is found that considerably less steep artery occlusion, in particular I(DS). With respect to ischemia detection, slope outperform often used high-frequency index (defined root mean square (rms) bandpass-filtered signal frequency...
The analysis of signals on complex topologies modeled by graphs is a topic increasing importance. Decompositions play crucial role in the representation and processing such information. Here, we propose new tight frame design that adapted to class graph. construction starts from prototype Meyer-type system kernels with uniform subbands. ensemble energy spectral density then defined for given set warped resulting subbands capture same amount signal class. This approach accounts at time graph...
<bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Introduction</b> : Deep learning models for detecting episodes of atrial fibrillation (AF) using rhythm information in long-term ambulatory ECG recordings have shown high performance. However, the rhythm-based approach does not take advantage morphological conveyed by different waveforms, particularly f-waves. As a result, performance such may be inherently limited....
A novel method for QRST cancellation during atrial fibrillation (AF) is introduced use in recordings with two or more leads. The based on an echo state neural network which estimates the time-varying, nonlinear transfer function between leads, one lead activity and another without, purpose of canceling ventricular activity. has different sets weights that define input, hidden, output layers, only set adapted every new sample to be processed. performance evaluated ECG signals, simulated...
The problem of classifying short atrial fibrillatory segments in ambulatory ECG recordings as being either paroxysmal or persistent is addressed by investigating a robust approach to signal characterization. method comprises preprocessing estimation the dominant frequency for purpose controlling subbands filter bank, computation relative subband (harmonics) energy, and sample entropy. Using minimum-error-rate classification different feature vectors, data set consisting 24-h from 50 subjects...
Objective: The present study addresses the problem of estimating respiratory rate from morphological ECG variations in presence atrial fibrillatory waves (f-waves). significance performing f-wave suppression before estimation is investigated. Methods: performance a novel approach to ECG-derived respiration, named “slope range” (SR) and designed particularly for operation fibrillation (AF), compared that two well-known methods based on either R-wave angle (RA) or QRS loop rotation (LA). A...