ECG wave detector and delineation with wavelets

Proceedings of the International Conference on Computational Intelligence in Medicine Healthcare, CIMED 2005, Costa da Caparica, June 29 - July 1, 2005

Variability analysis of discrete event series and wavefront patterns in surface electrocardiogram: contributions to psychophysiological and clinical research

The surface electrocardiogram (ECG) is an established diagnostic tool for the detection of abnormalities in the electrical activity of the heart. The interest of the ECG, however, extends beyond the diagnostic purpose. In recent years, studies in cognitive psychophysiology have related heart rate variability (HRV) to memory performance and mental workload. The aim of this thesis was to analyze the variability of surface ECG derived rhythms, at two different time scales: the discrete-event time scale, typical of beat-related features (Objective I), and the “continuous” time scale of separated sources in the ECG (Objective II), in selected scenarios relevant to psychophysiological and clinical research, respectively. Objective I) Joint time-frequency and non-linear analysis of HRV was carried out, with the goal of assessing psychophysiological workload (PPW) in response to working memory engaging tasks. Results from fourteen healthy young subjects suggest the potential use of the proposed indices in discriminating PPW levels in response to varying memory-search task difficulty. Objective II) A novel source-cancellation method based on morphology clustering was proposed for the estimation of the atrial wavefront in atrial fibrillation (AF) from body surface potential maps. Strong direct correlation between spectral concentration (SC) of atrial wavefront and temporal variability of the spectral distribution was shown in persistent AF patients, suggesting that with higher SC, shorter observation time is required to collect spectral distribution, from which the fibrillatory rate is estimated. This could be time and cost effective in clinical decision-making. The results held for reduced leads sets, suggesting that a simplified setup could also be considered, further reducing the costs. In designing the methods of this thesis, an online signal processing approach was kept, with the goal of contributing to real-world applicability. An algorithm for automatic assessment of ambulatory ECG quality, and an automatic ECG delineation algorithm were designed and validated.

An optimized lead system for long-term esophageal electrocardiography

Long-term electrocardiography (ECG) featuring adequate atrial and ventricular signal quality is highly desirable. Routinely used surface leads are limited in atrial signal sensitivity and recording capability impeding complete ECG delineation, i.e. in the presence of supraventricular arrhythmias. Long-term esophageal ECG might overcome these limitations but requires a dedicated lead system and recorder design. To this end, we analysed multiple-lead esophageal ECGs with respect to signal quality by describing the ECG waves as a function of the insertion level, interelectrode distance, electrode shape and amplifier's input range. The results derived from clinical data show that two bipolar esophageal leads, an atrial lead with short (15 mm) interelectrode distance and a ventricular lead with long (80 mm) interelectrode distance provide non-inferior ventricular signal strength and superior atrial signal strength compared to standard surface lead II. High atrial signal slope in particular is observed with the atrial esophageal lead. The proposed esophageal lead system in combination with an increased recorder input range of ±20 mV minimizes signal loss due to excessive electrode motion typically observed in esophageal ECGs. The design proposal might help to standardize long-term esophageal ECG registrations and facilitate novel ECG classification systems based on the independent detection of ventricular and atrial electrical activity.

A Reliable Downscaling of ECG Signals for the Detection of T wave Heterogeneity Features

In cardiovascular disease the definition and the detection of the ECG parameters related to repolarization dynamics in post MI patients is still a crucial unmet need. In addition, the use of a 3D sensor in the implantable medical devices would be a crucial mean in the assessment or prediction of Heart Failure status, but the inclusion of such feature is limited by hardware and firmware constraints. The aim of this thesis is the definition of a reliable surrogate of the 500 Hz ECG signal to reach the aforementioned objective. To evaluate the worsening of reliability due to sampling frequency reduction on delineation performance, the signals have been consecutively down sampled by a factor 2, 4, 8 thus obtaining the ECG signals sampled at 250, 125 and 62.5 Hz, respectively. The final goal is the feasibility assessment of the detection of the fiducial points in order to translate those parameters into meaningful clinical parameter for Heart Failure prediction, such as T waves intervals heterogeneity and variability of areas under T waves. An experimental setting for data collection on healthy volunteers has been set up at the Bakken Research Center in Maastricht. A 16 – channel ambulatory system, provided by TMSI, has recorded the standard 12 – Leads ECG, two 3D accelerometers and a respiration sensor. The collection platform has been set up by the TMSI property software Polybench, the data analysis of such signals has been performed with Matlab. The main results of this study show that the 125 Hz sampling rate has demonstrated to be a good candidate for a reliable detection of fiducial points. T wave intervals proved to be consistently stable, even at 62.5 Hz. Further studies would be needed to provide a better comparison between sampling at 250 Hz and 125 Hz for areas under the T waves.

ECG scar quantification correlates with cardiac magnetic resonance scar size and prognostic factors in Chagas' disease

Objective To test the hypothesis that 12-lead ECG QRS scoring quantifies myocardial scar and correlates with disease severity in Chagas' heart disease. Design Patients underwent 12-lead ECG for QRS scoring and cardiac magnetic resonance with late gadolinium enhancement (CMR-LGE) to assess myocardial scar. Setting University of Sao Paulo Medical School, Sao Paulo, Brazil. Patients 44 Seropositive patients with Chagas' disease without a history of myocardial infarction and at low risk for coronary artery disease. Main outcome measures Correlation between QRS score, CMR-LGE scar size and left ventricular ejection fraction. Relation between QRS score, heart failure (HF) class and history of ventricular tachycardia (VT). Results QRS score correlated directly with CMR-LGE scar size (R=0.69, p<0.0001) and inversely with left ventricular ejection fraction (R=-0.54, p=0.0002), which remained significant in the subgroup with conduction defects. Patients with class II or III HF had significantly higher QRS scores than those with class I HF (5.1 +/- 3.4 vs 2.1 +/- 3.1 QRS points (p=0.002)) and patients with a history of VT had significantly higher QRS scores than those without a history of VT (5.3 +/- 3.2% vs 2.6 +/- 3.4 QRS points (p=0.02)). A QRS score >= 2 points had particularly good sensitivity and specificity (95% and 83%, respectively) for prediction of large CMR-LGE, and a QRS score >= 7 points had particularly high specificity (92% and 89%, respectively) for predicting significant left ventricular dysfunction and history of VT. Conclusions The wide availability of 12-lead ECG makes it an attractive screening tool and may enhance clinical risk stratification of patients at risk for more severe, symptomatic Chagas' heart disease.

Cardiac MRI for Detection of Unrecognized Myocardial Infarction in Patients With End-Stage Renal Disease: Comparison With ECG and Scintigraphy

OBJECTIVE. The purposes of this study were to use the myocardial delayed enhancement technique of cardiac MRI to investigate the frequency of unrecognized myocardial infarction (MI) in patients with end-stage renal disease, to compare the findings with those of ECG and SPECT, and to examine factors that may influence the utility of these methods in the detection of MI. SUBJECTS AND METHODS. We prospectively performed cardiac MRI, ECG, and SPECT to detect unrecognized MI in 72 patients with end-stage renal disease at high risk of coronary artery disease but without a clinical history of MI. RESULTS. Fifty-six patients (78%) were men ( mean age, 56.2 +/- 9.4 years) and 16 (22%) were women ( mean age, 55.8 +/- 11.4). The mean left ventricular mass index was 103.4 +/- 27.3 g/m(2), and the mean ejection fraction was 60.6% +/- 15.5%. Myocardial delayed enhancement imaging depicted unrecognized MI in 18 patients (25%). ECG findings were abnormal in five patients (7%), and SPECT findings were abnormal in 19 patients (26%). ECG findings were false-negative in 14 cases and false-positive in one case. The accuracy, sensitivity, and specificity of ECG were 79.2%, 22.2%, and 98.1% (p = 0.002). SPECT findings were false-negative in six cases and false-positive in seven cases. The accuracy, sensitivity, and specificity of SPECT were 81.9%, 66.7%, and 87.0% ( not significant). During a period of 4.9-77.9 months, 19 cardiac deaths were documented, but no statistical significance was found in survival analysis. CONCLUSION. Cardiac MRI with myocardial delayed enhancement can depict unrecognized MI in patients with end-stage renal disease. ECG and SPECT had low sensitivity in detection of MI. Infarct size and left ventricular mass can influence the utility of these methods in the detection of MI.

Can ECG changes predict the long-term outcome in patients admitted to hospital for suspected acute myocardial infarction?

7,028 patients with suspected acute myocardial infarction and discharged alive from hospital were followed in a 10-year community-based study. The long-term prognosis was relatively good if the electrocardiograms (ECGs) were normal (5-year all-cause death rate 5%), poor with uncodable ECGs showing rhythm or conduction disturbances (37%), and intermediate with new Q wave, new ST elevation, new T wave inversion or ischemic ECG (17-21%), and with new ST depression (27%). Similar patterns were found for ischemic cardiac death and reinfarction. The long-term prognosis of patients with suspected acute myocardial infarction is relatively good if the ECGs are normal and poor if ECGs are uncodable. ST depression may be a marker for a worse long-term outcome.

Cytogenetic molecular delineation of a terminal 18q deletion suggesting neo-telomere formation

Deletion of the long arm of chromosome 18 is one of the most common segmental aneusomies compatible with life and usually involves a deletion of the terminal chromosomal region. However, the mechanisms implicated in the stabilization of terminal deletions are not well understood. In this study, we analyzed a girl with moderate mental retardation who had a cytogenetically visible terminal 18q deletion. In order to characterize the breakpoint in the terminal 18q region, we used fluorescence In situ hybridization (FISH) with bacterial artificial chromosomes (BACs) and pan-telomeric probes and also the array technique based on comparative genomic hybridization (array-CGH). FISH with pan-telomeric probes revealed no signal in the terminal region of the deleted chromosome, indicating the absence of normal telomere repeat (TTAGGG)n sequences in 18q. We suggest that neo-telomere formation by chromosome healing was involved in the repair and stabilization of this terminal deletion. (C) 2010 Elsevier Masson SAS. All rights reserved.

Further delineation of the 15q13 microdeletion and duplication syndromes: a clinical spectrum varying from non-pathogenic to a severe outcome

Background: Recurrent 15q13.3 microdeletions were recently identified with identical proximal (BP4) and distal (BP5) breakpoints and associated with mild to moderate mental retardation and epilepsy. Methods: To assess further the clinical implications of this novel 15q13.3 microdeletion syndrome, 18 new probands with a deletion were molecularly and clinically characterised. In addition, we evaluated the characteristics of a family with a more proximal deletion between BP3 and BP4. Finally, four patients with a duplication in the BP3-BP4-BP5 region were included in this study to ascertain the clinical significance of duplications in this region. Results: The 15q13.3 microdeletion in our series was associated with a highly variable intra-and inter-familial phenotype. At least 11 of the 18 deletions identified were inherited. Moreover, 7 of 10 siblings from four different families also had this deletion: one had a mild developmental delay, four had only learning problems during childhood, but functioned well in daily life as adults, whereas the other two had no learning problems at all. In contrast to previous findings, seizures were not a common feature in our series (only 2 of 17 living probands). Three patients with deletions had cardiac defects and deletion of the KLF13 gene, located in the critical region, may contribute to these abnormalities. The limited data from the single family with the more proximal BP3-BP4 deletion suggest this deletion may have little clinical significance. Patients with duplications of the BP3-BP4-BP5 region did not share a recognisable phenotype, but psychiatric disease was noted in 2 of 4 patients. Conclusions: Overall, our findings broaden the phenotypic spectrum associated with 15q13.3 deletions and suggest that, in some individuals, deletion of 15q13.3 is not sufficient to cause disease. The existence of microdeletion syndromes, associated with an unpredictable and variable phenotypic outcome, will pose the clinician with diagnostic difficulties and challenge the commonly used paradigm in the diagnostic setting that aberrations inherited from a phenotypically normal parent are usually without clinical consequences.

Delineation of sulphide ore-zones by borehole radar tomography at Hellyer Mine, Australia

Velocity and absorption tomograms are the two most common forms of presentation of radar tomographic data. However, mining personnel, geophysicists included, are often unfamiliar with radar velocity and absorption. In this paper, general formulae are introduced, relating velocity and attenuation coefficient to conductivity and dielectric constant. The formulae are valid for lossy media as well as high-resistivity materials. The transformation of velocity and absorption to conductivity and dielectric constant is illustrated via application of the formulae to radar tomograms from the Hellyer zinc-lead-silver mine, Tasmania, Australia. The resulting conductivity and dielectric constant tomograms constructed at Hellyer demonstrated the potential of radar tomography to delineate sulphide ore zones. (C) 2001 Elsevier Science B.V. All rights reserved.

Optimizing electrode positioning in 3-lead ECG chest devices

Although the 12-lead electrocardiogram has become an essential medical and research tool, many current and envisaged applications would benefit from simpler devices, using 3-lead ECG configuration. This is particularly true for Ambient Assisted Living (in a broad perspective). However, the chest anatomy of female patients, namely during pregnancy, can hamper the adequate placement of a 3-lead ECG device and, very often, electrodes are placed below the chest rather than at the precise thoracic landmarks. Thus, the aim of this study was to compare the effect of electrode positioning on the ECG signal of pregnant women and provide guidelines for device development. The effect of breast tissue on the ECG signal was investigated by relating breast size with the signal-to-noise ratio, root mean square and R-wave amplitude. Results show that the 3-lead ECG should be placed on the breast rather than under the breast and indicate positive correlation between breast size and signal-to-noise ratio.

Embedded platform for ECG biometric recognition

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia de Electrónica e Telecomunicações

ECG denoising based on adaptive signal processing technique

An Electrocardiogram (ECG) monitoring system deals with several challenges related with noise sources. The main goal of this text was the study of Adaptive Signal Processing Algorithms for ECG noise reduction when applied to real signals. This document presents an adaptive ltering technique based on Least Mean Square (LMS) algorithm to remove the artefacts caused by electromyography (EMG) and power line noise into ECG signal. For this experiments it was used real noise signals, mainly to observe the di erence between real noise and simulated noise sources. It was obtained very good results due to the ability of noise removing that can be reached with this technique. A recolha de sinais electrocardiogr a cos (ECG) sofre de diversos problemas relacionados com ru dos. O objectivo deste trabalho foi o estudo de algoritmos adaptativos para processamento digital de sinal, para redu c~ao de ru do em sinais ECG reais. Este texto apresenta uma t ecnica de redu c~ao de ru do baseada no algoritmo Least Mean Square (LMS) para remo c~ao de ru dos causados quer pela actividade muscular (EMG) quer por ru dos causados pela rede de energia el ectrica. Para as experiencias foram utilizados ru dos reais, principalmente para aferir a diferen ca de performance do algoritmo entre os sinais reais e os simulados. Foram conseguidos bons resultados, essencialmente devido as excelentes caracter sticas que esta t ecnica tem para remover ru dos.

Unveiling the Biometric Potential of Finger-Based ECG Signals

The ECG signal has been shown to contain relevant information for human identification. Even though results validate the potential of these signals, data acquisition methods and apparatus explored so far compromise user acceptability, requiring the acquisition of ECG at the chest. In this paper, we propose a finger-based ECG biometric system, that uses signals collected at the fingers, through a minimally intrusive 1-lead ECG setup recurring to Ag/AgCl electrodes without gel as interface with the skin. The collected signal is significantly more noisy than the ECG acquired at the chest, motivating the application of feature extraction and signal processing techniques to the problem. Time domain ECG signal processing is performed, which comprises the usual steps of filtering, peak detection, heartbeat waveform segmentation, and amplitude normalization, plus an additional step of time normalization. Through a simple minimum distance criterion between the test patterns and the enrollment database, results have revealed this to be a promising technique for biometric applications.