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The analysis of the Variability of the Heart Rate (HRV) is coming as an important indicator for different clinical applications like the prediction of arrhythmias, sudden cardiac death, assessing cardiovascular and metabolic illness progression or in sports physiology. In this paper we have developed an algorithm to detect a supraventricular arrhythmia, by processing the heart rate variability (HRV)...
Early detecetion of ST segment's depression or elevation is very important for prevention of myocardial ischemia and it is very important to prevent a myocardial infarction that may occur in the future. In this study, an algorithm based on Choi-Williams time-frequency distribution was developed in order to early detection of ST segment's depressions or elevations. The performance evaluation of the...
In this paper we present a QRS detection algorithm using accurate masks to determine the QRS wave peak locations in ECG signals. The Daubechies 6 discrete wavelet functions are used to generate the masks that locate the QRS complexes and narrow down the QRS searching to only within the masks. This method utilizes the good properties of this wavelet to enhance QRS features and increase the signal to...
Pulse oximeters use photoplethysmographic (PPG) signals for measurement of oxygen saturation in arterial blood. They measure volumetric changes in the blood flowing through the body, usually extremities such as a finger or an ear lobe. The peripheral pulse signal obtained by transmitted light through the illuminated body extremity, gets modulated by heart synchronous pulse, respiratory activity and...
The ability to generate computationally compact ECG analysis algorithms is of interest in the field of wearable physiologic monitors. Such remote monitors necessarily have limited on-board energy storage and therefore lack the computational power and physical memory often required for academic study of physiologic waveforms. Herein we evaluate a set of algorithms with markedly different computation...
Automated detection and classification of electrocardiogram (ECG) noise sources can play a crucial role in reliable measurement of ECG parameters for accurate diagnosis of cardiovascular diseases (CVDs) under unsupervised telehealth monitoring and intensive care unit (ICU) applications. Although the methods had quite acceptable detection rates, most methods are too complicated for real-time implementation...
A lot of information on the normal and pathological physiology of heart can be obtained in the form of ECG. The irregularity of heart resembles the shape of ECG. One cardiac cycle of ECG signal consists of characteristic points P-QRS-T. The amplitudes and intervals values of P-QRS-T segment determine the functioning of heart of every human. If the electrical activity of the heart is irregular, faster,...
Obstructive Sleep Apnea (OSA) is a breathing disorder that takes place during sleep, and has both short -- as well as long -- term consequences on patient's health. Real -- time monitoring for a patient can be carried out by making use of ElectroCardioGraphy (ECG) recordings. This paper introduces a methodology to forecast OSA events in the minutes following the current time instant. This is accomplished...
ECG analysis is used significantly in diagnosis, and biometrics. QRS complex detection is an important step in any application involving ECG signal. In this work, a novel approach for QRS complex detection based on chirplet transform is proposed. The QRS detection algorithm proposed in this work mainly consists of four steps. A preprocessing step to remove power line interference, computation of chirplet...
In this paper, we present the results of an analysis of the electrocardiogram (ECG) as a biometric using a novel short-time frequency method with robust feature selection. Our proposed method incorporates heartbeats from multiple days and fuses information. Single lead ECG signals from a comparatively large sample of 269 subjects that were sampled from the general population were collected on three...
Cardiac auscultation is one of the classical methods used by the physicians for diagnosis of cardiac abnormalities. There have been attempts to develop complex algorithms for automated diagnosis based on heart sounds. It is however, observed that developmental work towards integrated automated auscultation system targeted towards mass screening has been relatively low. In this paper, we propose a...
In this paper we employ the Matching Pursuit algorithm in order to obtain compact time-frequency representations of ECG data, which are then utilized from an ANN to achieve beat classification. To obtain optimum performance, the effect of the following attributes on the classification performance is examined: number of atoms, type of wavelet and number of ECG samples around the R peak. Our goal is...
This paper introduces the basic characteristics of Gabor, Chirplet, FMm let three time-frequency atom databases and the basic principle of the algorithm in signal processing. FMm let is the important tool of treating linear and nonlinear frequency shear signals, and FMm let atom database first applies into ECG signal processing. We compared with the three effect of signal processing based on three...
The aim of this study is to detect the ischemia-induced changes of heart rate variability (HRV) indices based on time-frequency analysis and to investigate the patterns of change when the duration of ischemia is concerned.
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