IoT technology has been recently adopted in the healthcare system to collect Electrocardiogram (ECG) signals for heart disease diagnosis and prediction. However, noises in collected ECG signals make the diagnosis and prediction system unreliable and imprecise. In this work, we have proposed a new lightweight approach to removing noises in collected ECG signals to perform precise diagnosis and p...

Nowadays, ICA based methods are widely used. However, ICA needs multiples channels for collecting electrocardiogram signals. One of the most significant advantages of utilizing ANFIS networks in FECG extraction is that the methods require only two record signals, one thoracic signal and one abdominal ECG signal. In the present work, ANFIS network is apply to extract the FECG signal from both EC...

In this paper, a new method to model ECG signals by means of "Predefined Personalized Signature and Envelope Functions" is presented. ECG signals are somewhat unique to a person. Moreover, it presents quasi-stationary behavior. Therefore in this work, on a frame basis, personal ECG signals Xi(t) is modeled by the form of Xi(t) ≈ Ciφi(t) αi(t). In this model, φi(t) is defined as the Personalized...

Biomedical signals can arise from one or many sources including heart, brains and endocrine systems. Multiple sources poses challenge to researchers which may have contaminated with artifacts and noise. The Biomedical time series signal like electroencephalogram (EEG), electrocardiogram (ECG), etc. The morphology of the cardiac signal is very important in most of diagnostics based on the ECG. T...

A recent trend in the field of biometrics is ECGbased, where electrocardiogram (ECG) signals are used as input to the biometric system. Previous work has shown that ECG has a good potential, which can be used alone as a biometric parameter or in combination with some other parameters for greater accuracy, due to its main key properties. This paper presents a study on the applicability of ECG si...

Electrocardiography (ECG) deals with the electrical activity of the heart. The condition of cardiac health is given by ECG and heart rate. A study of the non-linear dynamics of ECG signals for arrhythmia characterization is considered. The statistical analysis of the calculated features indicate that they differ significantly between normal heart rhythm and the different arrhythmia types and he...

Digital signal processing and data analysis are very often used methods in a biomedical engineering research. In this work, the descriptions of two detection algorithms for ECG characteristic points are enclosed. The detection algorithms presented in this work are based on Pan and Tompkins’ algorithm and wavelet transform for signal de-noising and detection of QRS complexes. In the first approa...

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 ...

The use of wearable recorders for long-term monitoring of physiological parameters has increased in the last few years. The ambulatory electrocardiogram (A-ECG) signals of five healthy subjects with four body movements or physical activities (PA)-left arm up down, right arm up down, waist twisting and walking-have been recorded using a wearable ECG recorder. The classification of these four PAs...