In this paper the main objective is to quantify and compare the instantaneous value of heart rate for normal breathing patterns during Meditation and Non Meditation conditions. This paper involves Analysis of Variance (ANOVA) technique for the analysis of the heart rate variability patterns during the meditative and non meditative states. The analysis is divided into three stages i.e. data acqu...

Electrocardiograms (ECGs) are signals that originate from the action of the human heart. The ECG is the key biosignal for aiding the clinical staff in disease diagnosis. The recognition and analysis of the ECG signals is a very important task. This could be difficult, because the size and form of these signals may change eventually and can be noised. ECG noise removal is complicated due to the ...

In this study, we developed a wearable electrocardiogram (ECG) sensor with human body communication (HBC) technology for vital data transmission in a car. The ECG signals were modulated with wideband pulse signals between 10 and 60 MHz based on an impulse radio (IR) scheme, which provides a data rate as high as 1.25 Mbps. To apply the HBC-based wearable ECG in a moving car, we employed a moving...

Wearable physiological monitoring systems have gained popularity in the recent years due to their ability to continuously monitor physiological signals, thereby making them suitable for home-healthcare applications. The electrocardiogram (ECG), phonocardiogram (PCG) and photoplethysmogram (PPG) signals have been studied and it has been observed that there is a correlation between the three sign...

The electrocardiographic (ECG) signal is a transthoracic manifestation of the electrical activity of the heart and is widely used in clinical applications. This chapter describes an unbiased linear adaptive filter (ULAF) to attenuate high-frequency random noise present in ECG signals. The ULAF does not contain a bias in its summation unit and the filter coefficients are normalized. During the a...

In this paper we study the compression techniques for electrocardiogram (ECG) signals based on Block Sorting Techniques. We introduce a new and faster block transformation than the Burrows and Wheeler Transformation (BWT), and later compare them for ECG data compression. We show that our algorithm yields better compression gain than the Burrows and Wheeler’s algorithm (BWA), Gzip and the Shorte...

Accurate electrocardiogram (ECG) parameters detection is an integral part of modern computerized ECG monitoring system. A growing concern that algorithms that diagnose ECG signals should be tested at different noise circumstances to verify algorithms’ reliability and efficiency of signal interpretation. This study investigates the accuracy and reliability of Hamilton-Tompkins (H-T) algorithm us...

Introduction Cardiovascular disease is a major cause of premature dying. If any patient is diagnosed at early stage of cardiovascular disease [(myocardial infarction (MI)], it may be possible to reverse disease process. Functional behavior of heart is represented by electrocardiogram (ECG), signals of which are quasiperiodic (Fig. 1). Various transform techniques (Fourier, wavelet etc.) are ine...

In a clinical study, a novel wireless electrocardiogram (ECG) recorder has been evaluated with regard to its ability to perform arrhythmia diagnostics. As the ECG recorder will detect a "non-standard" ECG signal, it has been necessary to compare those signals to "standard" ECG recording signals in order to evaluate the arrhythmia detection ability of the new system. Simultaneous recording of EC...