In this paper, we propose an effective compression method for electrocardiogram (ECG) signals. 1-D ECG signals are reconstructed to 2-D ECG data by period and complexity sorting schemes with image compression techniques to increase inter and intra-beat correlation. The proposed method added block division and mean period normalization techniques on top of conventional 2-D data ECG compression m...

Electrocardiograph (ECG) human identification has the potential to improve biometric security. However, improvements in ECG identification and feature extraction are required. Previous work has focused on single lead ECG signals. Our work proposes a new algorithm for human identification by mapping two-lead ECG signals onto a two-dimensional matrix then employing a sparse matrix method to proce...

--The purpose of this letter is to study a new ECG measurement by an annular FPC (flexible print circuit) electrode to the arm of the subject. This study attempts to use one FPC patch to measure ECG signals from a single-arm. The measurement system for the ECG circuit and analysis software was built to be able to measure and interpret the very weak and noisy ECG signals from the electrode. To c...

In this work, we apply the independent component analysis (ICA) on the extraction of artifacts from the electrocardio-graphic (ECG) signals. ECG analysis is not an easy task when artifacts (electrodes, muscle, breathing, etc) corrupts the ECG, hiding important information. If the mixed signals in the ECG recordings (heart signal and artifacts) are statistically independent, the ICA can blindly ...

Electrocardiogram (ECG) is an important biomedical signal for analyzing heart activity. Analysis of ECG becomes difficult if noise is augmented with the signal during acquisition. During recent years, several denoising techniques were analyzed within the field of signal processing. In this paper, non local means (NLM) filtering technique is explored for denoising the ECG signal. The noisy ECG s...

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...

Blind source separation (BSS) techniques are widely used to extract signals of interest from a mixture with other signals, such as extracting fetal electrocardiogram (ECG) signals from noninvasive recordings on the maternal abdomen. These BSS techniques, however, typically lack possibilities to incorporate any prior knowledge on the mixing of the source signals. Particularly for fetal ECG signa...

Even with the development of more advanced technology of ECG, there are still problems on interference to ECG signals. Many attempts have been made to detect and eliminate the source of noises and artifacts from the original ECG signals. Several studies have been done to observe and study the EMI effect, however, most of them only focus on the EMI effect of mobile phone during ECG acquisition. ...

Transmission techniques of biomedical signals through communication channels are currently an important issue in many applications related to clinical practice. These techniques can allow experts to make a remote assessment of the information carried by the signals, in a very cost-effective way. However, in many situations this process leads to a large volume of information. The necessity of ef...

An automatic configuration that can detect the position of R-waves, classify the normal sinus rhythm (NSR) and other four arrhythmic types from the continuous ECG signals obtained from the MIT-BIH arrhythmia database is proposed. In this configuration, a support vector machine (SVM) was used to detect and mark the ECG heartbeats with raw signals and differential signals of a lead ECG. An algori...