Cooperative sensors are a novel measurement architecture based on active dry electrodes that allows the acquisition of biopotential signals (e.g., electrocardiogram, ECG) on patients in a comfortable and easy-to-integrate manner. This paper starts by analyzing the classical methods for measuring multilead ECG signals. Based on these classical methods, we then briefly introduce the concept of co...

This study aims at proposing an efficient method for automated electrocardiography (ECG) artifact removal from surface electromyography (EMG) signals recorded from upper trunk muscles. Wavelet transform is applied to the simulated data set of corrupted surface EMG signals to create multidimensional signal. Afterward, independent component analysis (ICA) is used to separate ECG artifact componen...

Medical signals and images need special treatment especially when the data become bigger and bigger. One of the treatment that will be considered in this experiment is about the data compression. ECG (Electro Cardio Graph) signals will create very big data when the signals were collected in a long period of time. Several methods can be used to compress the ECG data. In this experiment we used n...

In this study, we investigated the difference between heart rate variability (HRV) derived from electrocardiogramic(ECG) signals and pulse rate variability (PRV) derived from photoplethysmographic(PPG) signals. Fourteen healthy subjects conducted the protocol: 10 min physiological signals including distal pulse wave on finger and ear from photoplethysmography (PPG), and heart beat from electroc...

In this paper we are to find the optimum multiwavelet for compression of electrocardiogram (ECG) signals. At present, it is not well known which multiwavelet is the best choice for optimum compression of ECG. In this work, we examine different multiwavelets on 24 sets of ECG data with entirely different characteristics, selected from MITBIH database. For assessing the functionality of the diffe...

BACKGROUND The presence of parasite interference signals could cause serious problems in the registration of ECG signals and many works have been done to suppress electromyogram (EMG) artifacts noises and disturbances from electrocardiogram (ECG). Recently, new developed techniques based on global and local transforms have become popular such as wavelet shrinkage approaches (1995) and time-freq...

The methods of Computational Intelligence (CI) including a framework of Granular Computing, open promising research avenues in the realm of processing, analysis and interpretation of biomedical signals. Similarly, they augment the existing plethora of “classic” techniques of signal processing. CI comes as a highly synergistic environment in which learning abilities, knowledge representation, an...

The problem of recognition and classification biomedical signals is a complex related to the interdisciplinary field computer science medicine. Within framework project implementation development new defibrillation equipment, it necessary solve problems analyzing electrocardiogram obtain diagnostic solution with possibility assigning specific condition pathological patient. This article present...