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BACKGROUND Fast and accurate quality estimation of the electrocardiogram (ECG) signal is a relevant research topic that has attracted considerable interest in the scientific community, particularly due to its impact on tele-medicine monitoring systems, where the ECG is collected by untrained technicians. In recent years, a number of studies have addressed this topic, showing poor performance in...

The most recent improvement of biomedical signal processing, information technology and communication has brought a new measurement to the medical world. It is now possible to record an ECG signal with a convenient electrocardiograph trivial and able to convert a micro-computer in electrocardiograph with the possibility of a diagnostic aid for automatic analysis. At the present changing from a ...

With the technological advancements in field of tele-health monitoring, it is now possible to gather huge amount electro-physiological signals such as electrocardiogram (ECG). It therefore necessary develop models/algorithms that are capable analysing these massive data real-time. This paper proposes a deep learning model for real-time segmentation heartbeats. The proposed DENS-ECG algorithm, c...

Data compression is a useful process in tele-monitoring applications, which lesser number of bits are needed to represent the same data. In this work, run-time lossless single-channel Electrocardiogram (ECG) and Photoplethysmogram (PPG) signals proposed, maintaining all dominant features. The data first quantized using optimal quantization level, so that fewer it, low error. Then, second order ...

Abstract Introduction The search for markers that can serve as screening methods young practitioners of physical activity has always raised an intense discussion between pediatricians and cardiologists. Thus, the ideal investigation algorithm should identify patients at high risk also among asymptomatic be low cost to society. This would only possible by including a diagnostic method largely ac...