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Filtering of ECG signal is an essential step in ECG signal processing and analysis. Since ECG is a low amplitude biosignal, it is easily corrupted by external noises, and by the presence of other biosignals. The aim of filtering is to remove unwanted noise while preserving important characteristics of the signal. Various filtering techniques are available thus choosing the right filter for ECG denoising...
Wearable devices for real-time ECG monitoring and analysis require an accurate but simple QRS detection algorithm which does not consume too much computational load. Dual-threshold QRS detection techniques are one of the promising solutions to overcome this problem. This study investigates the performance and robustness of a dual-threshold QRS detection method under different levels of noise and physical...
A wearable electrocardiogram (ECG) monitoring device with a customized SoC is reported. The SoC amplifies the ECG signal from passive electrodes and then digitizes and transforms it into wavelet coefficients. A low-power microcontroller (MCU) and a radio frequency (RF) module in the device resolve and send the wavelet coefficients to a mobile platform. The mobile platform uses machine learning algorithms...
A wearable electrocardiogram (ECG) monitoring device with a customized SoC is reported. The SoC amplifies the ECG signal from passive electrodes and then digitizes and transforms it into wavelet coefficients. A low-power microcontroller (MCU) and a radio frequency (RF) module in the device resolve and send the wavelet coefficients to a mobile platform. The mobile platform uses machine learning algorithms...
This paper introduces a lifting double-wavelet algorithm for electrocardiogram signal denoising by using the improved threshold function in the lifting wavelet decomposition to deal with wavelet coefficients. The results, based on data from MIT-BIT arrhythmia database, show that noise can be eliminated effectively with lower distortion and higher signal-to-noise ratio compared with the single wavelet...
Signal processing a major tool used for ECG analysis and interpretation in today's life. In ECG signal processing is used to improve the measurement accuracy and reproducibility comparatively. Separating respiration signals from ECG is one way of obtaining knowledge related to respiration especially when specialized equipments are not used to monitor the respiration continuously. There are chances...
Some factors that have increased cardiovascular incidents are sedentary lifestyle, poor eating habits, smoking, stress; hence the importance of continuously monitor cardiac activity in people. This research proposes the implementation of a wireless system to monitor the heart allowing visualization of the electrocardiogram (ECG) on a mobile device via Bluetooth (BT) technology and Arduino UNO board...
Adaptive Noise Cancellers (ANCs) are used to remove noise from the cardiac signals. In remote health monitoring system signals must be free from artifacts. In the proposed paper an attempt has been made to present a new ANC using Normalized Variable Step Size Least Mean Squared (NVLMS) algorithm. Sign Regressor Algorithm can reduce Computational Complexity and also to maximize the normalization of...
This paper presents a noise-reconfigurable resistive feedback amplifier with current-reuse technique for fetal ECG monitoring. The proposed amplifier allows for both tuning of the noise level and changing the power consumption according to the signal properties, minimizing the total power consumption while satisfying all application requirements. The amplifier together with its amplitude detector...
Electrocardiogram (ECG) is a type of measuring the electrical activities of heart. Each section of ECG is necessary for the diagnosis of various cardiac problems. But the amplitude and time period of ECG signal is generally corrupted by various noises. After an analog ECG signal is transformed into digital format, appropriate digital filter can be utilized to repress the various kinds of noise like...
Techniques for monitoring ambulatory patients have advanced greatly over the past 10 years. The advent of pocket computing, in the form of cellular phone technology, being one of the prime drivers. Until recently there was a great functional deficit in the performance of the average portable microprocessor and that which was used in the personal desktop computer. Today, smart phones have 1GHz processors...
The performance and practicality of a scale-based ballistocardiogram (BCG) system for hemodynamic monitoring of astronauts on extended space missions was demonstrated. The system consists of a modified electronic weighing scale fitted with foot bindings to mechanically couple the subject to the scale. This system was tested on a recent series of parabolic flights in which scale-based and accelerometry-based...
Electrocardiography (ECG) can be used to monitor patients for myocardial ischemia, which is a precursor to myocardial infarction. Ambulatory ECG is often contaminated with motion artifact. In this paper, we investigate the effect of motion artifact on myocardial ischemia alarms and on estimates of the ECG signal quality. The presence of motion artifact in an ambulatory ECG leads to false identification...
The respiration rate provides important information about the health. Recently, contactless sensing devices are becoming popular. Methods based on a video-camera (web-camera) recording and subsequent signal processing are a good example. In this paper, we present a method for the extraction of respiration phases from the videosequence. We implemented a single-step Lucas-Kanade method for obtaining...
Body position changes (BPC), which are often manifested in the ECG as shifts in the electrical axis of the heart, result in ST changes, and thus, may be misclassified as ischemic events during ambulatory monitoring. We have developed a BPC detector by modeling shifts as changes in the Karhunen-Loève transform coefficients of the QRS complex and the ST-T waveform. The noise is assumed to have a Laplacian...
Non-invasive fetal health monitoring during pregnancy has become increasingly important. Recent advances in signal processing technology have enabled fetal monitoring during pregnancy, using abdominal ECG recordings. Ubiquitous ambulatory monitoring for continuous fetal health measurement is however still unfeasible due to the computational complexity of noise robust solutions. In this paper an ECG...
Monitoring of the heart rate can provide vital clinical information, but can, in specific situations, be complicated due to the low signal to noise ratio (SNR) of the available physiological signals. Several methods to enhance the SNR are known from literature, e.g. wavelet-based enhancement methods, but most of these methods require a priori information on the recorded signals and are only applicable...
A wireless ECG monitoring system is presented that is able to perform high-quality ECG signal acquisition, beat detection, and real time monitoring of skin-electrode impedance which can be used to monitor the presence of motion artefacts. The whole system consumes only 170μW while performing local beat detection. The beat detection algorithm was verified against the MIT-BIH arrhythmia database and...
Fetal Heart Rate (FHR) monitoring gives important information about the fetus health state during pregnancy. This paper presents a new prototype for remote fetal monitoring. The device will allow to monitor FHR in a domiciliary context and to send fetal ECG traces to a hospital facility, where clinicians can interpret them. In this way the mother could receive prompt feedback about fetal wellbeing...
An LMS-based algorithm to monitor fetal and maternal heart rate in real time was implemented and evaluated on a development platform. Hardware has three modules: dsPIC30F digital signal controller, a low-noise analog front end and a storage stage. They were evaluated using on-chip debugging tools and a patient simulator. Algorithm performance was tested using simulation tools and real data. Other...
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