A survey on modern trends in ECG noise removal techniques

Chandran, Haritha; Ganesan, M.; Sumesh, E.P.

doi:10.1109/iccpct.2016.7530192

Cited by 41 publications

(12 citation statements)

References 13 publications

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“…Its recording dates back to the end of the 19th century. From that time, research addressed first the amplification of the signal, whose amplitude is in the µV range, and next to the design of filters that remove unwanted components (like powerline hum, or signals from body activity) [2].…”

Section: Related Work and Results Summarymentioning

confidence: 99%

Design of an Open Remote Electrocardiogram (ECG) Service

Ciuffoletti

2019

Future Internet

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Currently, the deployment of services for real-time delivery of an electrocardiogram to a remote site has a cost that prevents its widespread diffusion, which would contribute to saving lives with prevention, assistance and rescue efficiency. To fill this gap, we introduce the design of a remote electrocardiogram service that privileges open, low-cost options. The architecture is based on the HyperText Transfer Protocol (HTTP) and uses commercial off-the-shelf devices to implement the sensor on the patient’s side. The doctor uses a laptop browser to display the tracing, and a cloud computing instance connects the two using WebSockets. A prototype is built to evaluate overall performance, the power consumption of the patient’s side device, and the quality of rendering on doctor’s browser. The patient’s sensor prototype device is portable, and its power consumption is below 1 Watt, thus allowing a daylong autonomy when operated on batteries. Its cost is below 50$, and the required hardware is commercially available. The whole design is ready for on-field evaluation, and it is available in a public repository.

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Section: Related Work and Results Summarymentioning

confidence: 99%

Design of an Open Remote Electrocardiogram (ECG) Service

Ciuffoletti

2019

Future Internet

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“…Noise removal can be performed using various methods such as adaptive least mean squares (LMS) filtering, Kalman filtering, wavelet decomposition, bandpass filtering, etc. [ 34 , 35 ]. The complexity of the noise removal techniques increases depending on the purpose of the removal level of noise present.…”

Section: Discussionmentioning

confidence: 99%

Towards the Development of Nonlinear Approaches to Discriminate AF from NSR Using a Single-Lead ECG

Lee

Guo

Ravikumar

et al. 2020

Entropy

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Paroxysmal atrial fibrillation (Paro. AF) is challenging to identify at the right moment. This disease is often undiagnosed using currently existing methods. Nonlinear analysis is gaining importance due to its capability to provide more insight into complex heart dynamics. The aim of this study is to use several recently developed nonlinear techniques to discriminate persistent AF (Pers. AF) from normal sinus rhythm (NSR), and more importantly, Paro. AF from NSR, using short-term single-lead electrocardiogram (ECG) signals. Specifically, we adapted and modified the time-delayed embedding method to minimize incorrect embedding parameter selection and further support to reconstruct proper phase plots of NSR and AF heart dynamics, from MIT-BIH databases. We also examine information-based methods, such as multiscale entropy (MSE) and kurtosis (Kt) for the same purposes. Our results demonstrate that embedding parameter time delay ( τ ), as well as MSE and Kt values can be successfully used to discriminate between Pers. AF and NSR. Moreover, we demonstrate that τ and Kt can successfully discriminate Paro. AF from NSR. Our results suggest that nonlinear time-delayed embedding method and information-based methods provide robust discriminating features to distinguish both Pers. AF and Paro. AF from NSR, thus offering effective treatment before suffering chaotic Pers. AF.

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“…A review of heart monitoring systems comprising details of their functions, progress, and limitations is provided in [5] based on several modules, namely body sensors, analog to digital conversion and compression, analysis and classification, wireless transmission, and signal conditioning. A survey on various denoising techniques for ECG signals was presented in [6]. Work in [7] carries out the study comparing several wearable sensors utilized for ECG measurements while also reviewing various technical hurdles encountered during their development.…”

Section: Existing Survey Workmentioning

confidence: 99%

Advances of ECG Sensors from Hardware, Software and Format Interoperability Perspectives

et al. 2021

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It is well-known that cardiovascular disease is one of the major causes of death worldwide nowadays. Electrocardiogram (ECG) sensor is one of the tools commonly used by cardiologists to diagnose and detect signs of heart disease with their patients. Since fast, prompt and accurate interpretation and decision is important in saving the life of patients from sudden heart attack or cardiac arrest, many innovations have been made to ECG sensors. However, the use of traditional ECG sensors is still prevalent in the clinical settings of many medical institutions. This article provides a comprehensive survey on ECG sensors from hardware, software and data format interoperability perspectives. The hardware perspective outlines a general hardware architecture of an ECG sensor along with the description of its hardware components. The software perspective describes various techniques (denoising, machine learning, deep learning, and privacy preservation) and other computer paradigms used in the software development and deployment for ECG sensors. Finally, the format interoperability perspective offers a detailed taxonomy of current ECG formats and the relationship among these formats. The intention is to help researchers towards the development of modern ECG sensors that are suitable and approved for adoption in real clinical settings.

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A survey on modern trends in ECG noise removal techniques

Cited by 41 publications

References 13 publications

Design of an Open Remote Electrocardiogram (ECG) Service

Design of an Open Remote Electrocardiogram (ECG) Service

Towards the Development of Nonlinear Approaches to Discriminate AF from NSR Using a Single-Lead ECG

Advances of ECG Sensors from Hardware, Software and Format Interoperability Perspectives

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