scholarly journals Comparison of Active Electrode Materials for Non-Contact ECG Measurement

Sensors ◽  
2019 ◽  
Vol 19 (16) ◽  
pp. 3585 ◽  
Author(s):  
Shun Peng ◽  
Ke Xu ◽  
Wei Chen
Keyword(s):  
Electrode Materials ◽  
Ecg Monitoring ◽  
Active Electrode ◽  
Ecg Signals ◽  
Mode Decomposition ◽  
Flexible Printed Circuit ◽  
Conductive Textile ◽  
Quality Indexes

For long-term and more convenience electrocardiograph (ECG) monitoring, an active- electrode-based ECG monitoring system, which can measure ECG through clothes, is proposed in this paper. The hardware of the system includes active electrodes, signal processing and data transmission modules and the software mainly includes a denoising algorithm based on empirical mode decomposition (EMD). Then the proposed system was verified using the comparison of the ECG signals measured synchronously by active electrodes and Ag/AgCl electrodes. In addition, three flexible materials, including conductive textile, copper foil tape and a flexible printed circuit (FPC) are developed for the sensing layer with active electrodes. To compare the performance of these three materials for the sensing layer, the ECG signals of 10 subjects were measured by different materials in three postures and several indexes for quality evaluation were calculated. Results show that effective and clear ECG waveforms can be measured by all three kinds of materials and the quality of ECG signals measured by FPC is the best by conducting a significant t-test for signal quality indexes of three materials.

scholarly journals Unreadable Segment Recognition of Single-Lead ECG Signals Based on XGBoost: Fuision of Shannon Energy Envelope and Empirical Mode Decomposition

2021 ◽  
Author(s):  
Hanshuang Xie ◽  
Jiayi Yan ◽  
Huaiyu Zhu ◽  
Qineng Cao ◽  
Yamin Liu ◽  
...  
Keyword(s):  
Empirical Mode Decomposition ◽  
Error Rate ◽  
Wearable Devices ◽  
Ecg Signals ◽  
Mode Decomposition ◽  
Shannon Energy ◽  
Analysis System ◽  
Fold Cross Validation

The quality of ECG signals is commonly affected by severe noise, especially for the single-lead ECG signals acquired from long-term wearable devices. Recognizing and ignoring these interfered signals can reduce the error rate of automatic ECG analysis system, and in addition, improve the efficiency of cardiologists. Based on XGBoost classifier, we propose an unreadable ECG segment recognition method using features extracted through Shannon Energy Envelope (SEE) and Empirical Mode Decomposition (EMD). An unreadable CarePatchTM ECG patch database is established, containing 8169 readable segments and 6114 unreadable segments with a length of 10 seconds. The XGBoost with 5-fold cross-validation is applied and obtained an accuracy of 99.51+/-0.15%. In conclusion, SSE and EMD features contribute to the unreadable segments recognition and alleviate the misdiagnosis of abnormal rhythms.

scholarly journals A Wearable Electrocardiogram Telemonitoring System for Atrial Fibrillation Detection

Sensors ◽  
2020 ◽  
Vol 20 (3) ◽  
pp. 606 ◽  
Author(s):  
Minggang Shao ◽  
Zhuhuang Zhou ◽  
Guangyu Bin ◽  
Yanping Bai ◽  
Shuicai Wu
Keyword(s):  
Atrial Fibrillation ◽  
Ecg Monitoring ◽  
Web Browser ◽  
Ecg Signals ◽  
Cloud Server ◽  
Android App ◽  
Electrocardiogram Ecg ◽  
The Web ◽  
Ecg Data

In this paper we proposed a wearable electrocardiogram (ECG) telemonitoring system for atrial fibrillation (AF) detection based on a smartphone and cloud computing. A wearable ECG patch was designed to collect ECG signals and send the signals to an Android smartphone via Bluetooth. An Android APP was developed to display the ECG waveforms in real time and transmit every 30 s ECG data to a remote cloud server. A machine learning (CatBoost)-based ECG classification method was proposed to detect AF in the cloud server. In case of detected AF, the cloud server pushed the ECG data and classification results to the web browser of a doctor. Finally, the Android APP displayed the doctor’s diagnosis for the ECG signals. Experimental results showed the proposed CatBoost classifier trained with 17 selected features achieved an overall F1 score of 0.92 on the test set (n = 7270). The proposed wearable ECG monitoring system may potentially be useful for long-term ECG telemonitoring for AF detection.

scholarly journals A Long-Term, Portable ECG Patch Monitor Based on Flexible Dry Electrode

2022 ◽  
Author(s):  
Hao Chu ◽  
Chenxi Yang ◽  
Yantao Xing ◽  
Jianqing Li ◽  
Chengyu Liu
Keyword(s):  
Electrode Impedance ◽  
Ecg Monitoring ◽  
High Quality ◽  
Ecg Signals ◽  
Skin Electrode ◽  
Rr Interval ◽  
Dry Electrodes ◽  
Dry Electrode ◽  
And Storage

Abstract PurposeLong-term electrocardiogram (ECG) monitoring is an essential approach for the early diagnosis of cardiovascular diseases. Flexible dry electrodes that contains electrolyte without water could be a potential substitution of wet electrodes for long-term ECG monitoring. Therefore, this paper developes a long-term, portable ECG patch based on flexible dry electrodes, namely SEUECG-100.MethodA device consists of analog-front-end acquisition, data acquisition, and storage modules is developed and tested. An impedance test was conducted to compare the skin-electrode impedance of the flexible dry electrode and the Ag/AgCl wet electrode. The ECG signals were simutanously collected from the same subject using the SEUECG-100 and Shimmer device , which were then compared and analyzed from the perspective of ECG morphology, RR interval, and signal quality indices (SQI).ResultsThe experimental results reveal that the flexible dry electrode has the characteristics of low skin-electrode impedance. SEUECG-100 could collect high-quality ECG signals. The ECG signals collected by the two devices have a high RR interval correlation (r=0.999). SQI results show that SEUECG-100 is better than the Shimmer device in overcoming baseline drift. Long-term ECG acquisition and storage experiments show that SEUECG-100 could collect ECG signals with good stability and high reliability.ConclusionThe implementation of the proposed system design with dry electrodes could can effectively record long-term ECG monitoring with high quality in comparison to systems with wet electrodes from both impedance characteristics and signal morphology aspects.

scholarly journals A Wearable Device for Online and Long-Term ECG Monitoring

2018 ◽  
Author(s):  
Marco Longoni ◽  
Diego Carrera ◽  
Beatrice Rossi ◽  
Pasqualina Fragneto ◽  
Marco Pessione ◽  
...  
Keyword(s):  
Sparse Coding ◽  
Online Monitoring ◽  
Large Datasets ◽  
Wearable Device ◽  
Ecg Monitoring ◽  
Ecg Signals ◽  
Everyday Activities ◽  
Long Term Monitoring ◽  
Term Monitoring

We present a prototype wearable device able to perform online and long-term monitoring of ECG signals, and detect anomalous heartbeats such as arrhythmias. Our solution is based on user-specific dictionaries which characterizes the morphology of normal heartbeats and are learned every time the device is positioned. Anomalies are detected via an optimized sparse coding procedure, which assesses the conformance of each heartbeat to the user-specific dictionary. The dictionaries are adapted during online monitoring, to track heart rate variations occurring during everyday activities. Perhaps surprisingly, dictionary adaptation can be successfully performed by transformations that are user-independent and learned from large datasets of ECG signals.

scholarly journals Development of an Algorithm for Clustering Cardiac ECG Signals with Post-Correction for Long-Term ECG Monitoring

2021 ◽  
Vol 24 (2) ◽  
pp. 68-77
Author(s):  
I. A. Kondratyeva ◽  
A. S. Krasichkov ◽  
O. A. Stancheva ◽  
E. Mbazumutima ◽  
F. Shikema ◽  
...  
Keyword(s):  
Experimental Testing ◽  
Ecg Monitoring ◽  
Software Module ◽  
Ecg Signals ◽  
Synchronization Errors ◽  
Special Software ◽  
Deconvolution Problem ◽  
Cardiac Signals ◽  
Medical University

Introduction. The most common method for diagnosing cardiovascular diseases is the method of ECG monitoring. In order to facilitate the analysis of the obtained monitorograms, special software solutions for automated ECG processing are required. One possible approach is the use of algorithms for automated ECG processing. Such algorithms perform  clustering of cardiac signals by dividing the ECG into complexes of similar cardiac signals. The most representative complexes obtained by statistical averaging are subject to further analysis.Aim. Development of an algorithm for automated ECG processing,  which performs clustering of cardiac signals by dividing the ECG into complexes of similar cardiac signals.Materials and methods. Experimental testing of the developed software was carried out using patient records provided by the Pavlov First State Medical University of St  Petersburg. The software module was implemented in the MatLab environment.Results. An algorithm for clustering cardiac signals with post-correction for the tasks of long-term ECG monitoring and a software module on its basis were proposed.Conclusion.  The presence of a small number of reference cardiac signal complexes, obtained through ECG processing using the proposed algorithm, allows physicians to optimize the process of ECG analysis. The as- obtained information serves as a basis for assessing dynamic changes in the shape and other parameters of cardiac signals for both a particular patient and groups of patients. The paper considers the effect of synchronization errors of clustered cardiac signals on the shape of the averaged cardiac complex. The classical solution to the deconvolution problem leads to significant errors in finding an estimate of the true form of a cardiac signal complex. On the basis of analytical calculations, expressions were obtained for the correction of clustered cardiac signals. Such correction was shown to reduce clusterization errors associated with desynchronization, which creates a basis for investigating the fine structure of ECG signals.

scholarly journals Patient-Specific Detection of Atrial Fibrillation in Segments of ECG Signals using Deep Neural Networks

2019 ◽  
Vol 30 (1) ◽  
pp. 45-58 ◽  
Author(s):  
Jeyson A. Castillo ◽  
Yenny C. Granados ◽  
Carlos Augusto Fajardo Ariza
Keyword(s):  
Atrial Fibrillation ◽  
Computational Cost ◽  
Patient Specific ◽  
Specific Patient ◽  
Final Model ◽  
Ecg Signals ◽  
Sensitivity Specificity ◽  
Memory Resources

Atrial Fibrillation (AF) is the most common cardiac arrhythmia worldwide. It is associated with reduced quality of life and increases the risk of stroke and myocardial infarction. Unfortunately, many cases of AF are asymptomatic and undiagnosed, which increases the risk for the patients. Due to its paroxysmal nature, the detection of AF requires the evaluation, by a cardiologist, of long-term ECG signals. In Colombia, it is difficult to have access to an early diagnosis of AF because of the associated costs to the detection and the geographical distribution of cardiologists. This work is part of a macro project that aims to develop a specific-patient portable device for the detection of AF. This device will be based on a Convolutional Neural Network (CNN). We aim to find a suitable CNN model, which later could be implemented in hardware. Diverse techniques were applied to improve the answer regarding accuracy, sensitivity, specificity, and precision. The final model achieves an accuracy of , a specificity of , a sensitivity of  and a precision of . During the development of the model, the computational cost and memory resources were taking into account in order to obtain an efficient hardware model in a future implementation of the device.

A Wi-Fi IoT prototype for ECG monitoring exploiting a novel Compressed Sensing method

ACTA IMEKO ◽  
2020 ◽  
Vol 9 (2) ◽  
pp. 38
Author(s):  
Eulalia Balestrieri ◽  
Pasquale Daponte ◽  
Luca De Vito ◽  
Francesco Picariello ◽  
Sergio Rapuano ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Compressed Sensing ◽  
Battery Life ◽  
Ecg Signal ◽  
Ecg Monitoring ◽  
Ecg Signals ◽  
Reconstruction Quality ◽  
Acquisition Device ◽  
Iot Devices

<p><span lang="EN-US">The paper presents an Internet of Things (IoT) prototype which consists of a data acquisition device wirelessly connected to Internet via Wi-Fi, for continuous electrocardiogram (ECG) monitoring. The proposed system performs a novel Compressed Sensing (CS) based method on ECG signal with the aim of reducing the amount of transmitted data, thus realizing an efficient way to increase the battery life of such devices. For the assessment of the energy consumption of the device, an experimental setup was arranged and its description is presented. The evaluation of the reconstruction quality of the ECG signal in terms of Percentage of Root-mean-squared Difference (PRD</span><span lang="EN-US">) is reported for several Compression Ratios (CRs</span><span lang="EN-US">). The obtained experimental results clearly demonstrate the robustness and usefulness of the Wi-Fi based IoT devices adopting the considered CS-method for data compression of ECG signals. Furthermore, it allows reducing the energy consumption of the IoT device, by increasing the CR</span><span lang="EN-US">, without significantly degrading the quality of the reconstructed ECG signal.</span></p>

scholarly journals Development of a model of electric impedance in the contact between the skin and a capacitive active electrode when measuring electrocardiogram in combustiology

2021 ◽  
Vol 2 (5 (110)) ◽  
pp. 32-38
Author(s):  
Arsen Savchuk
Keyword(s):  
Saline Solution ◽  
Ecg Signal ◽  
Active Electrode ◽  
Modified Model ◽  
Physiological Processes ◽  
Proposed Model ◽  
Electrode Contact ◽  
Capacitive Electrode

Long-term ECG (electrocardiogram) measurement in patients with burns is a complicated problem since the overlapping of surface contact electrodes can lead to additional injuries. The possibility of ECG recording in patients with burns using capacitive electrodes was not proved, and there are no models of the electrode contact with a patient’s body while rehabilitation means are used. In this paper, the model of the contact between capacitive electrodes and the skin was modified and the circuit model of the contact: skin – bandages (saline solution) – film – active capacitive electrode, was described. The influence of the parameters of a capacitive electrode on the amplitude-frequency characteristics (AFC) of the contact of an electrode with skin was assessed. It was found that contact capacitance is crucial to obtain a high-quality ECG signal. The parameters of the impedance of bandages, saline solution, a dielectric film were calculated, and their effect on the AFC was studied. Based on the modified model, the AFC contact was modeled taking into consideration all the calculated parameters; it was found that the resulting AFC of the contact corresponds to the frequency range of the ECG signal. Analysis of the calculations proves the possibility of using capacitive electrodes when applying various rehabilitation means. It was found that at a change in the impedance of the saline solution from 0.1 gigaohms to 1 gigaohm, the changes in the AFC of the contact are not crucial for the final quality of the received signal. All calculations were carried out by modeling in the Qucs environment (ngspice SPICE). Simulation results can be used in the development of new types of capacitive electrocardiographic electrodes. The proposed model can be used to study other wound covers, as well as to model physiological processes when putting artificial skin and wound covers

scholarly journals Evaluation of dry textile electrodes for long-term electrocardiographic monitoring

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Milad Alizadeh-Meghrazi ◽  
Binbin Ying ◽  
Alessandra Schlums ◽  
Emily Lam ◽  
Ladan Eskandarian ◽  
...  
Keyword(s):  
Electrode Materials ◽  
Performance Metrics ◽  
Evaluation Procedure ◽  
Electrode Impedance ◽  
Ecg Signals ◽  
Skin Electrode ◽  
Electrocardiographic Monitoring ◽  
Textile Electrodes ◽  
Dry Electrode

Abstract Background Continuous long-term electrocardiography monitoring has been increasingly recognized for early diagnosis and management of different types of cardiovascular diseases. To find an alternative to Ag/AgCl gel electrodes that are improper for this application scenario, many efforts have been undertaken to develop novel flexible dry textile electrodes integrated into the everyday garments. With significant progresses made to address the potential issues (e.g., low signal-to-noise ratio, high skin–electrode impedance, motion artifact, and low durability), the lack of standard evaluation procedure hinders the further development of dry electrodes (mainly the design and optimization). Results A standard testing procedure and framework for skin–electrode impedance measurement is demonstrated for the development of novel dry textile electrodes. Different representative electrode materials have been screen-printed on textile substrates. To verify the performance of dry textile electrodes, impedance measurements are conducted on an agar skin model using a universal setup with consistent frequency and pressure. In addition, they are demonstrated for ECG signals acquisition, in comparison to those obtained using conventional gel electrodes. Conclusions Dry textile electrodes demonstrated similar impedance when in raised or flat structures. The tested pressure variations had an insignificant impact on electrode impedance. Looking at the effect of impedance on ECG signals, a noticeable effect on ECG signal performance metrics was not observed. Therefore, it is suggested that impedance alone is possibly not the primary indicator of signal quality. As well, the developed methods can also serve as useful guidelines for future textile dry-electrode design and testing for practical ECG monitoring applications.

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