scholarly journals Evaluation of patient electrocardiogram datasets using signal quality indexing

2019 ◽  
Vol 8 (2) ◽  
pp. 519-526
Author(s):  
Nazrul Anuar Nayan ◽  
Hafifah Ab Hamid
Keyword(s):  
Vital Signs ◽  
Extraction Process ◽  
Motion Artifacts ◽  
Accurate Information ◽  
Signal Quality ◽  
Emergency Rooms ◽  
Ecg Signals ◽  
Detection Quality ◽  
Electrocardiogram Ecg

Electrocardiogram (ECG) is widely used in the hospital emergency rooms for detecting vital signs, such as heart rate variability and respiratory rate. However, the quality of the ECGs is inconsistent. ECG signals lose information because of noise resulting from motion artifacts. To obtain an accurate information from ECG, signal quality indexing (SQI) is used where acceptable thresholds are set in order to select or eliminate the signals for the subsequent information extraction process. A good evaluation of SQI depends on the R-peak detection quality. Nevertheless, most R-peak detectors in the literature are prone to noise. This paper assessed and compared five peak detectors from different resources. The two best peak detectors were further tested using MIT-BIH arrhythmia database and then used for SQI evaluation. These peak detectors robustly detected the R-peak for signals that include noise. Finally, the overall SQI of three patient datasets, namely, Fantasia, CapnoBase, and MIMIC-II, was conducted by providing the interquartile range (IQR) and median SQI of the signals as the outputs. The evaluation results revealed that the R-peak detectors developed by Clifford and Behar showed accuracies of 98% and 97%, respectively. By introducing SQI and choosing only high-quality ECG signals, more accurate vital sign information will be achieved.

A Design Exploration of Intelligent Wearable Companion of Smartphone for Fitness and Healthcare

2019 ◽  
Vol 33 (08) ◽  
pp. 1959023
Author(s):  
Wen Qi
Keyword(s):  
Wearable Devices ◽  
Motion Artifacts ◽  
Signal Quality ◽  
Ecg Signals ◽  
Analog Front End ◽  
Fitness Industry ◽  
Different Types ◽  
Electrocardiogram Ecg ◽  
Product Forms ◽  
Future Topics

Wearable devices are increasingly gaining more attentions in healthcare and fitness industry due to their potentials to measure valuable physiological signals on the move. There are many researchers who have proposed different types of designs that embed biosensors into miniature wearable devices. In this paper, we present a wearable companion that monitors the cardiac activities of a wearer with smartphone. The device makes use of a single, integrated biosensor that is designed with a unique analog front-end circuitry and a dedicated signal processing pipeline. In order to meet the requirements of possible but different user scenarios, three types of product forms are presented. The experimental results show that electrocardiogram (ECG) signals collected are valid and consistent through the systems. Future topics include adding extra algorithms to remove motion artifacts in order to achieve better signal quality in various settings and include wireless communication through 4G.

Accurate Detection of ECG Signals in ECG Monitoring Systems by Eliminating the Motion Artifacts and Improving the Signal Quality Using SSG Filter with DBE

2019 ◽  
Vol 29 (02) ◽  
pp. 2050024
Author(s):  
Mahesh B. Dembrani ◽  
K. B. Khanchandani ◽  
Anita Zurani
Keyword(s):  
Signal Analysis ◽  
Motion Artifact ◽  
Motion Artifacts ◽  
Signal Quality ◽  
Ecg Signal ◽  
Qrs Complex ◽  
Ecg Signals ◽  
Cardiac Disorders ◽  
Digital Processor ◽  
Ica Algorithm

The automatic recognition of QRS complexes in an Electrocardiography (ECG) signal is a critical step in any programmed ECG signal investigation, particularly when the ECG signal taken from the pregnant women additionally contains the signal of the fetus and some motion artifact signals. Separation of ECG signals of mother and fetus and investigation of the cardiac disorders of the mother are demanding tasks, since only one single device is utilized and it gets a blend of different heart beats. In order to resolve such problems we propose a design of new reconfigurable Subtractive Savitzky–Golay (SSG) filter with Digital Processor Back-end (DBE) in this paper. The separation of signals is done using Independent Component Analysis (ICA) algorithm and then the motion artifacts are removed from the extracted mother’s signal. The combinational use of SSG filter and DBE enhances the signal quality and helps in detecting the QRS complex from the ECG signal particularly the R peak accurately. The experimental results of ECG signal analysis show the importance of our proposed method.

scholarly journals TWO-LEAD JOINT DETECTION ALGORITHM OF QRS COMPLEXES IN ECG SIGNAL

2021 ◽  
Author(s):  
WANSONG XU ◽  
TIANWU CHEN ◽  
FANYU DU
Keyword(s):  
Detection Algorithm ◽  
Detection Accuracy ◽  
Ecg Signal ◽  
Joint Detection ◽  
Ecg Signals ◽  
Detection Algorithms ◽  
Threshold Adjustment ◽  
Current Algorithm ◽  
Electrocardiogram Ecg

Objective: The detection of QRS complexes is an important part of computer-aided analysis of electrocardiogram (ECG). However, most of the existing detection algorithms are mainly for single-lead ECG signals, which requires high quality of signal. If the signal quality decreases suddenly due to some interference, then the current algorithm is easy to cause misjudgment or missed detection. To improve the detection ability of QRS complexes under sudden interference, we study the QRS complexes information on multiple leads in-depth, and propose a two-lead joint detection algorithm of QRS complexes. Methods: Firstly, the suspected QRS complexes are screened on the main lead. For the suspected QRS complexes with low confidence and the complexes that may be missed, further accurate detection and joint judgment shall be carried out at the corresponding position of the auxiliary lead. At the same time, the adaptive threshold adjustment algorithm and backtracking mechanism are used to modify the detection results. Results: The proposed detection algorithm is validated using 48 ECG records of the MIT-BIH arrhythmia database, and achieves average detection accuracy of 99.71%, sensitivity of 99.88% and positive predictivity of 99.81%. Conclusion: The proposed algorithm has high accuracy, which can effectively deal with the sudden interference of ECG signal. Meanwhile, the algorithm requires small amount of computation, and can be embedded into hardware for real-time detection.

Cardiorespiratory monitoring in the delivery room using transcutaneous electromyography

2020 ◽  
pp. fetalneonatal-2020-319535
Author(s):  
Ruud W van Leuteren ◽  
Eline Kho ◽  
Cornelia G de Waal ◽  
Arjan B te Pas ◽  
Hylke H Salverda ◽  
...  
Keyword(s):  
Prospective Observational Study ◽  
Intraclass Correlation ◽  
Newborn Infants ◽  
Vital Signs ◽  
Poor Quality ◽  
Delivery Room ◽  
Signal Quality ◽  
Monitoring Tool ◽  
Diaphragm Activity

ObjectiveTo assess feasibility of transcutaneous electromyography of the diaphragm (dEMG) as a monitoring tool for vital signs and diaphragm activity in the delivery room (DR).DesignProspective observational study.SettingDelivery room.PatientsNewborn infants requiring respiratory stabilisation after birth.InterventionsIn addition to pulse oximetry (PO) and ECG, dEMG was measured with skin electrodes for 30 min after birth.Outcome measuresWe assessed signal quality of dEMG and ECG recording, agreement between heart rate (HR) measured by dEMG and ECG or PO, time between sensor application and first HR read-out and agreement between respiratory rate (RR) measured with dEMG and ECG, compared with airway flow. Furthermore, we analysed peak, tonic and amplitude diaphragmatic activity from the dEMG-based respiratory waveform.ResultsThirty-three infants (gestational age: 31.7±2.8 weeks, birth weight: 1525±661 g) were included.18%±14% and 22%±21% of dEMG and ECG data showed poor quality, respectively. Monitoring HR with dEMG was fast (median 10 (IQR 10–11) s) and accurate (intraclass correlation coefficient (ICC) 0.92 and 0.82 compared with ECG and PO, respectively). RR monitoring with dEMG showed moderate (ICC 0.49) and ECG low (ICC 0.25) agreement with airway flow. Diaphragm activity started high with a decreasing trend in the first 15 min and subsequent stabilisation.ConclusionMonitoring vital signs with dEMG in the DR is feasible and fast. Diaphragm activity can be detected and described with dEMG, making dEMG promising for future DR studies.

scholarly journals Electrocardiogram Baseline Wander Suppression Based on the Combination of Morphological and Wavelet Transformation Based Filtering

2019 ◽  
Vol 2019 ◽  
pp. 1-7 ◽  
Author(s):  
Xiang-kui Wan ◽  
Haibo Wu ◽  
Fei Qiao ◽  
Feng-cong Li ◽  
Yan Li ◽  
...  
Keyword(s):  
Realistic Model ◽  
Suppression Effect ◽  
Ecg Signals ◽  
Morphological Filtering ◽  
Baseline Wander ◽  
Waveform Distortions ◽  
Electrocardiogram Ecg ◽  
Morphology Filter ◽  
Better Than

One of the major noise components in electrocardiogram (ECG) is the baseline wander (BW). Effective methods for suppressing BW include the wavelet-based (WT) and the mathematical morphological filtering-based (MMF) algorithms. However, the T waveform distortions introduced by the WT and the rectangular/trapezoidal distortions introduced by MMF degrade the quality of the output signal. Hence, in this study, we introduce a method by combining the MMF and WT to overcome the shortcomings of both existing methods. To demonstrate the effectiveness of the proposed method, artificial ECG signals containing a clinical BW are used for numerical simulation, and we also create a realistic model of baseline wander to compare the proposed method with other state-of-the-art methods commonly used in the literature. The results show that the BW suppression effect of the proposed method is better than that of the others. Also, the new method is capable of preserving the outline of the BW and avoiding waveform distortions caused by the morphology filter, thereby obtaining an enhanced quality of ECG.

scholarly journals Performance Evaluation of Plain Weave and Honeycomb Weave Electrodes for Human ECG Monitoring

2017 ◽  
Vol 2017 ◽  
pp. 1-13 ◽  
Author(s):  
Xueliang Xiao ◽  
Sandeep Pirbhulal ◽  
Ke Dong ◽  
Wanqing Wu ◽  
Xi Mei
Keyword(s):  
Signal To Noise Ratio ◽  
Reference Electrode ◽  
Electrode Impedance ◽  
Ecg Signals ◽  
Skin Electrode ◽  
Transfer Unit ◽  
Long Time ◽  
Innovative Materials ◽  
Electrocardiogram Ecg

Long-time monitoring of physiological parameters can scrutinize human health conditions so as to use electrocardiogram (ECG) for diagnosis of some human’s chronic cardiovascular diseases. The continuous monitoring requires the wearable electrodes to be breathable, flexible, biocompatible, and skin-affinity friendly. Weave electrodes are innovative materials to supply these potential performances. In this paper, four conductive weave electrodes in plain and honeycomb weave patterns were developed to monitor human ECG signals. A wearable belt platform was developed to mount such electrodes for acquisition of ECG signals using a back-end electronic circuit and a signal transfer unit. The performance of weave ECG electrodes was evaluated in terms of skin-electrode contacting impedance, comfortability, ECG electrical characteristics, and signal fidelity. Such performances were then compared with the values from Ag/AgCl reference electrode. The test results showed that lower skin-electrode impedance, higher R-peak amplitude, and signal-to-noise ratio (SNR) value were obtained with the increased density of conductive filaments in weave and honeycomb weave electrode presented higher comfort but poorer signal quality of ECG. This study inspires an acceptable way of weave electrodes in long- and real-time of human biosignal monitoring.

VT/VF Detection Method Based on ECG Signal Quality Assessment

2018 ◽  
Vol 27 (11) ◽  
pp. 1850169 ◽  
Author(s):  
Borisav Jovanović ◽  
Srdan Milenković ◽  
Milan Pavlović
Keyword(s):  
Cardiac Arrhythmias ◽  
Signal Analysis ◽  
Detection Method ◽  
Signal Quality ◽  
Ecg Signals ◽  
Battery Charge ◽  
Time Domain Signal ◽  
Signal Parameters ◽  
Life Threatening ◽  
Electrocardiogram Ecg

Artefacts which are present in electrocardiogram (ECG) recordings distort detection of life-threatening arrhythmias such as ventricular tachycardia and ventricular fibrillation. The method examines single ECG lead and exploits time domain signal parameters for real-time detection of severe cardiac arrhythmias. The method is dedicated to implementation in mobile ECG telemetry systems, which are designed by using low-power microcontrollers, operating more than a week on a single battery charge. The method has been validated on publicly available databases and the results are presented. We verified our method on ECG signals obtained without pre-selection meaning that the noisy intervals were not omitted from signal analysis.

Removal of ECG Baseline Wander Using a Resting Cycle Template

2021 ◽  
Vol 10 (1) ◽  
pp. 45
Author(s):  
Eladio Altamira-Colado ◽  
Miguel Bravo-Zanoguera ◽  
Daniel Cuevas-González ◽  
Marco Reyna-Carranza ◽  
Roberto López-Avitia
Keyword(s):  
Spline Interpolation ◽  
Motion Artifact ◽  
Motion Artifacts ◽  
New Method ◽  
Daily Activities ◽  
Pass Filter ◽  
Ecg Signals ◽  
Baseline Wander ◽  
Low Amplitude ◽  
Electrocardiogram Ecg

The development of electrocardiogram (ECG) wearable devices has increased due to its applications on ambulatory patients. ECG signals provide useful information about the heart behavior, but when daily activities are monitored, motion artifacts are introduced producing saturation of the signal, thus losing the information. The typical resolution used to record ECG signals is of maximum 16-bit, which might not be enough to detect low-amplitude potentials and at the same time avoid saturation due to baseline wander, since this last issue demands a low-gain signal chain. A high-resolution provides a more detailed ECG signal under a low gain input, and if the signal is corrupted by motion artifact noise but is not saturated, it can be filtered to recover the signal of interest. In this work, a 24-bit ADC is used to record the ECG, and a new method, the rest ECG cycle template, is proposed to remove the baseline wander. This new method is compared to high-pass filter and spline interpolation methods in their ability to remove baseline wander. This new method presumes that a user is able to establish a rest ECG during his/her daily activities.

scholarly journals Real-time QRS detection using integrated variance for ECG gated cardiac MRI

2016 ◽  
Vol 2 (1) ◽  
pp. 255-258 ◽  
Author(s):  
Marcus Schmidt ◽  
Johannes W. Krug ◽  
Georg Rose
Keyword(s):  
Real Time ◽  
Cardiac Mri ◽  
Vital Signs ◽  
Peak Detection ◽  
Resonance Imaging ◽  
Qrs Detection ◽  
Ecg Signals ◽  
Integrated Variance ◽  
Magnetic Resonance Imaging Mri ◽  
Electrocardiogram Ecg

AbstractDuring magnetic resonance imaging (MRI), a patient’s vital signs are required for different purposes. In cardiac MRI (CMR), an electrocardiogram (ECG) of the patient is required for triggering the image acquisition process. However, a reliable QRS detection of an ECG signal acquired inside an MRI scanner is a challenging task due to the magnetohydrodynamic (MHD) effect which interferes with the ECG. The aim of this work was to develop a reliable QRS detector usable inside the MRI which also fulfills the standards for medical devices (IEC 60601-2-27). Therefore, a novel real-time QRS detector based on integrated variance measurements is presented. The algorithm was trained on ANSI/AAMI EC13 test waveforms and was then applied to two databases with 12-lead ECG signals recorded inside and outside an MRI scanner. Reliable results for both databases were achieved for the ECG signals recorded inside (DBMRI: sensitivity Se = 99.94%, positive predictive value +P = 99.84%) and outside (DBInCarT: Se = 99.29%, +P = 99.72%) the MRI. Due to the accurate R-peak detection in real-time this can be used for monitoring and triggering in MRI exams.

scholarly journals Platform for Analysis and Labeling of Medical Time Series

Sensors ◽  
2020 ◽  
Vol 20 (24) ◽  
pp. 7302
Author(s):  
Andrejs Fedjajevs ◽  
Willemijn Groenendaal ◽  
Carlos Agell ◽  
Evelien Hermeling
Keyword(s):  
Time Series ◽  
Software Tool ◽  
Motion Artifacts ◽  
Signal Quality ◽  
Wide Range ◽  
Characteristic Points ◽  
Automated Processing ◽  
User Friendly ◽  
Medical Signals ◽  
Electrocardiogram Ecg

Reliable and diverse labeled reference data are essential for the development of high-quality processing algorithms for medical signals, such as electrocardiogram (ECG) and photoplethysmogram (PPG). Here, we present the Platform for Analysis and Labeling of Medical time Series (PALMS) designed in Python. Its graphical user interface (GUI) facilitates three main types of manual annotations—(1) fiducials, e.g., R-peaks of ECG; (2) events with an adjustable duration, e.g., arrhythmic episodes; and (3) signal quality, e.g., data parts corrupted by motion artifacts. All annotations can be attributed to the same signal simultaneously in an ergonomic and user-friendly manner. Configuration for different data and annotation types is straightforward and flexible in order to use a wide range of data sources and to address many different use cases. Above all, configuration of PALMS allows plugging-in existing algorithms to display outcomes of automated processing, such as automatic R-peak detection, and to manually correct them where needed. This enables fast annotation and can be used to further improve algorithms. The GUI is currently complemented by ECG and PPG algorithms that detect characteristic points with high accuracy. The ECG algorithm reached 99% on the MIT/BIH arrhythmia database. The PPG algorithm was validated on two public databases with an F1-score above 98%. The GUI and optional algorithms result in an advanced software tool that allows the creation of diverse reference sets for existing datasets.

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