Electrocardiogram Acquisition System Research Articles

Comparison of quantifiable electrocardiographic changes associated with severe hyperkalemia

BackgroundHyperkalemia (HK) is a life-threatening condition that is frequently evaluated by electrocardiogram (ECG). ECG changes in severe HK (≥ 6.3 mEq/L) are not well-characterized. This study sought to compare and correlate ECG metrics in severe HK to baseline normokalemic ECGs and serum potassium. MethodsA retrospective analysis of 340 severe HK encounters with corresponding normokalemic ECGs was performed. ResultsVarious ECG metrics were analyzed. P wave amplitude in lead II, QRS duration, T wave slope, ratio of T wave amplitude: duration, and ratios of T wave: QRS amplitudes were significantly different between normokalemic and HK ECGs. P wave amplitude attenuation in lead II correlated better with serum potassium than in V1. T wave metrics that incorporated both T wave and QRS amplitudes correlated better than metrics utilizing T wave metrics alone. ConclusionMultiple statistically significant and quantifiable differences among ECG metrics were observed between normokalemic and HK ECGs and correlated with increasing degrees of serum potassium and along the continuum of serum potassium. When incorporated into a logistic regression model, the ability to distinguish HK versus normokalemia on ECG improved significantly. These findings could be integrated into an ECG acquisition system that can more accurately identify severe HK.

Wireless CardioS framework for continuous ECG acquisition

A first-level textile-based electrocardiogram (ECG) monitoring system referred to as “CardioS” (cardiac sensor) for continuous health monitoring applications is proposed in this study to address the demand for resource-constrained environments. and the signal quality assessment of a wireless CardioS was studied. The CardioS consists of a Lead-I ECG signal recorded wirelessly using silver-plated nylon woven (Ag-NyW) dry textile electrodes to compare the results of wired wearable Ag-NyW textile electrode-based ECG acquisition system and CardioS. The effect of prolonged usage of Ag-NyW dry electrodes on electrode impedance was tested in the current work. In addition, electrode half-cell potential was measured to validate the range of Ag-NyW dry electrodes for ECG signal acquisition. Further, the quality of signals recorded by the proposed wireless CardioS framework was evaluated and compared with clinical disposable (Ag–AgCl Gel) electrodes. The signal quality was assessed in terms of mean magnitude coherence spectra, signal cross-correlation, signal-to-noise-band ratio (S band/N band), crest factor, low and high band powers and power spectral density. The experimental results showed that the impedance was increased by 2.5–54.6% after six weeks of continuous usage. This increased impedance was less than 1 MΩ/cm2, as reported in the literature. The half-cell potential of the Ag-NyW textile electrode obtained was 80 mV, sufficient to acquire the ECG signal from the human body. All the fidelity parameters measured by Ag-NyW textile electrodes were correlated with standard disposable electrodes. The cardiologists validated all the measurements and confirmed that the proposed framework exhibited good performance for ECG signal acquisition from the five healthy subjects. As a result of its low-cost architecture, the proposed CardioS framework can be used in resource-constrained environments for ECG monitoring.

Enhancing Digital Filtering to Electrocardiogram Analysis: Butterworth Filter Application

The electrocardiogram (ECG) of the human body is an important basis in heart function as well as the diagnosis of cardiovascular diseases, which has a very vital role in clinical diagnosis. Obtaining high-quality ECG signals with a portable remote ECG acquisition system is a big challenge given limited resources. According to the World Health Organization (WHO), disorders of the cardiovascular system still rank high, causing about 31% of deaths globally. This is because the symptoms of cardiovascular disease cannot be seen directly, but rather by conducting an electrocardiograph (ECG) examination. The purpose of this research is to record the electrical signals of the heart by comparing the 2nd order AD8232 module analogue filter with the 8th order Butterworth digital filter which is a better signal for easier reading. This research uses a multiplexer circuit for switching leads, AD8232 ECG module, 50Hz notch filter circuit, non-inverting amplifier, adder, Arduino Mega 2560, USB module, and an application to display digital signals, namely Delphi 7. Signal acquisition is done by monitoring for one minute. Data collection was carried out with 5 respondents 5 times on each lead. The results of the data collection can be concluded that 80% of digital filters display smoother signals for ECG signals than analogue filters

Accurate and Reliable Assessment of Heart Rate in Real-Life Clinical Settings Using an Imaging Photoplethysmography.

Remote photoplethysmography imaging (rPPGc) is a new method measuring essential parameters, such as heart rate (HR), which uses a video camera during teleconsultation. Our work aimed to evaluate the accuracy of such remote measurements compared with existing contact point measurement methods in real-life clinical settings. The prospective hospital-based study recruited 1045 patients who required a pulmonary function test. For each patient, measurements of HR using a standard electrocardiogram acquisition system (gold standard) were carried out concomitantly with the measurements made by the rPPGc system (Caducy v1.0.0) taken within a 60 s timeframe. Age, gender, and skin phototype were collected. We performed an intraclass coefficient correlation (ICC) and Bland–Altman plotting to determine the accuracy and precision of the rPPGc algorithm readings. We achieved measurement of HR using the two methods in 963 patients. The ICC measured at a 60 s timeframe, and when we compared the rPPGc with the gold standard, it had a 95% confidence interval (CI95) value of 0.886 [0.871:0.899]. In all, 94.6% (n = 911) patients showed promising results with a CI95 in Bland–Altman plotting. Fifty-two measurements were discordant, and further analysis established the method’s accuracy at 96.2%. Our results described a good accuracy and correlation between the rPPGc system and the gold standard, thus paving the way for more precise care via telemedicine.

Effects of Alzheimer's disease of varying severity on cardiac and autonomic function.

Alzheimer’s disease (AD) is one of the most common neurodegenerative diseases in the elderly. The aim of this study was to explore the effects of AD on cardiac function and autonomic nervous function, and the feasibility of electrocardiogram (ECG) in monitoring the development of AD. APP/PS1 double transgenic mice were used in the Morris water maze (MWM) experiment to evaluate the changes of cognitive ability of AD mice, then the non-invasive ECG acquisition system was used and the changes of ECG intervals and heart rate variability (HRV) were analyzed. AD mice already had cognitive dysfunction at the age of 5 months, reaching the level of mild dementia, and the degree of dementia increased with the course of disease. There were no significant changes in ECG intervals in the AD group at each month. The mean square of successive RR interval differences, percentage of intervals >6 ms different from preceding interval, and normalized high frequency power component in the AD group were decreased and low-to-high frequency power ratio and normalized low frequency power component were increased. Combined with the results of the MWM, it was shown that the regulation mechanism of sympathetic and parasympathetic nerves in mice was already imbalanced in early stage AD, which was manifested as the increase of excessive activity of sympathetic nerves and the inhibition of parasympathetic activities. Therefore, ECG-based analysis of HRV may become a means of daily monitoring of AD and provide an auxiliary basis for clinical diagnosis.

A Multi-channel ECG Acquisition System Based on FPGA

To collect accurate human Electrocardiogram (ECG) signal in complex scenarios and use them for subsequent disease pathology analysis by our laboratory team, we have designed a multi-channel acquisition system with adjustable gain, easy portability, and adaptability to most applications. The whole acquisition system is divided into the Electrode Group, Analog Front End (AFE), and the Data Storage System(DSS). The AFE uses a secondary amplification circuit as well as band-pass filtering and notch filtering circuits. The data storage side is an FPGA-based system design that realizes the functions including AD conversion, real-time display, and storage of data. Experiments show that this system can realize multi-channel and portable acquisition and storage of ECG signal under complex scenarios.

Two-Electrode ECG for Ambulatory Monitoring with Minimal Hardware Complexity.

This article introduces a two-electrode ground-free electrocardiogram (ECG) with minimal hardware complexity, which is ideal for wearable battery-powered devices. The main issue of ground-free measurements is the presence of noise. Therefore, noise suppression methods that can be employed for a two-electrode ECG acquisition system are discussed in detail. Experimental measurements of a living subject and patient simulator are used to investigate and compare the performance of the three proposed methods utilizing the ADS1191 analogue front-end for biopotential measurements. The resulting signals recorded for the simulator indicate that all three methods should be suitable for suppressing power-line noise. The Power Spectral Density (PSD) of the signals measured for a subject exhibits differences across methods; the signal power at 50 Hz is −28, −24.8, and −26 dB for the first, second, and third method, respectively. The digital postprocessing of measured signals acquired a high-quality ECG signal comparable to that of three-electrode sensing. The current consumption measurements demonstrate that all proposed two-electrode ECG solutions are appropriate as a battery-powered device (current consumption < 1.5 mA; sampling rate of 500 SPS). The first method, according to the results, is considered the most effective method in the suppression of power-line noise, current consumption, and hardware complexity.

A 2.64- μW 71-dB SNDR Discrete-Time Signal-Folding Amplifier for Reducing ADC's Resolution Requirement in Wearable ECG Acquisition Systems.

This paper presents the design of a low-power discrete-time signal-folding amplifier intended for use in place of programmable-gain amplifiers (PGA) in electrocardiogram (ECG) acquisition systems. The amplifier provides a fixed high gain while preventing output signal saturation even with rail-to-rail inputs, thanks to the proposed discrete-time signal folding technique; the fixed gain eliminates the need of gain-control circuitry while the high gain helps relax the resolution requirement of the analog-to-digital converter (ADC) that follows, thus resulting in lower power consumption and design complexity for the ADC. Fabricated in a standard 0.18- μm CMOS process, the amplifier occupies an active area of 0.254 mm2 and consumes 2.64 μW from a 1.2-V supply voltage. While amplifying a rail-to-rail input (2.4 Vpp differential) with a gain of 17.8V/V, the amplifier achieves a signal-to-noise-plus-distortion ratio (SNDR) of 71dB, thus making it very attractive for high-fidelity ECG recording amid large input interferences.

A Low-Power High-Data-Transmission Multi-Lead ECG Acquisition Sensor System.

This study presents a low-power multi-lead wearable electrocardiogram (ECG) signal sensor system design that can simultaneously acquire the electrocardiograms from three leads, I, II, and V1. The sensor system includes two parts, an ECG test clothing with five electrode patches and an acquisition device. Compared with the traditional 12-lead wired ECG detection instrument, which limits patient mobility and needs medical staff assistance to acquire the ECG signal, the proposed vest-type ECG acquisition system is very comfortable and easy to use by patients themselves anytime and anywhere, especially for the elderly. The proposed study incorporates three methods to reduce the power consumption of the system by optimizing the micro control unit (MCU) working mode, adjusting the radio frequency (RF) parameters, and compressing the transmitted data. In addition, Huffman lossless coding is used to compress the transmitted data in order to increase the sampling rate of the acquisition system. It makes the whole system operate continuously for a long period of time and acquire abundant ECG information, which is helpful for clinical diagnosis. Finally, a series of tests were performed on the designed wearable ECG device. The results have demonstrated that the multi-lead wearable ECG device can collect, process, and transmit ECG data through Bluetooth technology. The ECG waveforms collected by the device are clear, complete, and can be displayed in real-time on a mobile phone. The sampling rate of the proposed wearable sensor system is 250 Hz per lead, which is dependent on the lossless compression scheme. The device achieves a compression ratio of 2.31. By implementing a low power design on the device, the resulting overall operational current of the device is reduced by 37.6% to 9.87 mA under a supply voltage of 2.1 V. The proposed vest-type multi-lead ECG acquisition device can be easily employed by medical staff for clinical diagnosis and is a suitable wearable device in monitoring and nursing the off-ward patients.

A 0.3 V, 56 dB DR, 100 Hz fourth order low-pass filter for ECG acquisition system

This paper proposes an extremely low voltage, low power bulk-driven voltage follower (BD-VF). As an application of the proposed BD-VF, a 4th order low-pass filter (LPF) with cutoff frequency adjustable from 50 Hz to 250 Hz is designed for electrocardiogram (ECG) acquisition systems. The filter is implemented in UMC 180 nm CMOS technology occupying only 0.03 mm2 area. Post layout simulation results show that the filter offers 56 dB dynamic range even with an extremely low supply voltage of 0.3 V. The total power consumption of the filter is 4.8 nW for a cutoff frequency of 100 Hz. The Figure-of-merit (FoM) and capacitance/pole of the filter are 5.7 × 10−15 and 2.2 pF respectively. The proposed filter offers the lowest FoM compared to the state-of-the-art nW-class filters.

Efficient and Robust Approach for Heartbeat Detection of ECG Signal

This paper introduces an efficient and robust method for heartbeat detection based on the calculated angles between the successive samples of electrocardiogram (ECG) signal. The proposed approach involves three stages: filtering, computing the angles of the signal and thresholding. The suggested method is applied to two different types of ECG databases (QTDB and MIT-BIH). The results were compared with the other algorithms suggested in previous works. The proposed approach outperformed the other algorithms, in spite of its simplicity and their fast calculations. These features make it applicable in real-time ECG diagnostics systems. The suggested method was implemented in real-time using a low cost ECG acquisition system and it shows excellent performance.

A Study on Developing Cardiac Signals Recording Framework (CARDIF) Using a Reconfigurable Real-Time Embedded Processor

Due to recent developments in technology, there is a significant growth in healthcare monitoring systems. The most widely monitored human physiological parameters is electrocardiogram (ECG) which is useful for inferring the physiological state of humans. Most of the existing multi-channel ECG acquisition systems were not accessible in resource-constrained settings. This research study proposes a cardiac signal recording framework (CARDIF) using a reconfigurable input-output real-time embedded processor by employing a virtual instrumentation platform. The signal acquisition was configured using Lab VIEW virtual instrumentation block sets. A graphical user interface (GUI) was developed for real-time data acquisition and visualization. The time domain heart rate variability (HRV) statistics were calculated using CARDIF, and the same were compared with a clinical grade 12-channel ECG system. The quality of the acquired signals obtained from the proposed and standard systems was measured and compared by calculating signal-to-noise ratio (SNR). The proposed CARDIF was evaluated qualitatively by visual inspection by a clinician and quantitatively by fidelity measures and vital parameters estimation. The results are quite promising and can be extended for clinical validations.

SHOCKABLE VERSUS NONSHOCKABLE LIFE-THREATENING VENTRICULAR ARRHYTHMIAS USING DWT AND NONLINEAR FEATURES OF ECG SIGNALS

Shockable ventricular arrhythmias (VAs) such as ventricular tachycardia (VT) and ventricular fibrillation (VFib) are the life-threatening conditions requiring immediate attention. Cardiopulmonary resuscitation (CPR) and defibrillation are the significant immediate recommended treatments for these shockable arrhythmias to obtain the return of spontaneous circulation. However, accurate classification of these shockable VAs from nonshockable ones is the key step during defibrillation by automated external defibrillator (AED). Therefore, in this work, we have proposed a novel algorithm for an automated differentiation of shockable and nonshockable VAs from electrocardiogram (ECG) signal. The ECG signals are segmented into 5, 8 and 10[Formula: see text]s. These segmented ECGs are subjected to four levels of discrete wavelet transformation (DWT). Various nonlinear features such as approximate entropy ([Formula: see text], signal energy ([Formula: see text]), Fuzzy entropy ([Formula: see text]), Kolmogorov Sinai entropy ([Formula: see text], permutation entropy ([Formula: see text]), Renyi entropy ([Formula: see text]), sample entropy ([Formula: see text]), Shannon entropy ([Formula: see text]), Tsallis entropy ([Formula: see text]), wavelet entropy ([Formula: see text]), fractal dimension ([Formula: see text]), Kolmogorov complexity ([Formula: see text]), largest Lyapunov exponent ([Formula: see text]), recurrence quantification analysis (RQA) parameters ([Formula: see text]), Hurst exponent ([Formula: see text]), activity entropy ([Formula: see text]), Hjorth complexity ([Formula: see text]), Hjorth mobility ([Formula: see text]), modified multi scale entropy ([Formula: see text]) and higher order statistics (HOS) bispectrum ([Formula: see text]) are obtained from the DWT coefficients. Later, these features are subjected to sequential forward feature selection (SFS) method and selected features are then ranked using seven ranking methods namely, Bhattacharyya distance, entropy, Fuzzy maximum relevancy and minimum redundancy (mRMR), receiver operating characteristic (ROC), Student’s [Formula: see text]-test, Wilcoxon and ReliefF. These ranked features are supplied independently into the [Formula: see text]-Nearest Neighbor (kNN) classifier. Our proposed system achieved maximum accuracy, sensitivity and specificity of (i) 97.72%, 94.79% and 98.74% for 5[Formula: see text]s, (ii) 98.34%, 95.49% and 99.14% for 8[Formula: see text]s and (iii) 98.32%, 95.16% and 99.20% for 10[Formula: see text]s of ECG segments using only ten features. The integration of the proposed algorithm with ECG acquisition systems in the intensive care units (ICUs) can help the clinicians to decipher the shockable and nonshockable life-threatening arrhythmias accurately. Hence, doctors can use the CPR or AED immediately and increase the chance of survival during shockable life-threatening arrhythmia intervals.

Automated identification of shockable and non-shockable life-threatening ventricular arrhythmias using convolutional neural network

Ventricular tachycardia (VT) and ventricular fibrillation (VFib) are the life-threatening shockable arrhythmias which require immediate attention. Cardiopulmonary resuscitation (CPR) and defibrillation are highly recommended means of immediate treatment of these shockable arrhythmias and to resume spontaneous circulation. However, to increase efficacy of defibrillation by an automated external defibrillator (AED), an accurate distinction of shockable ventricular arrhythmias from non-shockable ones needs to be provided upfront. Therefore, in this work, we have proposed a novel tool for an automated differentiation of shockable and non-shockable ventricular arrhythmias from 2 s electrocardiogram (ECG) segments. Segmented ECGs are processed by an eleven-layer convolutional neural network (CNN) model. Our proposed system was 10-fold cross validated and achieved maximum accuracy, sensitivity and specificity of 93.18%, 95.32% and 91.04% respectively. Its high performance indicates that shockable life-threatening arrhythmia can be immediately detected and thus increase the chance of survival while CPR or AED-based support is performed. Our tool can also be seamlessly integrated with an ECG acquisition systems in the intensive care units (ICUs).

A wearable 12-lead ECG acquisition system with fabric electrodes.

Continuous electrocardiogram (ECG) monitoring is significant for prevention of heart disease and is becoming an important part of personal and family health care. In most of the existing wearable solutions, conventional metal sensors and corresponding chips are simply integrated into clothes and usually could only collect few leads of ECG signals that could not provide enough information for diagnosis of cardiac diseases such as arrhythmia and myocardial ischemia. In this study, a wearable 12-lead ECG acquisition system with fabric electrodes was developed and could simultaneously process 12 leads of ECG signals. By integrating the fabric electrodes into a T-shirt, the wearable system would provide a comfortable and convenient user interface for ECG recording. For comparison, the proposed fabric electrode and the gelled traditional metal electrodes were used to collect ECG signals on a subject, respectively. The approximate entropy (ApEn) of ECG signals from both types of electrodes were calculated. The experimental results show that the fabric electrodes could achieve similar performance as the gelled metal electrodes. This preliminary work has demonstrated that the developed ECG system with fabric electrodes could be utilized for wearable health management and telemedicine applications.

Design and Implementation of Wireless Body Area Network using physiological parameters

Applications of e-Health deals with various physiological signals like body temperature, Blood Pressure, Electrocardiogram(ECG) captured by either wired networks or wireless sensor networks (WSN).ECG is one of the important parameter. A three lead based ECG acquisition system, body temperature; pulse rate monitoring system is presented in the paper below which can store data. The data can be sent wirelessly to the doctor for further analysis. The proposed design makes use of wearable sensors which will not be of discomfort to the patient. The patient can move around easily.

Textile-based ECG acquisition system with capacitively coupled electrodes

In most traditional electrocardiogram (ECG) detection procedures, wet electrodes must be glued to the skin during the procedure and may cause problems such as inconvenience and skin irritation. Furthermore, the quality of the acquired signals decreases because the glue dehydrates over time. In this study, a non-contact ECG acquisition system based on capacitive coupling textile electrodes with low-power consumption and high input impedance is presented. We designed electrodes that have a composite and textile structure. A kind of conductive textile with stainless steel wire creates these electrodes. We wove the conductive textile that has good electrical conductivity with a surface resistivity of 1.25 Ω/sq. Both circuit models of the skin–electrode interface and amplifier for the capacitively coupled textile electrode were established, and the output signal-to-noise ratio (SNR) of the front-end circuit was proposed. The integrated system combines amplification, filter circuit and analogue-to-digital converter. The final measurement shows that the ECG signals acquired by our system are adequate for heartbeat detection and applicable to clinical practice.

A Fully Digital Front-End Architecture for ECG Acquisition System With 0.5 V Supply

This paper presents a new power-efficient electrocardiogram acquisition system that uses a fully digital architecture to reduce the power consumption and chip area. The proposed architecture is compatible with digital CMOS technology and is capable of operating with a low supply voltage of 0.5 V. In this architecture, no analog block, e.g., low-noise amplifier (LNA), and filters, and no passive elements, such as ac coupling capacitors, are used. A moving average voltage-to-time converter is used, which behaves instead of the LNA and antialiasing filter. A digital feedback loop is employed to cancel the impact of the dc offset on the circuit, which eliminates the need for coupling capacitors. The circuit is implemented in 0.18-um CMOS process. The simulation results show that the front-end circuit consumes 274 nW of power.

Demonstration of a fully differential VGA chip with small THD for ECG acquisition system**Project supported by the National Natural Science Foundation of China (Nos. 61264001, 61465004, 61161003, 61166004), the Guangxi Natural Science Foundation (Nos. 2013GXNSFAA019333, 2013GXNSFAA019338), the Science and Technology Research Key Project of Guangxi Department of Education (No. 2013ZD026), and the Innovation Project of GUET Graduate Education (No. GDYCSZ201457).

We present both a theoretical and experimental demonstration of a fully differential variable gain amplifier (VGA) with small total harmonic distortion (THD) for an electrocardiogram (ECG) acquisition system. Capacitive feedback technology is adopted to reduce the nonlinearity of VGA. The fully differential VGA has been fabricated in SMIC 0.18-μm CMOS process, and it only occupies 0.11 mm2. The measurements are in good agreement with simulation results. Experimental results show that the gain of VGA changes from 6.17 to 43.75 dB with a gain step of 3 dB. The high-pass corner frequency and low-pass corner frequency are around 0.22 Hz and 7.9 kHz, respectively. For each gain configuration, a maximal THD of 0.13% is obtained. The fully differential VGA has a low THD and its key performance parameters are well satisfied with the demands of ECG acquisition system application in the UWB wireless body area network.

A flexible dry electrode based on APTES-anchored PDMS substrate for portable ECG acquisition system

We developed a simple and low-cost flexible dry electrode with micro domes by depositing metal film directly on (3-aminopropyl)triethoxysilane (APTES)-anchored polydimethylsiloxane (PDMS) substrate for portable electrocardiogram (ECG) acquisition system. However, the adhesion between metal and PDMS was poor, and metal film on PDMS always exhibited wrinkles. To overcome these difficulties, before depositing Cu, PDMS substrate was treated by APTES aqueous solution. Then, we evaluated the metal film through the microscopic photographs, the surface roughness measurements and the adhesion tests. On the base of the deposition technique improvement, a PDMS-based dry electrode for ECG monitoring was fabricated. We studied the performance of the flexible dry electrode and the results showed the fabricated electrode produced good ECG signals with distinct P, QRS, and T waves. In addition, the fabricated flexible dry electrode with micro domes showed lower skin-contact impedance and could obtain ECG signals with higher SNR than the flat dry electrode.