Electrocardiographic Device Research Articles

The relationship between coronary slow-flow and frontal QRS-T angle

ObjectiveIt is known that increased frontal QRS-T angle, which is a new ventricular repolarization marker is associated with adverse cardiac outcomes. It has been observed that the coronary slow-flow (CSF) phenomenon can cause arrhythmias and sudden cardiac death. The aim of our study is to investigate the relationship between CSF in patients and the frontal QRS-T angle. Material and methodA total of 200 patients, 97 of who had CSF and 103 with the normal coronary flow (NCF), were included in our study. The CSF group was divided into two groups; single-vessel CSF and multi-vessel CSF. The TIMI-frame count was calculated from the coronary angiography images of each patient. 12-lead electrocardiography (ECG) records were examined. The frontal QRS-T angle was obtained from the automated reports of the ECG device. ResultsThe mean age of the study population was 50.7 ± 9.5 and 102 (51%) of patients were female. The frontal QRS-T angle was significantly higher in patients with CSF compared to the NCF group [48(31-64) vs 37(25-46), p = 0.001]. A positive correlation was observed between the frontal QRS-T angle and TIMI-frame count in the correlation analysis performed separately for LAD, Cx, RCA patients with CSF (respectively; r = 0.340 and p < 0.001, r = 0.262 and p = 0.002, r = 0.247 and p = 0.003). The frontal QRS-T angle was higher in patients with multi-vessel CSF than in patients with single-vessel CSF [53.5(41.5-76.5) vs 43.0(23.5-60.5), p = 0.039]. ConclusionThere is a positive correlation between frontal QRS-T angle and TIMI-frame count. The frontal QRS-T angle is higher in patients with CSF. Also, frontal QRS-T angle was higher in the multi-vessel CSF group.

Teaching the basic principles of electrocardiography experimentally.

Electrocardiography (ECG) is one of the most widely used methods in clinical diagnosis. Here we describe an experimental approach that offers hands-on learning of its basic principles. An experimental model that consists of a rubber foil with a low electrical conductivity and a DC power unit is used to simulate the body and the electric dipole of the heart. It enables students to learn about the main features of the electric dipole and to visualize the induced electric potential in the body. The determination of the characteristic equipotential lines around the dipole and the measurement of simple electrocardiograms, comprising bipolar and unipolar leads, are made with a low-cost voltmeter. To make the exercise more relevant to clinical ECG, as well as making it more interesting, the students are additionally tasked to measure their own electrocardiogram with a simple, personal handheld ECG device.

Long-Term Effect of Device-Guided Slow Breathing on Blood Pressure Regulation and Chronic Inflammation in Patients with Essential Hypertension Using a Wearable ECG Device.

Hypertension is related to autonomic nervous system (ANS) dysfunction, atherosclerosis and chronic inflammation. The stimulation of baroreflex regulation by slow-breathing exercise may improve the interplay among these systems. The objective of this study was to investigate the effect of device-guided slow breathing on ANS, cardiovascular system and chronic inflammation in hypertensive patients. We prospectively collected 36 essential hypertension patients who were requested to practice slow-breathing exercise 5 times per day for 3 months. The breathing exercise was guided by a cellphone app with a wearable electrocardiography device and a rhythm of 6 cycles per minute. Cardiovascular indicators including heart rate variability (HRV), blood pressure, pulse wave velocity and baroreflex indexes were sampled 3 times: at the first visit, and 1 month and 3 months after the intervention. The levels of blood inflammatory biomarkers, including tumor necrosis factor-alpha (TNF-α), interleukin-6, interleukin-1 receptor antagonist and C-reactive protein were also collected at all 3 visits. The longitudinal differences in these variables and their correlations were tested. There was a significant decrease in blood pressure after 1 month of exercise. A significantly continuous decrease in TNF-α was also observed. The baroreflex indexes were significantly increased in the acute intervention of slow-breathing but not in the longitudinal effect. The HRV variables did not show differences with time. There were positive correlations between sympathetic index and TNF-α and galectin-3. The effect of slow-breathing exercise on blood pressure and chronic inflammation was significant. HRV indexes may also be used to assess chronic inflammation.

Effectiveness of e-Health cardiac rehabilitation program on quality of life associated with symptoms of anxiety and depression in moderate-risk patients

Exploring new models of medical care requires evaluating the impact of new care strategies not only on physiological parameters but also on the quality of life of the patient. On the other hand the presence of anxiety together with depression requires further consideration when planning appropriate management strategies. The aim of this study was to examine the effectiveness of a home-based cardiac rehabilitation program incorporating an e-Health technology on health-related quality of life associated with symptoms of anxiety and depression in moderate-risk patients. A multicenter, randomized controlled clinical trial was designed to compare a traditional hospital based cardiac rehabilitation program (n = 38, 35 male) with a mixed home surveillance program where patients exercised at home with a remote electrocardiographic monitoring device (n = 33, 31 male). The Short Form-36 (SF-36) Health Survey and the Goldberg questionnaire were used to evaluate quality of life and the presence of symptoms of anxiety and depression respectively. The results of this study show that the type of cardiac rehabilitation program did not influence the improvement in quality of life (p = 0.854), but the presence of symptoms of anxiety and depression did (p = 0.001). Although both programs achieved a decrease in anxiety and depression symptoms and improved functional capacity (p ≤ 0.001), a significant interaction effect was found between the group with or without anxiety and depression symptoms and the type of program in the bodily pain dimension (p = 0.021). Trial registration: Retrospectively registered NCT02796404 (10/06/2016) in clinialtrials.gov.

Neurostimulator-induced ECG artefacts: A systematic analysis

ObjectivesDeep brain stimulation (DBS) is known to interfere with electrocardiographic (ECG) examinations. In emergency situations, such electrical interferences can not only thwart ECG diagnostics, but even induce an ECG pattern that causes the emergency medical service to initiate inadequate or even harmful therapy. Aim of this prospective study was to evaluate factors influencing ECG interpretation in DBS and to evaluate the susceptibility of ECG criteria ‘frequency’, ‘rhythm’, ‘regularity’, ‘QRS-configuration’, and ‘ST-segment’ on neurostimulation. Patients and methodsIn 33 DBS patients (17 male, 16 female, mean age 64 years), limb-, 12 channel-, Nehb, and adhesive paddle-lead ECG were performed in activated (n = 33) and deactivated (n = 31) stimulation mode during outpatient follow-up examinations. The examinations were carried out using three different ECG devices (two portable emergency ECG-monitor/defibrillation/pacer-devices, one stationary hospital device), resulting in 4096 ECG leads. Statistics have been based on regression analyses and on a maximum likelihood estimation regression model. ResultsMonopolar settings were found to be a relevant factor interfering significantly more often with ECG recording than bipolar parameters (p < 0.0001). Due to recurring movement artefacts, deactivation of bipolar stimulation might even significantly worsen ECG quality (p < 0.0001). Interpretability of ‘rhythm’ (β = −0.088, p = 0.03) and ‘frequency’ (β = −0.110, p = 0.02) revealed significant negative correlation to the applied neurostimulation voltage. Nehb lead yielded in highest ECG interpretability. ConclusionBipolar neurostimulation mode barely affected the ECGs; furthermore, the suppression of motion artefacts by neurostimulation can improve ECG quality. If monopolar neurostimulation is required, at least, stimulation voltage should be as low as possible to obtain good stimulation results.

Prognostic value of variables derived from heart rate variability in patients with traumatic brain injury after decompressive surgery.

Measurement of heart rate variability can reveal autonomic nervous system function. Changes in heart rate variability can be associated with disease severity, risk of complications, and prognosis. We aimed to investigate the prognostic value of heart rate variability measurements in patients with moderate-to-severe traumatic brain injury after decompression surgery. We conducted a prospective study of 80 patients with traumatic brain injury after decompression surgery using a noninvasive electrocardiography device for data collection. Assessment of heart rate variability parameters included the time and frequency domains. The correlations between heart rate variability parameters and one-year mortality and functional outcomes were analyzed. Time domain measures of heart rate variability, using the standard deviation of the RR intervals and the square root of the mean squared differences of successive RR intervals, were statistically significantly lower in the group of patients with unfavorable outcomes and those that died. In frequency domain analysis, very low-frequency and total power were significantly higher in patients with favorable functional outcomes. High-frequency, low-frequency, and total power were statistically significantly higher in patients who survived for more than one year. Multivariate analysis using a model combining age and the Glasgow Coma Scale score with variables derived from heart rate variability substantially improved the prognostic value for predicting long-term outcome. These findings reinforced the concept that traumatic brain injury impacts the brain-heart axis and cardiac autonomic modulation even after decompression surgery, and variables derived from heart rate variability may be useful predictors of outcome.

Artificial intelligence assessment for early detection of heart failure with preserved ejection fraction based on electrocardiographic features.

Although heart failure with preserved ejection fraction (HFpEF) is a rapidly emerging global health problem, an adequate tool to screen it reliably and economically does not exist. We developed an interpretable deep learning model (DLM) using electrocardiography (ECG) and validated its performance. This retrospective cohort study included two hospitals. 34 103 patients who underwent echocardiography and ECG within 1 week and indicated normal left ventricular systolic function were included in this study. A DLM based on an ensemble neural network was developed using 32 671 ECGs of 20 169 patients. The internal validation included 1979 ECGs of 1979 patients. Furthermore, we conducted an external validation with 11 955 ECGs of 11 955 patients from another hospital. The endpoint was to detect HFpEF. During the internal and external validation, the area under the receiver operating characteristic curves of a DLM using 12-lead ECG for detecting HFpEF were 0.866 (95% confidence interval 0.850-0.883) and 0.869 (0.860-0.877), respectively. In the 1412 individuals without HFpEF at initial echocardiography, patients whose DLM was defined as having a higher risk had a significantly higher chance of developing HFpEF than those in the low-risk group (33.6% vs. 8.4%, P < 0.001). Sensitivity map showed that the DLM focused on the QRS complex and T-wave. The DLM demonstrated high performance for HFpEF detection using not only a 12-lead ECG but also 6- single-lead ECG. These results suggest that HFpEF can be screened using conventional ECG devices and diverse life-type ECG machines employing the DLM, thereby preventing disease progression.

Sum of Sine Modeling Approach as a New Processing Technique For a Biometric System Based on ECG Signal

Biometrics is considered in current research as one of the best methods for authenticating human beings. In our paper, the heartbeat biometric, also called Electrocardiographic (ECG), is working on. This biometric is chosen because human ECGs cannot be falsely created and replicated. This study aims to find the best features from this biometric that can identify a person, given the extractions and classification algorithms for the heartbeat biometric signal. Depending on a literature study we work to propose a new and more efficient technique based on a new method for ECG features extraction and these features will be the inputs for pattern recognition classifier. This methodology will be tested on real experimental ECG data that is collected. The Data collected from 10 subjects by a commercial ECG device taking the data from lead 1. The pre-processing steps start with the Empirical Mode Decomposition (EMD) before digital filters which are: low pass, high pass, and derivative pass filters. Features extraction steps are peak detection, segmentation, and wave modeling for each segment. The classification used the Multi-Layer Perceptron and compared it to classification using Radial Basis Function were the results of MLP were much better for these applications since the accuracy of the final results of MLP is 99% and that related to the RBF is 95%.

On the Variability of Heart Rate Variability-Evidence from Prospective Study of Healthy Young College Students.

Heart rate variability (HRV) has been widely used as indices for autonomic regulation, including linear analyses, entropy and multi-scale entropy based nonlinear analyses, and however, it is strongly influenced by the conditions under which the signal is being recorded. To investigate the variability of healthy HRV under different settings, we recorded electrocardiograph (ECG) signals from 56 healthy young college students (20 h for each participant) at campus using wearable single-lead ECG device. Accurate R peak to R peak (RR) intervals were extracted by combing the advantages of five commonly used R-peak detection algorithms to eliminate data quality influence. Thorough and detailed linear and nonlinear HRV analyses were performed. Variability of HRV metrics were evaluated from five categories: (1) different states of daily activities; (2) different recording time period in the same day during free-running daily activities; (3) body postures of sitting and lying; (4) lying on the left, right and back; and (5) gender influence. For most of the analyzed HRV metrics, significant differences (p < 0.05) were found among different recording conditions within the five categories except lying on different positions. Results suggested that the standardization of ECG data collection and HRV analysis should be implemented in HRV related studies, especially for entropy and multi-scale entropy based analyses. Furthermore, this preliminary study provides reference values of HRV indices under various recording conditions of healthy young subjects that could be useful information for different applications (e.g., health monitoring and management).

Fabricating a Portable ECG Device Using AD823X Analog Front-End Microchips and Open-Source Development Validation.

Relevant to mobile health, the design of a portable electrocardiograph (ECG) device using AD823X microchips as the analog front-end is presented. Starting with the evaluation board of the chip, open-source hardware and software components were integrated into a breadboard prototype. This required modifying the microchip with the breadboard-friendly Arduino Nano board in addition to a data logger and a Bluetooth breakout board. The digitized ECG signal can be transmitted by serial cable, via Bluetooth to a PC, or to an Android smartphone system for visualization. The data logging shield provides gigabytes of storage, as the signal is recorded to a microSD card adapter. A menu incorporates the device’s several operating modes. Simulation and testing assessed the system stability and performance parameters in terms of not losing any sample data throughout the length of the recording and finding the maximum sampling frequency; and validation determined and resolved problems that arose in open-source development. Ultimately, a custom printed circuit board was produced requiring advanced manufacturing options of 2.5 mils trace widths for the small package components. The fabricated device did not degrade the AD823X noise performance, and an ECG waveform with negligible distortion was obtained. The maximum number of samples/second was 2380 Hz in serial cable transmission, whereas in microSD recording mode, a continuous ECG signal for up to 36 h at 500 Hz was verified. A low-cost, high-quality portable ECG for long-term monitoring prototype that reasonably complies with electrical safety regulations and medical equipment design was realized.

Opportunistic screening versus usual care for detection of atrial fibrillation in primary care: cluster randomised controlled trial

ObjectiveTo investigate whether opportunistic screening in primary care increases the detection of atrial fibrillation compared with usual care.DesignCluster randomised controlled trial.Setting47 intention-to-screen and 49 usual care primary care practices in...

Capacity of Palestinian primary health care system to prevent and control of non-communicable diseases in Gaza Strip, Palestine: A capacity assessment analysis based on adapted WHO-PEN tool.

The prevalence of non-communicable diseases (NCDs) are increasing in low-income countries including Palestine. This study was conducted to assess the capacity of Palestinian primary health care system to prevent and control of NCDs. This cross-sectional study in which, the World Health Organization package of essential NCDs interventions (WHO-PEN) tool, was used to assess the capacity of primary health care centers (PHCs) to prevent and control of NCDs. All governmental PHCs (n = 52) in Gaza Strip, Palestine were included in the final analysis. The centers readiness score was calculated as the average of domains indices. Then, the indices were compared to an agreed cutoff at 70%. Statistical analysis was performed using SPSS version 22. Out of 52 PHCs, only 21 (40.4%) were considered ready to prevent and control of NCDs; the highest readiness score was 79.4% and the lowest score was 29.2%. Furthermore, all governorates were not ready to prevent and control of NCDs (The readiness scores were < 70%), distributed as follow: 68.6%, 68.1%, 67.7%, 62.5% and 56.4%, for Rafah, Gaza, Khan-Yunis, Deir Al Balah and North Gaza, respectively. The governorates were differed significantly in terms of availability of aneroid blood pressure measuring devices, electrocardiography devices, Glibenclamide and Salbutamol tablets, patients counseling for diabetes self-management, patients education for self-administration of insulin (P values <.05 for all). The current study demonstrated critical gaps in the governmental PHCs capacity to prevent and control of NCDs, as most of PHCs failed to reach the minimum threshold of the WHO-PEN standards.

Investigation of the Application of New Mathematical Methods for the Analysis of Cardiac Data

The article shows the results of the implementation of the first stage of the project "Study of the application of new mathematical methods for analysis of cardiac data", funded by the Research Fund. The results are related to the creation of a portable information system for individual monitoring of the cardiovascular system, which includes a portable device for recording photoplethysmographic (PPG) signals and software for processing, mathematical analysis and assessment of heart rate variability. An important advantage of the portable device is the ability to constantly monitor and record the functioning and parameters of the cardiovascular system of the individual. This allows more accurate diagnosis of patients in different life situations in normal life, which is based on subsequent scientific analysis of the registered cardiac information through developed specialized software using linear and nonlinear mathematical methods. The article also shows the results for validation of the created new device, by means of an experimental scheme with which electrocardiographic (ECG) and PPG signals are registered simultaneously. The obtained two types of signals are compared in terms of the accuracy parameter of the registered signals. The results show that the two types of registered signals are identical; therefore the developed portable device can be used as an alternative to the currently widely used ECG and Holter devices.

Atrial Fibrillation in Indigenous Australians: A Multisite Screening Study Using a Single-Lead ECG Device in Aboriginal Primary Health Settings

Circulatory diseases continue to be the greatest cause of mortality for Australian Aboriginal and Torres Strait Islander people, and a major cause of persistently lower life expectancy compared with non-Aboriginal Australians. The limited information that exists on atrial fibrillation (AF) prevalence in Aboriginal and Torres Strait Islander communities is mostly based on hospital admission data. This shows AF as principal or additional admission diagnosis was 1.4 times higher compared to non-Aboriginal Australians, a higher incidence of AF across the adult life span after age 20 years and a significantly higher prevalence among younger patients. Our study estimates the first national community prevalence and age distribution of AF (including paroxysmal) in Australian Aboriginal people. A handheld single-lead electrocardiograph (ECG) device (iECG), known to be acceptable in this population, was used to record participant ECGs. This co-designed, descriptive cross-sectional study was conducted in partnership with 16 Aboriginal Community Controlled Health organisations at their facilities and/or with their services delivered elsewhere. The study was also conducted at one state community event. Three (3) Australian jurisdictions were involved: New South Wales, Western Australia and the Northern Territory. Study sites were located in remote, regional and urban areas. Opportunistic recruitment occurred between June 2016 and December 2017. People <45 years of age were excluded. Thirty (30) of 619 Aboriginal people received a 'Possible AF' and 81 an 'Unclassified' result from a hand-held smartphone ECG device. A final diagnosis of AF was made in 29 participants (4.7%; 95%CI 3.0-6.4%), 25 with known AF (five paroxysmal), and four with previously unknown AF. Three (3) of the four with unknown AF were aged between 55-64 years, consistent with a younger age of AF onset in Aboriginal people. Estimated AF prevalence increased with age and was higher in those aged >55 years than the general population (7.2% compared with 5.4%). Slightly more men than women were diagnosed with AF. This study is a significant contribution to the evidence which supports screening for AF in Aboriginal and Torres Strait Islander people commencing at a younger age than as recommended in the Australian guidelines (>65 years). We recommend the age of 55 years. Consideration should be given to the inclusion of AF screening in the Australian Government Department of Health annual 'Aboriginal and Torres Strait Islander Health Assessment'. ACTRN12616000459426.

Real-World Consumer-Grade Sensor Signal Alignment Procedure Applied to High-Noise ECG to BCG Signal Synchronization.

In recent years, consumer-grade sensors that measure health relevant physiological signals have become widely available and are increasingly used by consumers and researchers alike. While this allows for multiple novel, potentially highly beneficial, large-scale health monitoring applications, quality of these data streams is oftentimes suboptimal. This makes alignment of different high-frequency data streams from multiple, non-connected sensors, a difficult task. In this work we describe a noise-robust framework to align high-frequency signals from different sensors, that share some underlying characteristic, obtained in a free-living, non-clinical, home environment. We demonstrate the approach on the basis of a single-lead, medical-grade, mobile electrocardiography device and a consumer-grade sleep sensor that allows for ballistocardiography. Both commercially available sensors measure the physiological process of a heartbeat. We show, on the basis of real-world data with multiple people and sensors, that the two highly noisy and sometimes dissimilar signals could in most cases be aligned with considerable precision. As a result, we could reduce mean heartbeat peak-to-peak difference by 58.1% on average and increase signal correlation by 0.40 on average.

Eletrocardiografia computadorizada em ovinos adultos da raça Sulffolk: estudo comparativo

Computerized electrocardiography is a method widely used in veterinary medicine in several species and currently, with the availability of several devices in the market. In sheep, studies have shown variations in electrocardiographic values according to race, age, and methods of capture, but the values obtained in different computerized devices have not been compared. Thus, the present study sought to determine and compare the values of electrocardiographic variables between two computerized devices in healthy sheep. Fifty sheep (n = 50), Suffolk breed, female, launched, adult, non-pregnant, with average age and weight of two years and 50kg, respectively, were studied properly selected and clinically fit. The electrocardiographic tracings were obtained in two computerized electrocardiography devices (Apparatus A and B) individually and subsequently, with subsequent recording and interpretation of the tracings. The results showed a predominance of sinus rhythm in 78% (n = 39) and 22% (n = 11) with sinus arrhythmia in both devices. Significant differences among the devices (p <0.05) were identified in the duration variables (ms), such as P wave, P-R interval and segment, QRS complex, Q-T interval, S-T segment and T wave; and in the P-wave and R-wave amplitudes (mV). However, the values obtained were within the normal ranges recommended for the species, regardless of the capture method used. Thus, it is possible to conclude the presence of different values among the computerized electrocardiographs, suggesting variations in the tracking uptake sensitivity among the devices in released Suffolk sheep.

ANALISA KALIBRASI ALAT ELECTROCARDIOGRAPH MENGGUNAKAN ELECTROCARDIOGRAPH SIMULATOR (PHANTOM ECG)

An electrocardiograph is a device that can display a signal graphic showing the process of the heartbeat. From these signals it can be seen whether a person's heart rate is normal or not. The method used in this research is quantitative observation. Which aims to analyze the calibration of the Electrocardiograph (ECG) device using a simulator (Phantom ECG). And also aims to determine the results of the data obtained after observing the workflow of the tool. From the results of electrocardiograph testing at the Health Facility Security Center (BPFK) Medan, the results were obtained. Electrocardiograph testing at the paper speed set point 25 mm / sec 10 mm / mv obtained results of 25.18 +- 0.37 because it is within a tolerance value of +- 5%. At the paper speed set point of 50 mm / sec, 10 mm / sec, the result is 50.16 +- 0.37 because it is within a tolerance value of +- 5%. At the sensitivity setting point of 5 mm / mv, 25 mm / sec, the result is 5.24 +- 0.37 because it is within a tolerance value of +- 5%. At the sensitivity setting point of 10 mm / mv, 25 mm / sec, the result is 10.22 +- 0.37 because it is within a tolerance value of +- 5%. And at the sensitivity setting point of 20 mm / mv, 25 mm / sec, the result is 20.26 +- 0.36 because it is within a tolerance value of +- 5%.

Prediction of Left Ventricular Mass Index Using Electrocardiography in Essential Hypertension - A Multiple Linear Regression Model.

BackgroundCurrent electrocardiography (ECG) criteria indicate only the presence or absence of left ventricular hypertrophy (LVH). LVH is a continuum and a direct relationship exists between left ventricular mass (LVM) and cardiovascular event rate. We developed a mathematical model predictive of LVM index (LVMI) using ECG and non-ECG variables by correlating them with echocardiography determined LVMI.Patients and MethodsThe model was developed in a cohort of patients on treatment for essential hypertension (BP>140/90 mm of Hg) who underwent concurrent ECG and echocardiography. One hundred and forty-seven subjects were included in the study (56.38±11.84 years, 66% males). LVMI was determined by echocardiography (113.76±33.06 gm/m2). A set of ECG and non-ECG variables were correlated with LVMI for inclusion in the multiple linear regression model. The model was checked for multicollinearity, normality and homogeneity of variances.ResultsThe final regression equation formulated with the help of unstandardized coefficients and constant was LVMI=18.494+ 1.704 (aLL) + 0.969 (RaVL+SV3) + 0.295 (MBP) + 15.406 (IHD) (aLL – sum of deflections in augmented limb leads; RaVL+SV3 – sum of deflection of (R wave in aVL + S wave in V3); MBP – mean blood pressure; IHD=1 for the presence of the disease, IHD=0 for the absence of the disease).ConclusionIn the model, 50.4% of the variability in LV mass is explained by the variables used. The findings warrant further studies for the development of better and validated models that can be incorporated in microprocessor-based ECG devices. The determination of LVMI with ECG only will be a cost-effective and readily accessible tool in patient care.

Design and Implementation of a Portable ECG Device

Electrocardiography(ECG) is the technology of measuring the electrical changes of the heart. The electrical change is due to the depolarization and repolarization of the heart cells which produces a specific wave or complex. The potential developed is captured by the electrodes placed on the skin, which ranges in micro to millivolts. Weak signals captured by the electrodes are amplified and converted into a voltage that is readable for microcontroller ATmega328P. ECG is represented by the waves called P, QRS, and T waves. One cardiac cycle of the heart consists of P-QRS-T waves in ECG. The amplitude of the waves, complexes, and the time interval between different waves or segments conveys the total information on the working activity of the heart. A proper study of those waveforms and time intervals on ECG aids to determine and diagnose different cardiac abnormalities. This paper presents a method of extraction of voltage generated during cardiac movement of the human body using an electrode, amplifier, microcontroller and OLED screen. It describes the method of calculating heartbeats per minute from the ECG signal and displays beats per minute on the same OLED screen.

Screening for arrhythmia with the new portable single-lead electrocardiographic device (SnapECG): an application study in community-based elderly population in Nanjing, China.

SnapECG is a new handheld single-lead electrocardiograph (ECG) device used for arrhythmia screening, it is widely used in clinical practice but not in primary care. To evaluate the arrhythmia screening value of SnapECG among a community-based population. A cross-sectional community-based study of multistage stratified cluster sampling was conducted from March 1st to April 30th 2019. The sensitivities, specificities and the area under the receiver operating characteristic (AUCROC) curves of the SnapECG and reference 12-lead ECG on arrhythmia were calculated in three age-groups [50-64years, 65-74years, and over-75years]. A total of 2263 participants took part in the arrhythmia screening, these included 1479 aged 50-64 years, 602 aged 65-74years and 182 aged over-75years. The SnapECG categorized 1828 (80.8%) as sinus rhythm, 161 (7.1%) as premature atrial/ventricular contractions (PAVs/PCVs), 32 (1.4%) as possible atrial fibrillation (AF), 56 (2.5%) as supraventricular tachycardias or sinus bradycardia (SVT/SB) and 186 (8.2%) as unreadable. SnapECG had 89% sensitivity (95% CI 0.52-1.00) and 99% specificity (95% CI 0.97-0.99) of detecting AF in the 65-74years age-group. The AUCROC to detect AF was 0.94 for the 65-74years age-group, 0.77 for over-75years, 0.62 for the 50-64years. This study is the first community screening application of SnapECG. Main limitation is the SnapECG and the 12-lead ECG were not done simultaneously. In the people aged 65-74years, AF can be detected accurately by the SnapECG with high sensitivity, specificity and large area under the ROC curve, which might have the highest screening predictive accuracy.