An Advanced Holter Monitor Using AD8232 and MEGA 2560

2021 ◽  
Vol 14 (2) ◽  
pp. 80-87
Author(s):  
Zhudiah Annisa ◽  
Priyambada Cahya Nugraha ◽  
M Ridha Makruf
Keyword(s):  
Heart Disease ◽  
The Body ◽  
Ecg Signal ◽  
Ecg Monitoring ◽  
Standard Measurement ◽  
Main Design ◽  
Ecg Signals ◽  
Holter Monitor ◽  
Arduino Microcontroller ◽  
Sd Card

Monitoring of cardiac signals is very important for patients with heart disease. The detection of the ECG signal that is carried out for twenty hours will help the doctor to diagnose heart disease. The purpose of this study was to develop a portable ECG monitoring system and cost as it is called a Holter monitor. The main design of ECG module consists of the AD8232, DS3231 RTC module, Arduino microcontroller, and SD card memory. ECG signals are collected from the body of a standard measurement based LEAD II .. To record the raw data from the ECG signal, SD card memory is used to store data for further data analysis. Calibration is performed using a phantom ECG. This is done to make the design results are in accordance with the standard ECG machine.

scholarly journals A Centrifuge Calibrator Based on Personal Computer Equipped with Data Processor

2019 ◽  
Vol 1 (1) ◽  
pp. 14-19
Author(s):  
Habliya Asadina ◽  
Torib Hamzah ◽  
Dyah Titisari ◽  
Bedjo Utomo
Keyword(s):  
Certified Reference Materials ◽  
International Standards ◽  
Holter Monitor ◽  
Laser Sensors ◽  
Heart Monitoring ◽  
Main Series ◽  
Data Processor ◽  
Arduino Microcontroller ◽  
Sd Card ◽  
Calibration Laboratories

Calibration is an activity to determine the conventional truth of the value of the appointment of a measuring instrument by comparing traceable standards to national and international standards for measurement and / or international units and certified reference materials. The purpose of this study is to develop a system of efficient and practical centrifuge calibrators by sending the calibration results directly via bluetooth to a PC. The main series of centrifuge calibrators are Arduino modules, laser sensors and Bluetooth.The high low signal is obtained from the reflection of the laser beam aimed at the reflector point on the centrifuge plate, processed in the Arduino module and displayed on the LCD, the calibration results can be directly seen in the Delphi program. The design of this module is also equipped with a Bluetooth transmitter to send data to a PC. This module can be used in medical equipment calibration laboratories. Based on the results of testing and data collection on the 8 Tube centrifuge with a Lutron Tachometer ratio, the error value was 0.0136%. After planning, experimenting, making modules, testing modules, and collecting data, it can be concluded that the tool "centrifuge calibrator equipped with PC-based data processors" can be used and according to planning because the fault tolerance does not exceed 10%.Keywords—Holter Monitor; Heart Monitoring; Arduino Microcontroller; SD Card Memory

scholarly journals Artificial Neural Network-Based Automated ECG Signal Classifier

2013 ◽  
Vol 2013 ◽  
pp. 1-6 ◽  
Author(s):  
Sahar H. El-Khafif ◽  
Mohamed A. El-Brawany
Keyword(s):  
Neural Network ◽  
Heart Disease ◽  
Ischemic Heart Disease ◽  
Learning Algorithm ◽  
Normal Sinus Rhythm ◽  
Learning Rule ◽  
Higher Order ◽  
Ischemic Heart ◽  
Ecg Signal ◽  
Ecg Signals

The ECG signal is well known for its nonlinear dynamic behavior and a key characteristic that is utilized in this research; the nonlinear component of its dynamics changes more significantly between normal and abnormal conditions than does the linear one. As the higher-order statistics (HOS) preserve phase information, this study makes use of one-dimensional slices from the higher-order spectral domain of normal and ischemic subjects. A feedforward multilayer neural network (NN) with error back-propagation (BP) learning algorithm was used as an automated ECG classifier to investigate the possibility of recognizing ischemic heart disease from normal ECG signals. Different NN structures are tested using two data sets extracted from polyspectrum slices and polycoherence indices of the ECG signals. ECG signals from the MIT/BIH CD-ROM, the Normal Sinus Rhythm Database (NSR-DB), and European ST-T database have been utilized in this paper. The best classification rates obtained are 93% and 91.9% using EDBD learning rule with two hidden layers for the first structure and one hidden layer for the second structure, respectively. The results successfully showed that the presented NN-based classifier can be used for diagnosis of ischemic heart disease.

Development of medical capacitive coupling electrodes using the skin-electrode contact control

Sensor Review ◽  
2020 ◽  
Vol 40 (3) ◽  
pp. 347-354
Author(s):  
Gennadiy Evtushenko ◽  
Inna A. Lezhnina ◽  
Artem I. Morenetz ◽  
Boris N. Pavlenko ◽  
Arman A. Boyakhchyan ◽  
...  
Keyword(s):  
Personalized Medicine ◽  
The Body ◽  
Capacitive Coupling ◽  
Ecg Signal ◽  
Significant Deterioration ◽  
Content Type ◽  
Ecg Signals ◽  
Skin Electrode ◽  
Electrode Contact

Purpose The purpose of this paper is the development and study of capacitive coupling electrodes with the ability to monitor the quality of the skin–electrode contact in the process of electrocardiogram (ECG) diagnostics. The study’s scope embraces experimental identification of distortions contributed into the recorded ECG signal at various degrees of disturbance of the skin–electrode contact. Design/methodology/approach A capacitive coupling electrode is designed and manufactured. A large number of experiments was carried out to record ECG signals with different quality of the skin–electrode contact. Using spectral analysis, the characteristic distortions of the ECG signals in the event of contact disturbance are revealed. Findings It was found that the violation of the skin–electrode contact leads to significant deterioration in the recorded signal. In this case, the most severe distortions appear with various violations of the skin–electrode contact of two sensors in one lead. It has been experimentally shown that the developed sensor allows monitoring the quality of the contact, and therefore, improvement of the quality of signal registration, enabled by the use of bespoke processing algorithms. Practical implications These sensors will be used in personalized medicine devices and tele-ECG devices. Originality/value In this work, authors studied the effect of the skin–electrode contact of a capacitive electrode with the body on the quality of the recorded ECG signal. Based on the studies, the necessity of monitoring contact was shown to improve the quality of diagnostics provided by personalized medicine devices; the capacitive sensor with contact feedback was developed.

scholarly journals Detection and Classification of ECG Signal through Machine learning

2019 ◽  
Vol 8 (10) ◽  
pp. 3221-3227
Keyword(s):  
The Body ◽  
Wave Form ◽  
Ecg Signal ◽  
Software Application ◽  
Ecg Signals ◽  
Temporal Features ◽  
Associate Anomaly ◽  
The Individual ◽  
Electrocardiogram Ecg

The electrical activity which might be acquired by inserting the probes on the body exterior that is originated within the individual muscle cells of the heart and is summed to indicate an indication wave form referred to as the EKG (ECG). Cardiac Arrhythmia is an associate anomaly within the heart which may be diagnosed with the usage of signals generated by Electrocardiogram (ECG). For the classification of ECG signals a software application model was developed and has been investigated with the usage of the MIT-BIH database. The version is based on some existing algorithms from literature, entails the extraction of a few temporal features of an ECG signal and simulating it with a trained FFNN. The software version may be employed for the detection of coronary heart illnesses in patients. The neural network’s structure and weights are optimized using Particle Swarm Optimization (PSO). The FFNN trained with set of rules by PSO increase its accuracy. The overall accuracy and sensitivity of the algorithm is about 93.687 % and 92%.

scholarly journals LABVIEW BASED ECG SIGNAL ACQUISITION AND ANALYSIS

2021 ◽  
Vol 5 (9) ◽  
Author(s):  
Shila Dhande
Keyword(s):  
Heart Rate ◽  
Research Work ◽  
Heart Rhythm ◽  
The Body ◽  
P Wave ◽  
Signal Acquisition ◽  
Ecg Signal ◽  
Qrs Complex ◽  
Ecg Signals ◽  
Rr Interval

The system “LabVIEW based ECG signal acquisition and analysis” is developed to assist patients and doctors in health care. An arrhythmia is an abnormal heart rhythm. It may be so brief that it doesn’t change the overall heart rate, but it can cause the heart rate to be too slow or too fast. When arrhythmias are severe or last long enough, the heart may not be able to pump enough blood to the body. This can cause the patient to feel tired, lightheaded or may make him pass out. It can also cause death. Before treatment, it’s important for the doctor to know where an arrhythmia starts in the heart and whether it’s abnormal. An electrocardiogram (ECG) is often used to diagnose arrhythmias. “LabVIEW based ECG signal acquisition and analysis” is meant to acquire ECG signals from the patient and analyze it to detect and classify its anomalies and abnormalities. This is achieved by extracting amplitudes and durations of parameters of ECG waveform such as P wave, QRS complex, RR interval, and PR durations. These parameters are compared with the normal values to determine the type of abnormality- Tachycardia or Bradycardia. The database of the patient is maintained for further use by the doctor. The objective of LabVIEW based ECG signal acquisition and analysis aims at acquiring and analyzing temporal parameters of ECG signal such as P wave, QRS complex, RR interval, PR durations and amplitudes of the P wave, ST wave, identification of cardiac arrhythmia using LabVIEW. The research work has helped us to explore various features of LabVIEW like signal processing and automated database generation.

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 Adaptive Motion Artifact Reduction Based on Empirical Wavelet Transform and Wavelet Thresholding for the Non-Contact ECG Monitoring Systems

Sensors ◽  
2019 ◽  
Vol 19 (13) ◽  
pp. 2916 ◽  
Author(s):  
Xiaowen Xu ◽  
Ying Liang ◽  
Pei He ◽  
Junliang Yang
Keyword(s):  
Wavelet Transform ◽  
Heart Diseases ◽  
Motion Artifact ◽  
Motion Artifacts ◽  
Monitoring Systems ◽  
Ecg Signal ◽  
Wavelet Thresholding ◽  
Ecg Monitoring ◽  
Ecg Signals ◽  
Empirical Wavelet Transform

Electrocardiogram (ECG) signals are crucial for determining the health status of the human heart. A clean ECG signal is critical in analysis and diagnosis of heart diseases. However, ECG signals are often contaminated by motion artifact noise in the non-contact ECG monitoring systems. In this paper, an ECG motion artifact removal approach based on empirical wavelet transform (EWT) and wavelet thresholding (WT) is proposed. This method consists of five steps, namely, spectrum preprocessing, spectrum segmentation, EWT decomposition, wavelet threshold denoising, and EWT reconstruction. The proposed approach was used to process real ECG signals collected by the non-contact ECG monitoring equipment. The results of quantitative study and analysis indicate that this approach produces a better performance in terms of restorage of QRS complexes of the original ECG with reduced distortion, retaining useful information in ECG signals, and improvement of the signal to noise ratio (SNR) value of the signal. The output results of the practical ECG signal test show that motion artifact in the real recorded ECG is effectively filtered out. The proposed method is feasible for reducing motion artifacts from ECG signals, whether from simulation ECG signals or practical non-contact ECG monitoring systems.

scholarly journals Digitization of Documented Ecg Signals using Image Processing

2019 ◽  
Vol 9 (1) ◽  
pp. 1286-1289
Keyword(s):  
Heart Disease ◽  
Shortest Path ◽  
Disease Prediction ◽  
Ecg Signal ◽  
Digital Signals ◽  
Shortest Path Algorithm ◽  
Ecg Signals ◽  
Prediction Algorithms ◽  
Digital Format ◽  
Image Digitization

In order to implement the heart disease prediction algorithms, the scanned ECG images need to be digitized. The ECG image digitization from ECG images deals with converting the ECG images in to digital format which can be processed by heart disease prediction algorithms. To present the Heart disease prediction algorithms, the digital signals can be directly applied. In this paper we have presented an effective ECG digitization technique using Dijikstraw’s shortest path algorithm. The scanned ECG images are oversampled 8 times. Then ECG curve is traced using Dijikstraw’s shortest path algorithm. The shortest path computed represents the scanned ECG signal in digitized form which can be directly used for heart disease prediction. The proposed method gives the accurate digitization by reducing the complications of the digitization process

Design of Portable Electrocardiograph Monitoring System

2020 ◽  
Author(s):  
Jia Hua-Ping ◽  
Zhao Jun-Long ◽  
Liu Jun
Keyword(s):  
Real Time ◽  
Monitoring System ◽  
Data Storage ◽  
P Wave ◽  
Ecg Monitoring ◽  
The Public ◽  
Ecg Signals ◽  
Early Warning Mechanism ◽  
Timely Treatment ◽  
Ecg Data

Cardiovascular disease is one of the major diseases that threaten the human health. But the existing electrocardiograph (ECG) monitoring system has many limitations in practical application. In order to monitor ECG in real time, a portable ECG monitoring system based on the Android platform is developed to meet the needs of the public. The system uses BMD101 ECG chip to collect and process ECG signals in the Android system, where data storage and waveform display of ECG data can be realized. The Bluetooth HC-07 module is used for ECG data transmission. The abnormal ECG can be judged by P wave, QRS bandwidth, and RR interval. If abnormal ECG is found, an early warning mechanism will be activated to locate the user’s location in real time and send preset short messages, so that the user can get timely treatment, avoiding dangerous occurrence. The monitoring system is convenient and portable, which brings great convenie to the life of ordinary cardiovascular users.

Possibilities for treating aspirin-i lesions of the stomach and duodenum in patients with chronic coronary heart disease

2020 ◽  
Vol 98 (3) ◽  
pp. 231-235
Author(s):  
N. Yu. Borovkova ◽  
M. V. Buyanova ◽  
T. E. Bakka ◽  
M. P. Nistratova ◽  
T. V. Vlasova ◽  
...  
Keyword(s):  
Coronary Heart Disease ◽  
Heart Disease ◽  
Proton Pump Inhibitor ◽  
Blood Serum ◽  
Proton Pump ◽  
The Body ◽  
Control Group ◽  
Pge2 Level ◽  
Endogenous Prostaglandins ◽  
Chronic Coronary Heart Disease

To evaluate possibilities of aspirin-induced gastroduodenopathy treatment in the patients with chronic ischemic heart disease by means of applying the internal endogenous prostaglandins stimulant.  Material and methods. 340 patients suffering from chronic coronary heart disease and receiving a long-term acetylsalicylic acid (ASA) therapy were examined on the base of the cardiovascular care unit of The Nizhny Novgorod Regional Clinical Hospital named after N.A. Semaschko. There were evaluated frequency, nature and severity of the aspirin-induced gastroduodenopathy. The patients with coronary heart disease and aspirin-induced gastroduodenopathy were divided in two groups. In the first group of patients there was applied rebamipide therapy (in a single daily dose 300 mg) in combination with the proton pump inhibitor (PPI) — pantoprazole. In the second group there was applied only pantoprazole therapy. For the purpose of specification of AIG pathogenetic mechanisms development, all the examined chronic coronary heart disease cases were tested on the prostaglandin E2 (PGE2) level in blood serum before the therapy beginning and after the treatment. The control group was formed of chronic coronary heart disease patients showing no AIG evidence. Statistical processing of the received data was fulfilled with the program «Statistika 10.0». Results. AIG was registered in 15% out of 340 chronic coronary heart disease patients. According to the endoscopic examination erosive disease of the body and antrum prevailed among the patients. The PGE2 level in the blood serum was significantly lower (р = 0,00087) in these patients in comparison with the control group. In association with PPI and rebamipide mixed therapy, esophagogastroduodenoscopy results showed no pathological findings in gastrointestinal mucosa and statistically significant (р = 0,00067) blood serum PGE2 level growing in all the treated patients. As a result of exclusive PPI therapy there was marked positive dynamics in endoscopic view in 19 out of 25 patients and a tendency to normalization of PGE2 level in the blood serum. However, PGE2 level growing was insignificant. Conclusion. The presented research demonstrates the possibility of AIG treatment with the use of internal endogenous prostaglandins stimulant — rebamipide in complex with proton pump inhibitor PPI therapy.

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