scholarly journals Design of a Wearable 12-Lead Noncontact Electrocardiogram Monitoring System

Sensors ◽  
2019 ◽  
Vol 19 (7) ◽  
pp. 1509 ◽  
Author(s):  
Chien-Chin Hsu ◽  
Bor-Shing Lin ◽  
Ke-Yi He ◽  
Bor-Shyh Lin
Keyword(s):  
Myocardial Ischemia ◽  
Monitoring System ◽  
Mechanical Design ◽  
Heart Diseases ◽  
Signal Quality ◽  
Ecg Signal ◽  
Ventricular Premature Contraction ◽  
Dry Electrodes ◽  
Electrocardiogram Monitoring ◽  
Electrocardiogram Ecg

A standard 12-lead electrocardiogram (ECG) is an important tool in the diagnosis of heart diseases. Here, Ag/AgCl electrodes with conductive gels are usually used in a 12-lead ECG system to access biopotentials. However, using Ag/AgCl electrodes with conductive gels might be inconvenient in a prehospital setting. In previous studies, several dry electrodes have been developed to improve this issue. However, these dry electrodes have contact with the skin directly, and they might be still unsuitable for patients with wounds. In this study, a wearable 12-lead electrocardiogram monitoring system was proposed to improve the above issue. Here, novel noncontact electrodes were also designed to access biopotentials without contact with the skin directly. Moreover, by using the mechanical design, this system allows the user to easily wear and take off the device and to adjust the locations of the noncontact electrodes. The experimental results showed that the proposed system could exactly provide a good ECG signal quality even while walking and could detect the ECG features of the patients with myocardial ischemia, installation pacemaker, and ventricular premature contraction.

scholarly journals Fractal Based Analysis of the Influence of Odorants on Heart Activity

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Hamidreza Namazi ◽  
Vladimir V. Kulish
Keyword(s):  
Heart Rate ◽  
Heart Diseases ◽  
Approximate Entropy ◽  
Ecg Signal ◽  
Heart Activity ◽  
Heart Research ◽  
Olfactory Stimuli ◽  
Important Challenge ◽  
External Stimuli ◽  
Electrocardiogram Ecg

Abstract An important challenge in heart research is to make the relation between the features of external stimuli and heart activity. Olfactory stimulation is an important type of stimulation that affects the heart activity, which is mapped on Electrocardiogram (ECG) signal. Yet, no one has discovered any relation between the structures of olfactory stimuli and the ECG signal. This study investigates the relation between the structures of heart rate and the olfactory stimulus (odorant). We show that the complexity of the heart rate is coupled with the molecular complexity of the odorant, where more structurally complex odorant causes less fractal heart rate. Also, odorant having higher entropy causes the heart rate having lower approximate entropy. The method discussed here can be applied and investigated in case of patients with heart diseases as the rehabilitation purpose.

scholarly journals Smartphone based ECG Acquisition and Analysis

2021 ◽  
Vol 9 (VI) ◽  
pp. 539-543
Author(s):  
Renuka Vijay Kapse
Keyword(s):  
Cardiovascular Diseases ◽  
Cause Of Death ◽  
Health Monitoring ◽  
Early Warning ◽  
Heart Diseases ◽  
Ecg Signal ◽  
Android Application ◽  
Ecg Signals ◽  
Heart Damage ◽  
Electrocardiogram Ecg

Health monitoring and technologies related to health monitoring is an appealing area of research. The electrocardiogram (ECG) has constantly being mainstream estimation plan to evaluate and analyse cardiovascular diseases. Heart health is important for everyone. Heart needs to be monitored regularly and early warning can prevent the permanent heart damage. Also heart diseases are the leading cause of death worldwide. Hence the work presents a design of a mini wearable ECG system and it’s interfacing with the Android application. This framework is created to show and analyze the ECG signal got from the ECG wearable system. The ECG signals will be shipped off an android application via Bluetooth device. This system will automatically alert the user through SMS.

scholarly journals The Real-time Electrocardiogram Signal Monitoring System in Wireless Sensor Network

2019 ◽  
Vol 15 (02) ◽  
pp. 4
Author(s):  
Anchana Muankid ◽  
Mahasak Ketcham
Keyword(s):  
Wireless Sensor Network ◽  
Real Time ◽  
Sensor Network ◽  
Monitoring System ◽  
Wireless Sensor ◽  
Ecg Signal ◽  
The Real ◽  
Receiver Module ◽  
Signal Monitoring ◽  
Electrocardiogram Ecg

The Cardiovascular disease (CVD) is the most of death in the world. Electrocardiogram (ECG) is the graph that shows heart electrical activities. The physician record and detect the abnormal Electrocardiogram (ECG) signal by the Holter monitor that patient need to carry on the device for record ECG signal in 24 hours. Pan-Tomkins algorithm was appropriate for Real-time ECG signal recognition because high accuracy and rapidly analysis. This research propose the Real-time ECG Signal monitoring system for detect the abnormal ECG signal by using Pan-Tomkins algorithm with Wireless Sensor Network. The system separated into 2 part; sender module and receiver module. Experimental the system by using the ECG signal data from MIT-BIH database. Selected 20 samples of abnormal ECG signal then experimental at 10 and 20 meters sender module-receiver module distance, calculate R-R interval and R amplitude threshold The results show that the Real-time ECG signal monitoring system detect 17 abnormal ECG signal, the accuracy is 85%. This systems efficient for detect the abnormal of ECG signal in real-time.

An IoT-Based Remote Health Monitoring System for Smart Healthcare

2020 ◽  
pp. 231-254
Author(s):  
Uday Maji ◽  
Rohan Mandal ◽  
Saurav Bhattacharya ◽  
Shalini Priya
Keyword(s):  
Internet Of Things ◽  
Monitoring System ◽  
Health Monitoring ◽  
Remote Monitoring ◽  
Ecg Signal ◽  
Smart Healthcare ◽  
Electrocardiogram Ecg ◽  
Monitoring Devices ◽  
Remote Health Monitoring System ◽  
Remote Health

Many automated health monitoring devices detect health abnormalities based on gleaned data. One of the effective approaches of monitoring a senior cardiac patient is the analysis of an Electrocardiogram (ECG) signal, as proven by various studies and applications. However, diagnosis results must be communicated to an expert. An intelligent and effective technology gaining wide popularity known as ‘internet of things' or ‘IoT' allows remote monitoring of the patient.

scholarly journals Mobile Messaging Services-Based Personal Electrocardiogram Monitoring System

2009 ◽  
Vol 2009 ◽  
pp. 1-7 ◽  
Author(s):  
Ashraf A. Tahat
Keyword(s):  
Mobile Phone ◽  
Monitoring System ◽  
Low Cost ◽  
Vital Signs ◽  
Smart Phone ◽  
Ecg Signal ◽  
Area Network ◽  
Application Software ◽  
Data Services ◽  
Electrocardiogram Monitoring

A mobile monitoring system utilizing Bluetooth and mobile messaging services (MMS/SMSs) with low-cost hardware equipment is proposed. A proof of concept prototype has been developed and implemented to enable transmission of an Electrocardiogram (ECG) signal and body temperature of a patient, which can be expanded to include other vital signs. Communication between a mobile smart-phone and the ECG and temperature acquisition apparatus is implemented using the popular personal area network standard specification Bluetooth. When utilizing MMS for transmission, the mobile phone plots the received ECG signal and displays the temperature using special application software running on the client mobile phone itself, where the plot can be captured and saved as an image before transmission. Alternatively, SMS can be selected as a transmission means, where in this scenario, dedicated application software is required at the receiving device. The experimental setup can be operated for monitoring from anywhere in the globe covered by a cellular network that offers data services.

scholarly journals Classification of Multi Heart Diseases With Android Based Monitoring System

2020 ◽  
pp. 14-22
Keyword(s):  
Feature Extraction ◽  
Heart Diseases ◽  
Confusion Matrix ◽  
Predictive Coding ◽  
Classification Performance ◽  
Support Vector ◽  
Ecg Signal ◽  
Linear Predictive Coding ◽  
Electrocardiogram Ecg

Electrocardiogram (ECG) examination via computer techniques that involve feature extraction, pre-processing and post-processing was implemented due to its significant advantages. Extracting ECG signal standard features that requires high processing operation level was the main focusing point for many studies. In this paper, up to 6 different ECG signal classes are accurately predicted in the absence of ECG feature extraction. The corner stone of the proposed technique in this paper is the Linear predictive coding (LPC) technique that regress and normalize the signal during the pre-processing phase. Prior to the feature extraction using Wavelet energy (WE), a direct Wavelet transform (DWT) is implemented that converted ECG signal to frequency domain. In addition, the dataset was divided into two parts , one for training and the other for testing purposes Which have been classified in this proposed algorithm using support vector machine (SVM). Moreover, using MIT AI2 Companion was developed by MIT Center for Mobile Learning, the classification result was shared to the patient mobile phone that can call the ambulance and send the location in case of serious emergency. Finally, the confusion matrix values are used to measure the proposed classification performance. For 6 different ECG classes, an accuracy ration of about 98.15% was recorded. This ratio became 100% for 3 ECG signal classes and decreases to 97.95% by increasing ECG signal to 7 classes.

scholarly journals Designing ECG Monitoring Healthcare System Based on Internet of Things Blynk Application

2020 ◽  
Vol 1 (3) ◽  
pp. 106-111 ◽  
Author(s):  
Dathar Hasan ◽  
Ayad Ismaeel
Keyword(s):  
Monitoring System ◽  
Healthcare System ◽  
Medical Devices ◽  
Human Population ◽  
Continuous Monitoring ◽  
Heart Diseases ◽  
Medical Expenditure ◽  
Ecg Signal ◽  
Ecg Monitoring ◽  
Monitoring Process

Nowadays, heart diseases are considered to be the primary reasons for unexpected deaths. Thus, various medical devices have been developed by engineers to diagnose and scrutinize various diseases. Healthcare has become one of the most substantial issues for both individuals and government due to brisk growth in human population and medical expenditure. Many patients suffer from heart problems causing some critical threats to their life, therefore they need continuous monitoring by a traditional monitoring system such as Electrocardiographic (ECG) which is the most important technique used in measuring the electrical activity of the heart, this technique is available only in the hospital which is very costly and far for remote patients. The development of wireless technologies enables to build a network of connected devices via the internet. The proposed ECG monitoring system consists of AD8382 ECG sensor to read patient's data, Arduino Uno, ESP8266 Wi-Fi module, and IoT Blynk application. The implementation of the proposed ECG healthcare system enables the doctor to monitor the patient's remotely using IoT Blynk application installed on his smartphone for processing and visualizing the patient's ECG signal. The monitoring process can be done at any time and anywhere without the need for the hospital.

An IoT-Based Remote Health Monitoring System for Smart Healthcare

2021 ◽  
pp. 455-473
Author(s):  
Uday Maji ◽  
Rohan Mandal ◽  
Saurav Bhattacharya ◽  
Shalini Priya
Keyword(s):  
Internet Of Things ◽  
Monitoring System ◽  
Health Monitoring ◽  
Remote Monitoring ◽  
Ecg Signal ◽  
Smart Healthcare ◽  
Electrocardiogram Ecg ◽  
Monitoring Devices ◽  
Remote Health Monitoring System ◽  
Remote Health

Many automated health monitoring devices detect health abnormalities based on gleaned data. One of the effective approaches of monitoring a senior cardiac patient is the analysis of an Electrocardiogram (ECG) signal, as proven by various studies and applications. However, diagnosis results must be communicated to an expert. An intelligent and effective technology gaining wide popularity known as ‘internet of things' or ‘IoT' allows remote monitoring of the patient.

scholarly journals Electrocardiogram Fiducial Point Detector Using a Bilateral Filter and Symmetrical Point-Filter Structure

2021 ◽  
Vol 18 (20) ◽  
pp. 10792
Author(s):  
Tae-Wuk Bae ◽  
Kee-Koo Kwon ◽  
Kyu-Hyung Kim
Keyword(s):  
Noise Suppression ◽  
Signal To Noise Ratio ◽  
Heart Diseases ◽  
Bilateral Filter ◽  
Ecg Signal ◽  
Edge Preservation ◽  
T Wave ◽  
The Difference ◽  
Electrocardiogram Ecg ◽  
Point Detector

The characteristics or aspects of important fiducial points (FPs) in the electrocardiogram (ECG) signal are complicated because of various factors, such as non-stationary effects and low signal-to-noise ratio. Due to the various noises caused by the ECG signal measurement environment and by typical ECG signal deformation due to heart diseases, detecting such FPs becomes a challenging task. In this study, we introduce a novel PQRST complex detector using a one-dimensional bilateral filter (1DBF) and the temporal characteristics of FPs. The 1DBF with noise suppression and edge preservation preserves the P- or T-wave whereas it suppresses the QRS-interval. The 1DBF acts as a background predictor for predicting the background corresponding to the P- and T-waves and the remaining flat interval excluding the QRS-interval. The R-peak and QRS-interval are founded by the difference of the original ECG signal and the predicted background signal. Then, the Q- and S-points and the FPs related to the P- and T-wave are sequentially detected using the determined searching range and detection order based on the detected R-peak. The detection performance of the proposed method is analyzed through the MIT-BIH database (MIT-DB) and the QT database (QT-DB).

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