ECG Classifier

Cardio Diseases (CD) is the leading global cause of death, accounting for more than 17.6 million deaths per year in 2016, a number that is expected to grow to more than 23.6 million by 2030. This death rate is very high and increasing by each passing day. Considering the above consequences and to ov

Project Title

ECG Classifier

Project Area of Specialization

Artificial Intelligence

Project Summary

Cardio Diseases (CD) is the leading global cause of death, accounting for more than 17.6 million deaths per year in 2016, a number that is expected to grow to more than 23.6 million by 2030. This death rate is very high and increasing by each passing day. Considering the above consequences and to overcome this ratio, ECG can be monitored and if any rare change occurs, may be reported. Precautions may be taken which will give less harm to health if compared to the situation when one does not know about the variation in the heart rate. ECG does not only measure the heart rate, but it also helps to measure heart rhythm(types of heartbeat), tracing the delays in transmission. Using ECG, several Heart diseases  can be diagnosed. Heart Inflammation, Cardiac Arrest and enlargement of the heart are some of those. Keeping in view the above usage of ECG, we are going to design ECG microcontroller reader. The objective  is to develop a wearable device which measure ECG and keep the log of ECG rate. This rate is maintained accordingly. Once the patient visits doctor, doctor me see the unusual change with respect to timing and may diagnose the disease. Not only this, if the person suffers from an unusual ECG which is alarming for health, it will notify the patient using android app. This app will keep the record of ECG and will generate alarm when needed. This may help to overcome sudden attacks and cardiac arrests. This device will contain ECG sensor combined with microcontroller and will connect to mobile

 application for keeping record using IOT.

Project Objectives

Project main objectives are listed below:

•  Make a real time ECG Classifier
•  Assemble hardware for getting ECG input
•  Connect Android Application with server to view records

 Testing whole system

Project Implementation Method

Our work of classification of ECG is divided into four phases. These four phases are getting ECG of patient, sending it to server for classification, classification and training of ECG by Machine Learning, giving result to the patient in the form of alert or notification through android app. Each phase is discussed in detailed below:

• Getting ECG of the patient.

We will use the ECG module to get the ECG input. This ECG module is AD8232. This will be connected with the Body of the patient to get the ECG. On the other side, it will be connected with the microcontroller. The microcontroller will get input from the ECG module. We will use the Arduino UNO microcontroller.

• Sending data to server for classification

After getting input from the ECG Module. Input will be sent to the server by using the internet. We will use A7 GSM GPRS GPS 3 in 1 module for internet connectivity. After getting internet connectivity the input will be sent to the server for the next step.

• Training and classification of ECG by using Machine Learning Algorithms.

This step is a major part of our project. This part makes our device unique from other devices available in the market. When the input is sent to the server, this input is classified by the trained model. The result of classification will be either normal or abnormal. This classification is done periodically which means the input will be sent multiple times and it will be classified and it will be stored in the database for the record. We will try different Machine Learning Algorithms for training the model like SVM, DT to get the best accuracy.

• Notifying the Patient through the app.

This phase needs the development of an android app. This app must be friendly enough to easily communicate with the user. There will an auto notifying system which will alarm the patient when his/her heart behaves abnormally. Apart from it, the user can view logs and the data rate of his/her heart. This data can be shown to doctors for further suggestion and prescription.

Benefits of the Project

An ECG gives two major kinds of information. First, by measuring time intervals on the ECG, a doctor can determine how long the electrical wave takes to pass through the heart. Finding out how long a wave takes to travel from one part of the heart to the next shows if the electrical activity is normal or slow, fast or irregular. Second, by measuring the amount of electrical activity passing through the heart muscle, a cardiologist may be able to find out if parts of the heart are too large or are overworked.

This is hectic for a person to get ECG check-up routinely. For this problem, we have a solution. The solution is Microcontroller based ECG Device to continuously monitor the ECG. The ECG signals will be sent to the server. The ECG signals will be classified as normal and abnormal signals. Our proposed work is analysing and classification of ECG signals to predict the normal heart control. This classification will be carried out by using different techniques of Machine Learning.

The ECG machines available today are different. Mostly ECG Machines are placed near the patient bed in the hospital or the clinic of doctors. They also need a consultant to use. Normal people cannot operate these devices. Only experts know how to operate them. To overcome the problem, we have used a module, which will take ECG and through Machine Learning it will classify ECG and will notify the person whether the ECG is normal or not. The classification of ECG will help us in finding the condition of the heart if it needs medical treatment. This can surely help a patient to know about his/her disease before any loss.

Technical Details of Final Deliverable

We will have a real time ECG Classifier, which will consist of folowing:

• Machine Learning based Classifier.
• A hardware device to take ECG.
• An Android Application tp show ECG.

Final Deliverable of the Project

HW/SW integrated system

Core Industry

Health

Other Industries

Core Technology

Artificial Intelligence(AI)

Other Technologies

Internet of Things (IoT)

Sustainable Development Goals

Good Health and Well-Being for People

Required Resources

If you need this project, please contact me on contact@adikhanofficial.com