Heart Disease Prediction and monitoring System

The modern lifestyle or fast-forward life has a significant impact on the lives of people. Many people across the globe are suffering from heart-related diseases due to stress, lifestyle habits, and some from genes irrespective of their age. Early detection of cardiac diseases can decrease the morta

Project Title

Heart Disease Prediction and monitoring System

Project Area of Specialization

Software Engineering

Project Summary

The modern lifestyle or fast-forward life has a significant impact on the lives of people. Many people across the globe are suffering from heart-related diseases due to stress, lifestyle habits, and some from genes irrespective of their age. Early detection of cardiac diseases can decrease the mortality rate and overall complications.

So, the Heart Disease prediction and monitoring system is end-user support and an online consultation project.   It aims to provide a mobile application platform to predict the occurrences of heart disease based on various symptoms/parameters and remotely monitor the heart patients, to allow care teams/doctors to monitor and manage patients outside of traditional healthcare encounters.

For the prediction of heart disease, a system will take input a few symptoms and parameters from a user (normal person) that can be measured at home and will provide an output of a heart disease prediction using a machine learning model, along with a recommendation of consulting a doctor in case of positive prediction. A system will provide a user with an interface to take an online appointment with a doctor for a checkup.

Furthermore, a system will allow the doctors to examine and diagnose heart patients remotely, based on real-time monitoring and analysis of patient health data (i.e., collected using smart wearables(i.e. Health watch)). The application will use artificial intelligence technology to diagnose the diseases Broadly, Remote patient monitoring will include methods for 1) patient data collection, 2) data transmission, analysis, and presentation to the care team/doctors, and 3) clinical review and action in response to the RPM information. Moreover, In case of a heart condition gets intense; the system will issue a warning along with suggestions to a patient and update the doctor about the patient’s situation to avoid any inconvenience.

The application will be developed in such a way that any future enhancement can be easily implementable and will require minimal maintenance

Project Objectives

The main objectives of the Heart Disease prediction and monitoring system are:

•To facilitate the remote cardiac patients in getting the latest healthcare services so that patients located far from the medical care, facilities through remote monitoring systems, which might not be possible otherwise.

•To provide a more holistic view of a patient’s health over time, increase visibility into a patient’s adherence to treatment, and enable timely intervention before a costly care episode

•To Help clinicians strengthen their relationships with, and improve the experience of, their patients by using the data analyzed, to develop a personalized care plan and prescribe medicine for better outcomes.

• So we aim to create an app to predict heart disease in a normal person using some different parameters, an AI Rule-Based Expert System to Monitor a patient’s condition on daily basis, provide useful suggestions and recommendations, provide doctors an Access to the patients' data analysis and medical reports also enable them to prescribe the medicines remotely and also provide an interface between the doctor and the patients for two-way communication.

Project Implementation Method

Heart Disease prediction and monitoring system is end-user support and online consultation project.   It aims to provide a mobile application platform to predict the occurrences of heart disease based on various symptoms/parameters and remotely monitor the heart patients, to allow care teams/doctors to monitor and manage patients outside of traditional healthcare encounters.System development follows the incremental model for our application in which requirements are broken down into multiple modules. This model is completed in steps from phase design, implementation, testing/verification, and maintenance. Each iteration passes through the requirements, design, coding, and testing phases. Each release of the system adds functionality to the previous release until all the functionalities have been implemented.

Heart Disease prediction Module:

For the prediction of heart disease, a system will take input a few symptoms and parameters from a user (normal person) that can be measured at home and will provide an output of a heart disease prediction using a machine learning model, along with a recommendation of consulting a doctor in case of positive prediction.

• For Heart disease prediction we will be using the random forest algorithm as it offers a good accuracy of 95%. Furthermore, we follow the following steps,

•(1) Data collection,

•(2) Data preprocessing,

•(3) Implementation of the techniques,

• (4) Performance measure

Heart Disease Monitoring:

Remote patient monitoring will include methods for patient data collection, data transmission, analysis, and presentation to the care team/doctors, and clinical review and action in response to the collected information. Moreover, In case of a heart condition gets intense; the system will issue a warning along with suggestions to a patient and update the doctor about the patient’s situation to avoid any inconvenience.

Patient physiological data will be collected daily (2 times a day) using smart health wearable (health watch/ wrist band), Application will store the patient’s data, and analyze the parameters such as pulse rate, BP, cholesterol, medications, and exercise to keep the track of patient’s health. The application provides an interface for doctors and patients to get an insight into patients’ health remotely and provide treatment.

The remote Patient Monitoring module includes methods for:

1) patient data collection,

2) data transmission,

3) Analysis

4) presentation to the care team,

5) clinical review and action in response to the RPM information.

Block Diagram of a complete system:

Benefits of the Project

Following are the benefits of a project:

1. The modern lifestyle or fast-forward life has a significant impact on the lives of people. Many people across the globe are suffering from heart-related diseases due to stress, lifestyle habits, and some from genes irrespective of their age. Early detection of cardiac diseases can decrease the mortality rate and overall complications. At present, when one suffers from a particular disease, then the person has to visit a doctor which is time-consuming and costly too. Also, if the user is out of reach of doctors and hospitals it may be difficult for the user as the disease cannot be identified and diagnosed. So as our prediction algorithm has 95% of accuracy, our app will accurately predict heart disease in a normal person using some parameters. With the help of the system, the user will be able to know the probability of the disease with the given symptoms and parameters.
2. Apart from this, remote medical surveillance services are experiencing a growing demand, generally coming from chronically ill patients and particularly elderly people due to their frequent travel constraints. Also, the most widely accepted way of maintaining heart patients has been regular checkups with the doctor. However, it is not possible to monitor patients every day in all cases accurately and consultation of a patient for 24 hours by a doctor is not available since it requires more sapience, time, and expertise. So, if the above process can be completed using an automated program, it can save time as well as money and it could be easier for the patient which can make the process easier. . So our system will allow the doctors to examine and diagnose heart patients remotely, based on real-time monitoring and analysis of patient health data (i.e., collected-using-smart-health wearable).
3. It becomes important when people become old and with chronic diseases such as cardiovascular disease, are not able to track their condition properly without specialized medical personnel or sophisticated equipment for surveillance, especially in remote cities. So, our heart monitoring system that collects and monitors the health status of the user in real-time using smart health wearables, will benefit the patients by saving their money and time visiting clinics and medical centers unless there is a need for it.
4. Furthermore, As we know Health care is an essential part of human life. Researchers have found that the body gives signals of inappropriate heart functioning before a heart attack. So, Heart Patients need periodic monitoring of vital parameters and appropriate treatments based on medical data and health status. So, In case of a heart condition gets intense; our system will issue a warning along with suggestions to a patient and update the doctor about the patient’s situation to avoid any inconvenience.

Technical Details of Final Deliverable

1. Heart Disease Prediction and Monitoring Software (Android app)
2. User Manual documents
3. Project Documentation 
4. SRS and Design Document
5. App launch on Playstore

Final Deliverable of the Project

HW/SW integrated system

Core Industry

Health

Other Industries

IT , Medical , Others

Core Technology

Artificial Intelligence(AI)

Other Technologies

Wearables and Implantables, Big Data

Sustainable Development Goals

Good Health and Well-Being for People, Partnerships to achieve the Goal

Required Resources

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