IoT Based Heart Attack Monitoring and Prediction System

Project Title

IoT Based Heart Attack Monitoring and Prediction System

Project Area of Specialization Electrical/Electronic EngineeringProject Summary

IoT based heart attack monitoring and Prediction system is related to medical and healthcare field, it is made to improve healthcare facilities in our world and to make it easier for everyone to take care of their health. It is a device that our world needs the most, it consists of a few sensors working with the microcontroller which monitors the basic parameters of a person’s body, using Internet of things, cloud computing and machine learning techniques it predicts the upcoming heart attack before it happens.

The whole process of the device is autonomous, that means once a user wears this device it starts monitoring the heart health right away. The system deals with the knowledge domains like the Internet of things, machine learning, embedded systems, cloud computing and sensor interfacing etc.

Project Objectives

The main objectives of this project are

• mainly to make a device that can monitor and predict the heart attack by using a few sensors for monitoring health parameters that are related to heart attack and then applying machine learning algorithms to predict the final result.
• Another objective of the making is to introduce a wearable device commercially to everyone so that they don’t have to rely on doctors and hospital for their heart condition every day. Which is a clear way means this device will monitor the patient’s health real-time and save the previous history of that person in the cloud for later use. This way a patient can show his weekly or monthly progress to his personal doctor so that he can analyze the weekly/monthly health patterns.
• One of the main and very productive objective or goal was to interlink Electrical engineer, telecommunication, cloud computing and machine learning for the betterment of the healthcare facilities.
• This thesis explains how to make a low cost but cost-effective and very productive device that can change the future of medical filed in coming days.

Project Implementation Method

The scope of this project is divided into two parts.

1. Hardware Part: for measuring health parameters

this part is consisting of esp-32 dev board along with the wearable sensors network, which is used to monitor the health parameters like, ECG, blood pressure, heart rate and chest pain etc. Wi-Fi will enable the device to make a connection in between the clouds to make continuous receiving and transforming of the data.

1. Software Part (Cloud): for collecting data and applying Machine Learning algorithms

This part is mainly consisting of cloud computing and machine learning algorithms. The data from the wearable hardware device is being sent to the firebase cloud where this data is being fetched to the google cloud platform for implementing machine learning techniques to predict the final result.

Benefits of the Project

This device deals with a lot of electrical engineering fields such as,

1. Communication between devices
2. Internet of things
3. Sensors interfacing
4. Circuit analyses
5. Machine Learning
6. Cloud Computing
7. Microcontrollers and Processors
8. Datamining and
9. Servers interfacing etc

   Every day we see people dying out of heart attacks and strokes, there really was the need for a device which can predict the heart attack or any other cardiovascular disease before it happens.

   This device has been created to fulfil that space in the field of healthcare for the betterment of society. It is made with a goal to minimize the death toll due to CVDs that is increasing every year dramatically and to save the lives of millions of people all around the globe. It is made to make quick action possible and let authorities act fast in case of emergencies so that life can be saved. This device can be lifesaving tech for many people.

Technical Details of Final Deliverable

The final product will be:

A wearable device made up of wearable sensors like ECG, Heart Rate and Blood Pressure, it will have an LCD. when user will wear this device the device will monitor these parameters and send it to the cloud platforms to predict the final results.

Essential Hardware Components:

• Esp-32 Dev module as a microcontroller
• AD8232 ECG Sensor which is a sensor for ECG graph
• Heart Rate Sensor for measuring heart rate
• Blood Pressure Monitor: digital blood pressure monitors, can be easily found in the market
• LCD, to sow the results

Essential Software Components:

• firebase cloud for health parameter history
• Google cloud for the machine learning process
• Linear Regression.
• Logistic Regression.
• Decision Tree.
• SVM.
• Naive Bayes.
• kNN.
• K-Means.
• Random Forest.will be used and the algorithm with best accuracy will be selected

Final Deliverable of the Project HW/SW integrated systemCore Industry HealthOther Industries Telecommunication Core Technology Internet of Things (IoT)Other Technologies Artificial Intelligence(AI), Wearables and ImplantablesSustainable Development Goals Good Health and Well-Being for PeopleRequired Resources

Item Name	Type	No. of Units	Per Unit Cost (in Rs)	Total (in Rs)
			Total in (Rs)	32410
ESP-32 Dev Module	Equipment	2	1100	2200
ECG Sensor AD832	Equipment	2	3300	6600
Heart Rate Sensor	Equipment	2	550	1100
Blood Pressure Monitor	Equipment	2	5000	10000
Connection Wires Bundle	Equipment	3	120	360
Bread Boards	Equipment	3	150	450
Data Cable	Equipment	1	200	200
LCDs	Equipment	2	300	600
PCD Designing	Equipment	1	2000	2000
LEDs	Equipment	5	60	300
Sationary	Miscellaneous	10	60	600
Thesis/Prints	Miscellaneous	2	1500	3000
Transportation/Deliveries	Miscellaneous	5	1000	5000