EMBEDDED SYSTEM FOR AUTOMATIC DETECTION OF HEART DISEASES USING ECG MACHINE

Project Title

EMBEDDED SYSTEM FOR AUTOMATIC DETECTION OF HEART DISEASES USING ECG MACHINE

Project Area of Specialization Artificial IntelligenceProject Summary

Electrocardiogram (ECG) is used to detect problems in the electric activity of a patient’s heart and, thereby, detect the type of heart disease. It allows detection of various characteristics in a patient’s heart including abnormalities in, size and position of chambers, damage to tissue, cardiac pathologies present, and heart rate. The problem with today’s ECG instruments is its inability to characterize the signals without a doctor’s complete evaluation and diagnosis. The study of ECG pattern and heart rate variability in terms of computer-based analysis and automatic detection and classification of diseases can be very helpful in diagnostics.

In this project, an ECG will be taken by ECG machine and this ECG signal will be sent to the embedded system. In the embedded system, features from an ECG signal will be extracted and classifier will be used to know about the disease type.

Project Objectives

• To implement AI algorithm on embedded system to characterise ECG waveform
• Classification and prediction of heart diseases using features and classification algorithms.

Project Implementation Method

The ECG machine will send results (waveform/features) to the Device after performing ECG ,Features will be extracted from ECG waveform based on P,Q, R, S,T points, which will be compared with an established database using machine learning algorithms which will classify the given sample and predict the most probable disease according to the results of ECG

Benefits of the Project

• Beneficial for the Doctor to detect different types of heart disease in minimum period of time.
• Increase in heart patient’s safety and improvement in the effectiveness of their treatment.
• Increment in the quality and efficiency of treatment of heart diseases in hospitals and heart centers.

Technical Details of Final Deliverable

Input: ECG

Output: Disease Prediction

Voltage : 12V DC

LCD size: 10inch

Gadget Dimensions: 12 x 8 x 4 inch

Microcontroller: Raspberry Pi B+ (1.4GHz , 1GB )

Final Deliverable of the Project HW/SW integrated systemType of Industry Medical Technologies Artificial Intelligence(AI)Sustainable 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)	62800
Raspberry Pi 3B+	Equipment	1	7300	7300
Raspberry Pi universal usb power supply	Equipment	1	1200	1200
Input: ECG Output: Disease Prediction Voltage : 12V DC LCD size: 7inc	Equipment	1	2300	2300
Device body	Equipment	1	2000	2000
ECG Machine	Equipment	1	50000	50000