EMBEDDED SYSTEM FOR AUTOMATIC DETECTION OF HEART DISEASES USING ECG MACHINE
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, cardi
Project Title
EMBEDDED SYSTEM FOR AUTOMATIC DETECTION OF HEART DISEASES USING ECG MACHINE
Project Area of Specialization
Project 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
Type of Industry
Technologies
Sustainable Development Goals
Required Resources
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| 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 |
| Total in (Rs) | 62800 |
If you need this project, please contact me on contact@adikhanofficial.com
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