Classification of ECG data using Deep learning techniques
Make a cheap, portable single-lead ECG device. The captured stream will be then processed for predictions of what type of cardiac anomaly is present, if any. This will allow for at risk people to perform repeated scans for early detection of cardiac issues, as well for doctors to cut down on personn
Project Title
Classification of ECG data using Deep learning techniques
Project Area of Specialization
Project Summary
Make a cheap, portable single-lead ECG device. The captured stream will be then processed for predictions of what type of cardiac anomaly is present, if any. This will allow for at risk people to perform repeated scans for early detection of cardiac issues, as well for doctors to cut down on personnel cost and effort.
Project Objectives
- Make a cheap, portable ecg device
- An andriod application to show the results of the scans.
- Design and implement a deep learning model for processing of the ECg sample submitted.
Project Implementation Method
The project is implemented using deep learning, the model of which will be either deployed on the cloud or integrated into the andriod application. Work on which of these approaches might be more feasible is ongoing.
Benefits of the Project
It will allow doctors as well as individual patients to have a basic diagnostic device which will allow for early detection of cardiac diseases, as well as allow doctors to cut down on time and personnel cost for basic ECG scans.
Technical Details of Final Deliverable
The andriod app will show the details of the result of the ECG sample submitted, as well as history of previous scans. Multiple patients can be added. The results of the scans will be available in both concise and detailed format. The ECG may be collected using the basic device prototype
Final Deliverable of the Project
Core Industry
Other Industries
Core Technology
Other Technologies
Sustainable Development Goals
Required Resources
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| AD8232 | Equipment | 2 | 2500 | 5000 |
| ESP-32 WROOM | Equipment | 2 | 1500 | 3000 |
| battery | Equipment | 2 | 1000 | 2000 |
| breadboard | Equipment | 2 | 100 | 200 |
| misc circuit items | Equipment | 2 | 400 | 800 |
| housing for device | Miscellaneous | 2 | 1000 | 2000 |
| med. sensor pads | Miscellaneous | 1 | 5000 | 5000 |
| iot platform subscription | Equipment | 1 | 23000 | 23000 |
| google cloud subscription | Equipment | 1 | 36000 | 36000 |
| testing costs | Miscellaneous | 1 | 3000 | 3000 |
| Total in (Rs) | 80000 |
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