Student Name | School | Degree | Year | |
---|---|---|---|---|
Mahelaka | BS Computer Science | Undergraduate | Fifth | [email protected] |
Tabeed | BS Computer Science | Undergraduate | Fifth | [email protected] |
Numan Akram | BS Computer Science | Undergraduate | Fifth | [email protected] |
Inter School Idea ? | No |
Do you need expertises from another area: | No |
If Yes please provide details of expertises you need: |
Idea Name: | Atrial Fibrillation detection using ECG signals |
Slogan: | Take care of your lub dub, so you not don |
Supervisor Name: | saeed iqbal khattak |
Supervisor Designation: | Assistant Professor & Researcher |
Supervisor School: | SEECS |
Supervisor Department: | Computer Science |
Contact number: | 03339533493 |
Email ID: | [email protected] |
Abstract: | |
CVD is the major cause of the high death rate worldwide. and account for around 33% of all deaths 17.9 million people died from cardiovascular disease in 2019, globally 32 percent of deaths considering. by the cause of heart failure and strokes, 85% of death are accrued. By considering the issue of (AF). We are making a model that will detect the AF in a person | |
What is the unmet need in society that your idea will fulfill ? | |
As we have seen, heart issues are the most widely recognized issue all around the world. We propose a model that identifies the ongoing state of the patient. By carrying out this model the patient will get to know what is happening to the heart. assuming it is moderate or serious | |
Who needs it ? How many would benefit ? | |
People who are already heart patients having Cardiovascular diseases or a normal people who can be affected by CVD | |
How will the solution works | |
Our model will be an (API) server that will get information from any incorporated device(Hardware/Software) and return the anticipated result utilizing Deep learning calculation Random Forest of the patient spillage circumstance. We will calculate the (R-R) intervals in the ECG and compare different data sets for getting the final result for the patient. as we will be having 3 types of data sets (12 Electrocardiography, Atrial fibrillation, Angina). By getting the raw ECG data as input | |
Who are your competitors ? How is your solution different | |
As there are many devices that tell the heartbeat of a normal person, Our Solution is based on both normal and abnormal heartbeats. which can be integrated with any hardware that can detect the heart rate. and tells how much percent of (AF) or abnormal and normal heartbeat is present rtp 2023 | |
Status: | new |
Entry Date & Time: | 2022-12-30 (1850) |