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Idea - FICS

Atrial Fibrillation detection using ECG signals

Team and Contact Details

Student Name School Degree Year Email
MahelakaBS Computer ScienceUndergraduateFifth[email protected]
TabeedBS Computer ScienceUndergraduateFifth[email protected]
Numan AkramBS Computer ScienceUndergraduateFifth[email protected]

Inter School Idea ? No
Do you need expertises from another area: No
If Yes please provide details of expertises you need:

Idea Details

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)