Idea - FICS

Handy ECG

Team and Contact Details

Student Name School Degree Year Email
Saleha NoorCEMEUndergraduateFourth[email protected]
Nawal FatimaCEMEUndergraduateFourth[email protected]
Muhammad Atif BabarCEMEUndergraduateFourth[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: Handy ECG
Slogan: Handy ECG can save life
Supervisor Name: Dr Hamid Jabbar
Supervisor Designation: Associate Professor
Supervisor School: CEME
Supervisor Department: Department of Mechatronics Engineering
Contact number: 0300 5274026
Email ID: [email protected]
Abstract:
    The main Idea is to develop a portable and IOT based ECG device that will be acquiring an ECG signal and will be using machine learning algorithm to check any abnormalities and detect arrhythmia.
What is the unmet need in society that your idea will fulfill ?
    Among a number of life taking diseases, heart diseases are on the top. ECG is the one of the oldest method for detecting cardiac diseases yet not efficiently Our project will focus on meeting this need in the society to timely detect cardiac diseases using more accurate and feasible device system.
Who needs it ? How many would benefit ?
   Our project focuses on good health and well being of society. This device will assist doctors in hospitals . The Main goal is to meet the limitations of already working ECG devices like Holter etc and utilizing machine learning to develop more precise and efficient system to detect heart diseases.
How will the solution works
    The Solution and Technical working of project is based on three parts, Firstly Data Acquisition of an ECG signal will be done by using appropriate method and circuitry. In the Second Step Machine learning algorithm will be utilized to check for any abnormalities and detecting arrhythmia. All the computing will be performed on the cloud server, This server will be interfaced with the microcontroller. After the processing results will be displayed on some useful medium.
Who are your competitors ? How is your solution different
    Our competitors are the ones dealing with ECG and ML in biomedical engineering. Our device is different from them in a way that normally such devices only detect the abnormal heart conditions but we are using machine learning to make portable device ''specifically detecting arrhythmia'' as well .
Status: new
Entry Date & Time: 2021-12-15 (1513)