Idea Details

Team and Contact Details

SNo Student Name School Degree Year Email
1Suleman TahirCEMEUndergraduateFourthsuleman1231@hotmail.com
1Umair NadeemCEMEUndergraduateFourthumair.nadeem37@mts.ceme.edu.pk
1Hamza AzamCEMEUndergraduateFourthhamza.azam37@mts.ceme.edu.pk
1Muazzam AliCEMEUndergraduateFourthmuazam.ali37@mts.ceme.edu.pk

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: ECG monitoring
Slogan: Its all in the pulse
Supervisor Name: Dr. Nauman Razzaq
Supervisor Designation: Associate Professor
Supervisor School: College of Electrical and Mechanical Engineering(CEME)
Supervisor Department: Department of Mechatronics Engineering
Contact number: +923338124894
Email ID: nauman.razzaq@yahoo.com
Abstract:
    Smart phone based ECG monitoring portable device with real time feature extraction and wireless transmission
What is the unmet need in society that your idea will fulfill ?
    1 out of 4 deaths in USA is due to heart disease. There is a need for continuous monitoring of heart to check for any abnormalities and to start early treatment if any abnormality arises.
Who needs it ? How many would benefit ?
   Everyone with a heart issue needs this device for monitoring the electrical activity of one's heart. 1 out of 4 people in USA is dying of heart diseases, so the number is quite large as to how many would benefit from this device
How will the solution works
    We have used analogue front end to measure the electrical activity of the heart and this Ecg signal is fed to a smartphone via microcontroller ESP32 . Feature extraction algorithm is implemented at this stage to detect features at real time and similarly, the data is transmitted to other cellular device via wireless means.
Who are your competitors ? How is your solution different
    Our main competitor is Holter monitor that provides offline feature extraction. Our device is different in a sense that it provides real time feature extraction functionality that is more beneficial to the people as compare to offline feature extraction.
Status: Approved
Entry Date & Time: 2018-12-23 (1158)