Idea Details

Team and Contact Details

SNo Student Name School Degree Year Email
1Aqsa RahimCEMEUndergraduateFourthaqsa.rahim1@gmqil.com
1Khunsha NadeemCEMEUndergraduateFourthkhunsha.nadeem@hotmail.com
1Amna SagheerCEMEUndergraduateFourthkhunsha.nadeem@hotmail.com
1Zaid bin ShabirCEMEUndergraduateFourthzaidshabbir17@gmail.com

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: Emotion Charting
Slogan: Bring it Out
Supervisor Name: Dr Usman Akram
Supervisor Designation: Associate Professor
Supervisor School: EME College
Supervisor Department: Computer Engineering
Contact number: 03336913921
Email ID: usmakram@gmail.com
Abstract:
    The main idea of our project is to detect emotions using the real time monitoring of physiological signals. The processed data is sent to the website which can be accessed by the doctor or patients
What is the unmet need in society that your idea will fulfill ?
    It is very difficult to know the emotions of paralytic and stroke patients. The idea of our project is to detect the emotions of these kind of patients who can't express their emotions easily and then these emotions will be used for emotion charting that can be accessed by the doctors.
Who needs it ? How many would benefit ?
   It will be used to know the emotions of paralytic, stroke patients whose emotions can not be detected easily. Moreover it will be beneficial for the doctors I . e they can treat their patients according to their mental and emotional state. Patients family can also keep the track of the emotions.
How will the solution works
    To analyse patient’s physiological signals using signal processing and machine learning techniques for emotion charting. We will train the data using supervised learning and than we will correlate the testing data with the training data to detect the emotions. For training the data we will use machine learning algorithms I . e CNN.This data will be sent on a website where all the processed data can be viewed by the doctors and the patients family.
Who are your competitors ? How is your solution different
    The present solutions for emotion detection is feature and speak recognition. Our solution will be using physiological signals and machine learning techniques for emotion detection as they are useful for knowing the internal feelings of a person as compared to the other methods.
Status: Approved
Entry Date & Time: 2018-12-23 (1423)