Real Time Emotion Charting Device Using Physiological Signals

Project Title

Real Time Emotion Charting Device Using Physiological Signals

Project Area of Specialization Artificial IntelligenceProject Summary

The project is an Emotion Charting Device Using ECG and GSR Signals classifying into 7 emotions(happy,sad,fear,anger,neutral,disgust,surprise).Initially we trained the CNN Algorithm with an american dataset in(using the same sensors as ours) then we moved towards real time extraction from human body.The input to CNN algorithm is scalogram and spectogram of the signals(frequency spectrum).The accuracy of the product is 92%.Our project is successfully able to extract ECG and GSR from human body and chart into the 7 emotions

Project Objectives

-To help the autism patients

-To provide a means of expression to stroke patients especially suffering from aphasia(language imparment leading to inabilty to convert your thoughts into words or not being able to speak)

-To diagnose and treat people dealing with depressive disorders

Project Implementation Method

We have been using Shimmer sensors from Ireland to extract the signals.Initially we trained our algorithm a dataset using the same senors.(Completed)

-Extracted live signals from the human body and took it as input to our system and classified emotions(Completed).

-Trying to further  increase the accurcay(In progress)

-Testing our project on the users(In progress)

-Website for public access of results(in progress)

-Hardware Implementation of the device(on scedule)

Benefits of the Project

-Monitor the emotions of autism patients not capable of verbal and non verbal communications

-Will help physicatrists around the world to better monitor and treat their patients

-Provide means of expression to stroke patients

-Market Resarch/Customer Experience 

-Applicable on general public too

Technical Details of Final Deliverable

The final product will be a wearble device that will extract the the signals from the user with the sensors embeded on the device.Using the raspery pie the signals will be  uploded on cloud ,accessed for processing.The results will then be uploaded on the app for public access.The device will consist of an ECG module,GSR Sensor,raspery pie and lithium battery

Final Deliverable of the Project HW/SW integrated systemType of Industry Health Technologies Artificial Intelligence(AI)Sustainable Development Goals Good Health and Well-Being for PeopleRequired Resources

Item Name	Type	No. of Units	Per Unit Cost (in Rs)	Total (in Rs)
			Total in (Rs)	80000
Shimmer Development Kit	Equipment	1	70000	70000
Pcb,rasperypie,lithium battery,casing	Miscellaneous	1	10000	10000