Thesis Topic Details

Topic ID:
3330
Title:
Are You Stressed? Detecting the onset of stress using mobile phones
Supervisor:
Salil Kanhere
Research Area:
Pervasive computing, Artificial Intelligence, Mobile Computing
Associated Staff
Assessor:
Mahbub Hassan
Topic Details
Status:
Active
Type:
R & D
Programs:
CS CE SE
Group Suitable:
Yes
Industrial:
No
Pre-requisites:
Android development, machine learning
Description:
Smartphones are open and programmable and come with a growing number of powerful embedded sensors, such as an accelerometer, digital compass, gyroscope, GPS, microphone, and camera, which are enabling new sensing applications across a wide variety of domains such as social networks, mobile health, gaming, entertainment, education and transportation.

Application delivery channels such as the AppStore and Market have transformed plain old cell phones into app phones, capable of downloading a myriad of applications in an instant.

My research group has worked on transforming the everyday smart phone into a cognitive phone by pushing intelligence to the phone and the computing cloud to make inferences about people's behavior, surroundings and their life patterns.

In this project, we will investigate if it is possible to detect if a person is stressed by observing subtle changes in the person's usage of his/her phone. Potential indicators of stress include: raised voice during phone calls, forceful tapping on the touch screen, excessive fidgeting, etc. We will develop a system that uses a variety of embedded sensors on the phone (accelerometers, microphone, touch screen, etc) to detect the onset of stress.
Comments:
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Past Student Reports
  Ronald Jiqin HUYNH in s2, 2012
Cough Detection using Mobile Phones
 

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