Title :
Mobile app for stress monitoring using voice features
Author :
Virginia Sandulescu;Sally Andrews;David Ellis;Radu Dobrescu;Oscar Martinez-Mozos
Author_Institution :
Dept. of Automatic Control and Industrial Informatics, Politehnica University of Bucharest, Bucharest, Romania
Abstract :
The paper describes the steps involved in designing and implementing a mobile app for real time monitoring of mental stress using voice features and machine learning techniques. The app is easy to use and completely non-invasive. It is called StressID and it is available in the Google Play store. With the use of a server application presenting a web interface, interested parties may remotely monitor the stress states detected by the mobile app, enlarging the number of use case scenarios.
Keywords :
"Stress","Feature extraction","Mobile communication","Libraries","Biomedical monitoring","Monitoring","Support vector machines"
Conference_Titel :
E-Health and Bioengineering Conference (EHB), 2015
Print_ISBN :
978-1-4673-7544-3
DOI :
10.1109/EHB.2015.7391411