• DocumentCode
    3736376
  • 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
  • fYear
    2015
  • Firstpage
    1
  • Lastpage
    4
  • 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"
  • Publisher
    ieee
  • Conference_Titel
    E-Health and Bioengineering Conference (EHB), 2015
  • Print_ISBN
    978-1-4673-7544-3
  • Type

    conf

  • DOI
    10.1109/EHB.2015.7391411
  • Filename
    7391411
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3736376