Home > Research > Publications & Outputs > Mobile app for stress monitoring using voice fe...

Associated organisational unit

Electronic data

  • EHB_2015_paper_166

    Rights statement: ©2015 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

    Accepted author manuscript, 260 KB, PDF-document

    Available under license: CC BY: Creative Commons Attribution 4.0 International License

Links

Text available via DOI:

View graph of relations

Mobile app for stress monitoring using voice features

Research output: Contribution in Book/Report/ProceedingsPaper

Published
  • Virginia Sandulescu
  • Sally Andrews
  • David Ellis
  • Radu Dobrescu
  • Oscar Martinez-Mozos
Close
Publication date19/11/2015
Host publicationE-Health and Bioengineering Conference (EHB), 2015
PublisherIEEE
Pages1-4
Number of pages4
ISBN (Print)9781467375450
<mark>Original language</mark>English

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.

Bibliographic note

©2015 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.