Skip to main navigation Skip to search Skip to main content

An open source mobile platform for psychophysiological self tracking

  • National Research Council of Italy

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Self tracking is a recent trend in e-health that refers to the collection, elaboration and visualization of personal health data through ubiquitous computing tools such as mobile devices and wearable sensors. Here, we describe the design of a mobile self-tracking platform that has been specifically designed for clinical and research applications in the field of mental health. The smartphone-based application allows collecting a) self-reported feelings and activities from pre-programmed questionnaires; b) electrocardiographic (ECG) data from a wireless sensor platform worn by the user; c) movement activity information obtained from a tri-axis accelerometer embedded in the wearable platform. Physiological signals are further processed by the application and stored on the smartphone's memory. The mobile data collection platform is free and released under an open source licence to allow wider adoption by the research community (download at: http://sourceforge.net/projects/psychlog/).
Original languageEnglish
Title of host publicationMedicine Meets Virtual Reality 19
EditorsJ.D. Westwood, R.S. Haluck, R.A. Robb, K.G. Vosburgh, S.W. Westwood, S. Senger, L. Felländer-Tsai
Pages136-138
Number of pages3
Volume173
DOIs
Publication statusPublished - 2012

Publication series

NameSTUDIES IN HEALTH TECHNOLOGY AND INFORMATICS

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Electrocardiography
  • Mental Health
  • Monitoring, Ambulatory
  • Pilot Projects
  • Remote Sensing Technology
  • Telecommunications

Fingerprint

Dive into the research topics of 'An open source mobile platform for psychophysiological self tracking'. Together they form a unique fingerprint.

Cite this