An open source mobile platform for psychophysiological self tracking

Andrea Gaggioli, Pietro Cipresso, Silvia Serino, Giovanni Pioggia, Gennaro Tartarisco, Giovanni Baldus, Daniele Corda, Giuseppe Riva

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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 preprogrammed 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 publicationStudies in Health Technology and Informatics
Pages136-138
Number of pages3
Volume173
DOIs
Publication statusPublished - 2012
EventMedicine Meets Virtual Reality 19: NextMed, MMVR 2012 - Newport Beach, CA, United States
Duration: Feb 9 2012Feb 11 2012

Other

OtherMedicine Meets Virtual Reality 19: NextMed, MMVR 2012
CountryUnited States
CityNewport Beach, CA
Period2/9/122/11/12

Keywords

  • Computerized experience sampling
  • ECG
  • Self-tracking
  • Smartphones
  • Wearable sensors

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics
  • Health Information Management

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