An open source mobile platform for psychophysiological self tracking

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

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)

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
Pages (from-to)136-138
Number of pages3
JournalNot available
Volume173
Publication statusPublished - 2012

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