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An open source mobile platform for psychophysiological self tracking

Academic Article
Publication Date:
2012
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/).
Iris type:
01.01 Articolo in rivista
Keywords:
Computerized experience sampling; ECG; wearable sensors; self-tracking; smartphones
List of contributors:
Pioggia, Giovanni; Tartarisco, Gennaro
Authors of the University:
PIOGGIA GIOVANNI
TARTARISCO GENNARO
Handle:
https://iris.cnr.it/handle/20.500.14243/226773
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