mQoL smart lab
Alexandre De Masi, Matteo Ciman, Mattia Gustarini, Katarzyna Wac · 2016
As a base for hypothesis formulation and testing, accurate, timely and reproducible data collection is a challenge for all researchers. Data collection is especially challenging in uncontrolled environments, outside of the lab and when it involves many collaborating disciplines, where the data must serve quality research in all of them. In this paper, we present own "mQoL Smart Lab" for interdisciplinary research efforts on individuals' "Quality of Life" improvement. We present an evolution of our current in-house living lab platform enabling continuous, pervasive data collection from individuals' smartphones. We discuss opportunities for mQoL stemming from developments in machine learning and big data for advanced data analytics in different disciplines, better meeting the requirements put on the platform.