Recognizing human actions, reliably inferring their meaning and being able to potentially
exchange mutual social information are core challenges for autonomous systems when they …

Collecting experimental data from multiple sensing devices has just recently become quite
popular in behavioral and social sciences. Among existing devices, mobile phones stand …

Mobile sensing—that is, the ability to unobtrusively collect sensor data from built-in phone
and attached wearable sensors—have proven to be a powerful approach to understanding …

Advancement in smart sensing and computing technologies has provided a dynamic
opportunity to develop intelligent systems for human activity monitoring and thus assisted …

The burden of entry into mobile crowdsensing (MCS) is prohibitively high for human-subject
researchers who lack a technical orientation. As a result, the benefits of MCS remain beyond …

The increasing amount of human-related and/or human-originated data in current systems is
both an opportunity and a challenge. Nevertheless, despite relying on the processing of …

Current state-of-the-art systems in the literature using wearables are not capable of
distinguishing a large number of fine-grained and/or complex human activities, which may …

Objective To review published empirical literature on the use of smartphone-based passive
sensing for health and wellbeing. Material and methods A systematic review of the English …

Background: With the growing ubiquity of smartphones and wearable devices, there is an
increased potential of collecting passive sensing data in mobile health. Passive data such …

Cecilia Mascolo is a Reader in Mobile Systems in the Computer Laboratory, University of
Cambridge. She has published extensively in the areas of mobile computing, mobility and …