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Crowdsourced Data Collection of Physical Activity and Health Status: An App Solution


Daniel Kelly, Brian Caulfield, Kevin Curran

Publication Type: 
Refereed Conference Meeting Proceeding
Health status measurements are vital in understanding a patient’s health. However, current means of measuring health status, such as questionnaires, are limited. Research has shown that there is a need for more objective and accurate methods of measuring health status. We postulate that novel sensor solutions could be used to make observations about a patients’ behaviour and make predictions relating to their health status. In order to achieve this overall goal, the problem of building a dataset comprising behaviour observations, from sensors, and health status measure must be addressed. In this work, we propose a crowd-sourced solution to this dataset problem where a Smartphone App is developed in order to facilitate in the collection of behaviour data, via sensors, and health status information. Results show that, after just 4 months, 1311 people have downloaded the App and 541 participants have completed a health status questionnaire (SF-36). Preliminary analysis of the data also shows a statistically significant correlation between the amount of time a participant is active and the health status of the participant.
Conference Name: 
International Conference on Wireless Mobile Communication and Healthcare MobiHealth 2016:
Digital Object Identifer (DOI): 
Publication Date: 
Research Group: 
National University of Ireland, Dublin (UCD)
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