Research Article
Crowdsourced Data Collection of Physical Activity and Health Status: An App Solution
@INPROCEEDINGS{10.1007/978-3-319-58877-3_20, author={Daniel Kelly and Brian Caulfield and Kevin Curran}, title={Crowdsourced Data Collection of Physical Activity and Health Status: An App Solution}, proceedings={Wireless Mobile Communication and Healthcare. 6th International Conference, MobiHealth 2016, Milan, Italy, November 14-16, 2016, Proceedings}, proceedings_a={MOBIHEALTH}, year={2017}, month={6}, keywords={}, doi={10.1007/978-3-319-58877-3_20} }
- Daniel Kelly
Brian Caulfield
Kevin Curran
Year: 2017
Crowdsourced Data Collection of Physical Activity and Health Status: An App Solution
MOBIHEALTH
Springer
DOI: 10.1007/978-3-319-58877-3_20
Abstract
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.