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J. Sens. Actuator Netw. 2015, 4(4), 315-335; doi:10.3390/jsan4040315

Lesson Learned from Collecting Quantified Self Information via Mobile and Wearable Devices

1
Department of Computer Science and Engineering, University of California Riverside, Riverside 92521, CA, USA
2
Faculty of Computer Science, University of Vienna, Vienna A-1090, Austria
3
Department of Computer Science, Liverpool John Moores University, Liverpool L33AF, UK
4
Institute of Technology, University of Ontario, Oshawa L1H7K4, ON, Canada
5
Islamic Azad University Central Tehran Branch, Tehran 1469669191, Iran
*
Author to whom correspondence should be addressed.
Academic Editors: Yang Liu and Hongyi Wu
Received: 12 September 2015 / Revised: 27 October 2015 / Accepted: 27 October 2015 / Published: 5 November 2015
(This article belongs to the Special Issue Mobile Computing and Applications)
View Full-Text   |   Download PDF [855 KB, uploaded 5 November 2015]   |  

Abstract

The ubiquity and affordability of mobile and wearable devices has enabled us to continually and digitally record our daily life activities. Consequently, we are seeing the growth of data collection experiments in several scientific disciplines. Although these have yielded promising results, mobile and wearable data collection experiments are often restricted to a specific configuration that has been designed for a unique study goal. These approaches do not address all the real-world challenges of “continuous data collection” systems. As a result, there have been few discussions or reports about such issues that are faced when “implementing these platforms” in a practical situation. To address this, we have summarized our technical and user-centric findings from three lifelogging and Quantified Self data collection studies, which we have conducted in real-world settings, for both smartphones and smartwatches. In addition to (i) privacy and (ii) battery related issues; based on our findings we recommend further works to consider (iii) implementing multivariate reflection of the data; (iv) resolving the uncertainty and data loss; and (v) consider to minimize the manual intervention required by users. These findings have provided insights that can be used as a guideline for further Quantified Self or lifelogging studies. View Full-Text
Keywords: lifelogging; Quantified Self; user experiment; smartwatch; smartphone; data collection lifelogging; Quantified Self; user experiment; smartwatch; smartphone; data collection
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Rawassizadeh, R.; Momeni, E.; Dobbins, C.; Mirza-Babaei, P.; Rahnamoun, R. Lesson Learned from Collecting Quantified Self Information via Mobile and Wearable Devices. J. Sens. Actuator Netw. 2015, 4, 315-335.

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