Research Article
Is Fitbit Fit for Sleep-Tracking? Sources of Measurement Errors and Proposed Countermeasures
@INPROCEEDINGS{10.1145/3154862.3154897, author={Zilu Liang and Bernd Ploderer and Mario Chapa-Martell}, title={Is Fitbit Fit for Sleep-Tracking? Sources of Measurement Errors and Proposed Countermeasures}, proceedings={11th EAI International Conference on Pervasive Computing Technologies for Healthcare}, publisher={ACM}, proceedings_a={PERVASIVEHEALTH}, year={2018}, month={1}, keywords={sleep health personal informatics wearable fitbit data quality hci}, doi={10.1145/3154862.3154897} }- Zilu Liang
Bernd Ploderer
Mario Chapa-Martell
Year: 2018
Is Fitbit Fit for Sleep-Tracking? Sources of Measurement Errors and Proposed Countermeasures
PERVASIVEHEALTH
ACM
DOI: 10.1145/3154862.3154897
Abstract
It is now easy to track one’s sleep through consumer wearable devices like Fitbit from the comfort of one’s home. However, compared to clinical measures, the data generated by such consumer devices is limited in its accuracy. The aim of this paper is to explore how users perceive accuracy issues, possible measurement errors and what can be done to address these issues. Through an interview study with 14 Fitbit users we identified three main sources of errors: (1) lack of definition of sleep metrics, (2) limitations in underlying data collection and processing mechanisms, and (3) lack of rigor in tracking approach. This paper proposes countermeasures to address these issues, both from the aspect of technological advancement and through engaging end-users more closely with their data.
