Uncertainty Visualization for Mobile and Wearable Devices Based Activity Recognition Systems

ABSTRACT

Mobile and wearable devices based activity recognition systems utilize built-in sensors to identify the activities performed by users pervasively. However, most of these systems do not explicitly present the sensing process to users and are prone to uncertainty. The presence of uncertainty makes users feel confused about the behaviors of activity recognition systems, which may affect the confidence of users. Uncertainty visualization has become an interesting research topic purporting to help users better understand systems. In this paper, we present an uncertainty visualization to reveal the process of mobile and wearable devices based activity recognition systems. We conducted an experiment to evaluate the uncertainty visualization by using a particular simulated mobile and wearable devices based activity recognition application. The results showed that the uncertainty visualization was effective in helping users understand and trust the judgments and inferences of the activity recognition application. Based on the advice of participants, we concluded a few directions to improve the uncertainty visualization.

Acknowledgments

This work was funded by the Ministry of Industry and Information Technology of China [grant number 2010ZX01042-002-003-001]; China Knowledge Centre for Engineering Sciences and Technology [grant number CKCEST-2014-1-5]; the Natural Science Foundation of China [grant number 60703040], [grant number 61332017]; the Science and Technology Department of Zhejiang Province [grant number 2011C13042], [grant number 2015C33002]. We would like to thank all the participants for all the time and energy they have contributed to this research.

Notes

¹ http://www.nytimes.com/projects/hurricanes/?nl=todaysheadlines&emc=thab1#!/2011/Irene

² http://www.sojump.com

Additional information

Notes on contributors

Miaomiao Dong

Miaomiao Dong is a PhD student in the College of Computer Science and Technology, Zhejiang University, China. Her research interests mainly focus on human–computer interaction.

Ling Chen

Ling Chen is an associate professor in the College of Computer Science and Technology, Zhejiang University, China, where he received his PhD in computer science in 2004. His research interests include ubiquitous computing, location-aware computing, HCI, and data mining.

Liwen Wang

Liwen Wang is a PhD student in the College of Computer Science and Technology, Zhejiang University, China. Her research interests mainly focus on human–computer interaction in LBS.

Xianta Jiang

Xianta Jiang is a PhD in the School of Engineering Science, Simon Fraser University, Canada. His research interests include ubiquitous computing and human–computer interaction.

Gencai Chen

Gencai Chen is a professor in the College of Computer Science and Technology, Zhejiang University, China. His research interests include location-aware computing, HCI, database management systems, and data mining.