Towards detection of bad habits by fusing smartphone and smartwatch sensors

Muhammad Shoaib, Stephan Bosch, Hans Scholten, Paul J. M. Havinga, Ozlem Durmaz Incel
2015 2015 IEEE International Conference on Pervasive Computing and Communication Workshops (PerCom Workshops)  
Recently, there has been a growing interest in the research community about using wrist-worn devices, such as smartwatches for human activity recognition, since these devices are equipped with various sensors such as an accelerometer and a gyroscope. Similarly, smartphones are already being used for activity recognition. In this paper, we study the fusion of a wristworn device (smartwatch) and a smartphone for human activity recognition. We evaluate these two devices for their strengths and
more » ... nesses in recognizing various daily physical activities. We use three classifiers to recognize 13 different activities, such as smoking, cannot be recognized with a smartphone in the pocket position alone. We show that the combination of a smartwatch and a smartphone recognizes such activities with a reasonable accuracy. The recognition of such complex activities can enable well-being applications for detecting bad habits, such as smoking, missing a meal, and drinking too much coffee. We also show how to fuse information from these devices in an energy-efficient way by using low sampling rates. We make our dataset publicly available in order to make our work reproducible.
doi:10.1109/percomw.2015.7134104 dblp:conf/percom/ShoaibBSHI15 fatcat:vudnb2hmife2tbnpsqwus54cqi