Smart Chair: What Can Simple Pressure Sensors under the Chairs' Legs Tell Us about User Activity?

In this paper, we investigate how much information about user activity can be extracted from simple pressure sensors mounted under the legs of a chair. We show that it is possible to detect not only different postures (0.826 accuracy for 5 subjects and 7 classes), but also subtle hand and head related actions like typing and nodding (0.880 accuracy for 5 subjects and 5 classes). Combining features related to postures and such simple actions, we can detect high-level activities such as working on a PC, watching a movie or eating in a continuous, real-life data stream. In a dataset of 105.6 hours recorded from 4 subjects, we achieved 0.783 accuracy for 7 classes. Keywords—ubiquitous computing; smart chair; resistive pres- sure sensor; activity recognition