Chi Harold Liu, Jiajia Wen, et al.
INFOCOM WKSHPS 2011
Proposed is a light-weight unsupervised decision tree based classification method to detect the user's postural actions, such as sitting, standing, walking and running as user states by analysing the data from a smartphone accelerometer sensor. The proposed method differs from other approaches by applying a sufficient number of signal processing features to exploit the sensory data without knowing any a priori information. Experiments show that the proposed method still makes a solid differentiation in user states (e.g. an above 90% overall accuracy) even when the sensor is operated under slower sampling frequencies. © The Institution of Engineering and Technology 2013.
Chi Harold Liu, Jiajia Wen, et al.
INFOCOM WKSHPS 2011
Chi Harold Liu, Ting He, et al.
WCNC 2010
Chi Harold Liu, Jun Fan, et al.
IEEE TETC
Yili Gong, Wenjie Wang, et al.
INFOCOM WKSHPS 2011