Wearable sensor based human posture recognition
Jianwu Wang, Zhichuan Huang, Wenbin Zhang, Ankita Patil, Ketan Patil, Ting Zhu, Eric J. Shiroma, Mitchell Aaron Schepps, Tamara B. Harris · 2016
Human posture recognition has a wide range of applications including elderly care and video surveillance. This paper discusses how to recognize human postures using wearable devices. From real-world data, we analyze the challenges in terms of result performance, recognition efficiency and sensor selection. To deal with the challenges, we present our design with five techniques: i) oversampling and undersampling methods, ii) ensemble learning, iii) sensor selection, iv) stream data classification and v) post-processing techniques. We verify our design and show our findings through extensive experiments on real-world data, which shows our approach can achieve up to 91.5% overall weighted average accuracy for all three postures. We also discuss possible extensions of our work.