Motion primitive-based human activity recognition using a bag-of-features approach

Human activity modeling and recognition using wearable sensors is important in pervasive healthcare, with applications including quantitative assessment of motor function, rehabilitation, and elder care. Previous human activity recognition techniques use a "whole-motion" model in which continuous sensor streams are divided into windows with a fixed time duration whose length is chosen such that all the relevant information in each activity...