Chest-mounted inertial measurement unit for pedestrian motion classification using continuous hidden Markov model

This paper presents a method for pedestrian motion classification based on MEMS inertial measurement unit (IMU) mounted on the chest. The choice of mounting the IMU on the chest provides the potential application of the current study in camera-aided inertial navigation for positioning and personal assistance. In the present work, five categories of the pedestrian motion including standing, walking, running, going upstairs, and going down the stairs are considered in the classification procedure. As the classification method, the continuous hidden Markov model (HMM) is used in which the output density functions are assumed to be Gaussian mixture models (GMMs). The correct recognition rates based on the experimental results are about 95%.