Human motion tracking and recognition using HMM by a mobile robot
International Journal of Intelligent Unmanned Systems
ISSN: 2049-6427
Article publication date: 8 February 2013
Abstract
Purpose
The aim of this paper is to develop autonomous mobile home healthcare robots, which are capable of observing patients’ motions, recognizing the patients’ behaviours based on observation data, and providing automatically calling for medical personnel in emergency situations. The robots to be developed will bring about cost‐effective, safe and easier at‐home rehabilitation to most motor‐function impaired patients (MIPs).
Design/methodology/approach
The paper has developed following programs/control algorithms: control algorithms for a mobile robot to track and follow human motions, to measure human joint trajectories, and to calculate angles of lower limb joints; and algorithms for recognizing human gait behaviours based on the calculated joints angle data.
Findings
A Hidden Markov Model (HMM) based human gait behaviour recognition taking lower limb joint angles and body angle as input was proposed. The proposed HMM based gait behaviour recognition is compared with the Nearest Neighbour (NN) classification methods. Experimental results showed that a human gait behaviour recognition using HMM can be achieved from the lower limb joint trajectory with higher accuracy than compared classification methods.
Originality/value
The research addresses human motion tracking and recognition by a mobile robot. Human gait behaviour recognition is HMM based lower limb joints and body angle data from extracted from kinect sensor at the mobile robot.
Keywords
Citation
Nergui, M., Yoshida, Y., Imamoglu, N., Gonzalez, J., Sekine, M. and Yu, W. (2013), "Human motion tracking and recognition using HMM by a mobile robot", International Journal of Intelligent Unmanned Systems, Vol. 1 No. 1, pp. 76-92. https://doi.org/10.1108/20496421311298152
Publisher
:Emerald Group Publishing Limited
Copyright © 2013, Emerald Group Publishing Limited