Sensing Human Walking: Algorithms and Techniques for Extracting and Modeling Locomotion



This chapter reports the most popular methods used to evaluate the main properties of human walking. We will mainly focus on: global parameters (such as step length, frequency, gait asymmetry and regularity), kinematic parameters (such as joint angles depending on time), dynamic values (such as the ground reaction force and the joint torques) and muscle activity (such as muscle tension). A large set of sensors have been introduced in order to analyze human walking in biomechanics and other connected domains such as robotics, human motion sciences, computer animation... Among all these sensors, we will focus on: mono-point sensors (such as accelerometers), multi-point sensors (such as flock of sensors, opto-electronic systems and video analysis), and dynamic sensors (such as force plates or electromyographic sensors). For the most popular systems, we will describe the most popular methods and algorithms used to compute the parameters described above. All along the chapter we will explain how these algorithms could provide original methods for helping people to design natural navigation in VR.


Motion analysis Gait analysis Motion sensors Gait parameters Walking Biomechanics Sensory information 


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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  1. 1.University Rennes2 RennesFrance

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