Interplay between Stride Velocity, Stride Frequency and Stride Length in Human Gait Transition

Doppelhammer N,Vereshchaga Y,Baumgartner W

doi:10.4172/1948-593x.1000209

Abstract

This paper presents the results of studying human gait transition outside the laboratory setting on a treadmill by means of wearable sensor technology. Combined inertial measurement and pressure sensor units embedded in footwear were employed to analyze the movement of the lower limbs during walk-run and run-walk transitions. Experimental data from 20 subjects was used to study three parameters - stride velocity, stride length and stride frequency. We focused on seven strides centered around the transition stride, that is, the stride in-between walking and running that has only a single floating phase. Three subjects underwent additional testing on a treadmill to capture the differences in kinematics between the two environments. The stride frequency varied least with both a subject’s individual transition behavior and the environment. The former can be concluded from the standard deviations evaluated for each stride, which were lower for stride frequency than for velocity and length. The latter was derived by comparing the results from within and outside the laboratory: Stride frequency shifted similarly in both cases, mainly within 2-4 strides, to the attractor of the new gait. Velocity profiles differed, with acceleration being more uniform and much lower on the treadmill. Stride lengths were inversely proportional: In the walk-run transition, when the belt of the treadmill was sped up, stride lengths decreased. In the run-walk transition, when the belt was slowed down, stride lengths increased. This phenomenon is attributable mainly to the dominant nature of the stride frequency, which forces changes in stride length in order to fulfill the velocity constraint. A non-laboratory environment lacks such a constraint, thus giving rise to free transition behavior. Stride frequency, being easy to measure, is well suited to analyzing and defining gait in a practical context.

Highlights

Development of assisting technologies which predict human intention and enable biomechanical analysis of movement for safety or rehabilitation purposes is of interest in many applications, including research into active exoskeletal robotic systems
We studied seven strides centered around the transition stride (TS) and investigated both the walk-run transition (WRT) and the run-walk transition (RWT)
Maximum deceleration in the RWT was registered between 3S and -1S at an acceleration of -0.45 m/s (Figure 3B)

Summary

Introduction

Development of assisting technologies which predict human intention and enable biomechanical analysis of movement for safety or rehabilitation purposes is of interest in many applications, including research into active exoskeletal robotic systems. Conclusions drawn from human gait transition investigated on a treadmill do not automatically apply outside the laboratory, since many kinematic, physiological and perceptual differences exist. This could be, for example, the absence of optical flow or differences in cognitive-affective mechanisms, such as when the subject is intimidated by unforeseeable accelerations. Studies have reported remarkable differences in gait transition between the two environments Both the spontaneously chosen acceleration and the preferred transition speed were considerably higher outside the laboratory than in the treadmill case [5,6]. Stride frequency and stride length are two further interesting parameters, because they are closely related to stride velocity via vs = fsls (1) This relationship is valid independent of the environment. It adapts rapidly and robustly to changes in gait and can be measured

Procedures

Results

Discussion