A kinematic method for footstrike pattern detection in barefoot and shod runners

Abstract

Footstrike patterns during running can be classified discretely into a rearfoot strike, midfoot strike and forefoot strike by visual observation. However, the footstrike pattern can also be classified on a continuum, ranging from 0% to 100% (extreme rearfoot to extreme forefoot) using the strike index, a measure requiring force plate data. When force data are not available, an alternative method to quantify the strike pattern must be used. The purpose of this paper was to quantify the continuum of foot strike patterns using an easily attainable kinematic measure, and compare it to the strike index measure. Force and kinematic data from twenty subjects were collected as they ran across an embedded force plate. Strike index and the footstrike angle were identified for the four running conditions of rearfoot strike, midfoot strike and forefoot strike, as well as barefoot. The footstrike angle was calculated as the angle of the foot with respect to the ground in the sagittal plane. Results indicated that the footstrike angle was significantly correlated with strike index. The linear regression model suggested that strike index can be accurately estimated, in both barefoot and shod conditions, in the absence of force data.

Conflict of interest statement

CONFLICT OF INTEREST

Study sponsors were not involved in the study design, collection, analysis and interpretation of data, writing of the manuscripts or the decision to submit the manuscript for publication.

Copyright © 2011 Elsevier B.V. All rights reserved.

Figures

Figure 1

Calculation of the SI. The location of the COP at initial contact along the longitudinal axis of the foot coordinate system (A), is normalized by the foot length and multiplied by 100 to obtain a percentage of the foot length.

Figure 2

Five anatomical (red) and 5 tracking (white) markers on the shoe. The calcaneal tracking markers were placed directly on the rearfoot, and can be seen through cutouts in the rear of the shoe. FSA was calculated as the angle between vector AB and anteroposterior axis in the lab coordinate system. The FSA in resting stance was subtracted from all values such that 0° corresponds with a flat foot.

Figure 3

Regression model of SI vs. FSA. Each of the 20 subjects were tested in all 4 conditions, thus, there are 60 shod data points (20 RFS, 20 MFS and 20 FFS determined by visual inspection), and 20 barefoot data points.