Elsevier

Gait & Posture

Volume 35, Issue 4, April 2012, Pages 535-540
Gait & Posture

Analysis of a kinetic multi-segment foot model part II: Kinetics and clinical implications

https://doi.org/10.1016/j.gaitpost.2011.11.012Get rights and content

Abstract

Kinematic multi-segment foot models have seen increased use in clinical and research settings, but the addition of kinetics has been limited and hampered by measurement limitations and modeling assumptions. In this second of two companion papers, we complete the presentation and analysis of a three segment kinetic foot model by incorporating kinetic parameters and calculating joint moments and powers. The model was tested on 17 pediatric subjects (ages 7–18 years) during normal gait. Ground reaction forces were measured using two adjacent force platforms, requiring targeted walking and the creation of two sub-models to analyze ankle, midtarsal, and 1st metatarsophalangeal joints. Targeted walking resulted in only minimal kinematic and kinetic differences compared with walking at self selected speeds. Joint moments and powers were calculated and ensemble averages are presented as a normative database for comparison purposes. Ankle joint powers are shown to be overestimated when using a traditional single-segment foot model, as substantial angular velocities are attributed to the mid-tarsal joint. Power transfer is apparent between the 1st metatarsophalangeal and mid-tarsal joints in terminal stance/pre-swing. While the measurement approach presented here is limited to clinical populations with only minimal impairments, some elements of the model can also be incorporated into routine clinical gait analysis.

Highlights

► The addition of kinetics may help diagnose some foot and ankle disorders. ► We have provided normative multi-segment foot joint moments and powers. ► Kinetics can be incorporated into other multi-segment foot models during push off. ► Power transfer occurs between the 1st metatarsophalangeal and mid-tarsal joints.

Introduction

Kinematic multi-segment foot models have been increasingly used in clinical gait analysis and human movement research; however, the addition of kinetics to multi-segment foot modeling has been limited and hampered by force measurement limitations [1], [2], [3] and unproven modeling assumptions [4]. Scott and Winter [5] created an early kinetic model, calculating moments for eight separate foot joints. Analysis was confined to two-dimensions and force measurement methodology required the superposition of multiple trials interacting with a small custom-built force sensor. MacWilliams et al. [6] later proposed the only three-dimensional kinetic model found in the literature. Sixteen markers were used to create eight segments, requiring many assumptions on joint motion. To measure subarea forces, pressure and force data from separate trials were combined using an estimation method [1], [3], and the mediolateral forces between segments were neglected when calculating joint moments [2]. Given the limitations in repeatability and force measurement technology, these models may be too complex for use in clinical analysis.

The addition of kinetics to multi-segment foot modeling may provide additional insight into foot and ankle function as well as influence the evolution of multi-segment foot models. Measurement limitations may be more readily overcome and model parameters more robustly implemented in a model that is simpler than those previously attempted. In part I of this two-part study, a three-segment foot model was described and analyzed. Segment reference frames and joint centers were defined for use with inverse dynamics methods, and the model's kinematic behavior was characterized during normal gait. Segment rigidity analysis showed deformable behavior for the Forefoot segment during transitions between stance and swing, which should be kept in mind when evaluating angular velocities and joint powers (i.e. dependent on chosen tracking markers). In this companion paper, additional parameters needed for inverse dynamics calculations are defined, ground reaction forces are measured, and model kinetics are calculated. Implications for clinical gait analysis are discussed.

Section snippets

Overview

A particular hurdle in calculating multi-segment foot kinetics is measuring the complete ground reaction forces (GRFs comprising normal forces, shear forces, and a free moment) under each segment, as there are currently no commercially available devices capable of subarea GRF measurement. In this study, we chose to use two adjacent force platforms to directly measure GRFs. Practically, this required visual targeting of the force platforms; and because only two segments could be evaluated at a

Results

Differences between targeted and self-selected speed walking variables were minimal (Table 1), although there were several statistically significant trends. Stride time tended to be slightly increased in the MID model trials, while stance time was slightly increased in both the MID model and TOE model trials (Table 1A). There were no statistical differences in stride length. Joint angle RMS differences (Table 1B) were less than or equal to 1.0° at the ankle and mid-tarsal joints (MID model

Discussion

This second of two companion papers completes the description and analysis of a three segment kinetic multi-segment foot model. While effort was made to accurately model multi-segment foot mass distributions and inertia tensors, these play a minimal role in inverse dynamics calculations compared with the dominant ground reaction force [9]. This was further confirmed in this study by the small differences found in the ankle joint moments between the MID and FOOT models and between the TOE and

Conclusions

In these companion papers, we have presented and analyzed a simple kinetic multi-segment foot model that is less reliant on assumptions in force measurement and joint motions than those previously presented. While the methodology employed to measure subarea forces is not ideal for pathological gait, some elements of the model can be incorporated into routine analysis. The model and associated normal database may be of benefit in understanding and monitoring pathologies. Specific examples

Conflicts of interest statement

None.

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    NIOSH disclaimer: The findings and conclusions in this report are those of the authors and do not necessarily represent the views of the National Institute for Occupational Safety and Health.

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