Original article
Quantitative Gait Analysis in Parkinson’s Disease: Comparison With a Healthy Control Group

https://doi.org/10.1016/j.apmr.2004.08.012Get rights and content

Abstract

Sofuwa O, Nieuwboer A, Desloovere K, Willems AM, Chavret F, Jonkers I. Quantitative gait analysis in Parkinson’s disease: comparison with a healthy control group.

Objective

To compare gait parameters in Parkinson’s disease (PD) during the on-phase of medication cycle with those of healthy elderly control subjects.

Design

A group-comparison study.

Setting

Gait analysis laboratory of a university hospital.

Participants

Fifteen patients with PD and 9 healthy elderly controls.

Interventions

Not applicable.

Main outcome measures

Spatiotemporal, kinematic, and kinetic gait parameters.

Results

The PD spatiotemporal results showed a significant reduction in step length and walking velocity compared with controls. In the kinematics, the major feature of the PD group was a markedly reduced ankle plantarflexion excursion (at 50%–60% of the gait cycle). Most important, the kinetics showed reduced ankle push-off power and hip pull-off power. Unlike the control subjects, the patients with PD did not show any correlation between ankle generation (push-off) power and stride length (r=.19) or with gait speed (r=.29). Correction for walking velocity did not result in significant changes in the kinetics between the groups.

Conclusions

Reduced ankle (push-off) power generation and reduced hip flexion (pull-off) power persisted in PD gait despite being tested in the on-phase of the medication cycle. Lack of a correlation between ankle and hip power generation and walking velocity suggests that peripheral and central factors contribute to lack of forward progression. Patients with PD may benefit from intervention strategies that correct the kinematic and the kinetic gait components.

Section snippets

Participants

This study was part of a larger study in which 20 patients with PD and 10 healthy elderly control subjects were recruited. Informed consent was obtained according to the stipulations of the Declaration of Helsinki. For the purposes of this study, 15 patients with PD (11 men, 4 women) and 9 control subjects (3 men, 6 women) with comparable age, weight, and height (table 1) and with complete spatiotemporal, kinematic, and kinetic data sets were selected. The control subjects were selected from a

Spatiotemporal data

Table 2 shows the spatiotemporal variables of the PD and control groups. A significantly lower walking velocity (P=.004) and stride length (P=.002) was found for the PD group. They also appeared to have a lower cadence and spent more time in the double-support phase of gait, but these changes were not significant.

Kinematics

The kinematic differences between the 2 study groups were most pronounced at the ankle joint (table 3). The amount of maximal dorsiflexion observed in the stance and in the swing phase

Discussion

This study describes the spatiotemporal, kinematic, and kinetic variables of gait in subjects with PD compared with control subjects, as measured in the on-phase of their medication cycle. Despite being tested during the on-phase, gait abnormalities were still observed. Although few kinematic changes were found, possibly because of large variability in the data, pronounced differences between PD and controls were present in the kinetic profiles.

Conclusions

The data of our study confirm that ankle plantarflexors are mostly affected in PD gait. In addition, hip flexors appear to be implicated in the abnormal gait pattern in PD. Walking velocity did not largely affect the results, which suggests that it is not the cause of the kinetic gait deviations found. Moreover, lack of correlation between stride length, gait velocity, and ankle and hip power generation suggest that central factors, as well as peripheral factors, are involved in the diminished

Acknowledgments

This research came about as part of the RESCUE project. We thank Gert Kwakkel, PhD, and Erwin Van Wegen, MS, of the Vrije Universiteit of Amsterdam and Diana Jones, PhD, and Lynn Rochester, PhD, of Northumbria University (UK) for their contribution as collaborators within the RESCUE consortium.

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      QGA can be performed complementary to a clinical observations where spatio-temporal parameters are calculated such as walking speed, stride length and cadence. This analysis is usually performed on vulnerable patients to determine functional limitations or pathologies – orthopaedic, neurologic or traumatic – affecting gait parameters [1] and facilitate treatment decision making. Studying human movement and understanding the biomechanical aspects are essential to improve rehabilitation treatments [2].

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    Supported by the European Commission Framework V funding (grant no. QLRT-2001-00120).

    No party having a direct interest in the results of the research supporting this article has or will confer a benefit on the author(s) or on any organization with which the author(s) is/are associated.

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