Original articleQuantitative Gait Analysis in Parkinson’s Disease: Comparison With a Healthy Control Group
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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2022, Measurement: Journal of the International Measurement ConfederationCitation Excerpt :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].
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.