Elsevier

Gait & Posture

Volume 29, Issue 2, February 2009, Pages 261-266
Gait & Posture

Does walking strategy in older people change as a function of walking distance?

https://doi.org/10.1016/j.gaitpost.2008.09.002Get rights and content

Abstract

This study investigates whether the spatio-temporal parameters of gait in the elderly vary as a function of walking distance. The gait pattern of older subjects (n = 27) over both short (SWD < 10 m) and long (LWD > 20 m) walking was evaluated using an ambulatory device consisting of body-worn sensors (Physilog®). The stride velocity (SV), gait cycle time (GCT), and inter-cycle variability of each parameter (CV) were evaluated for each subject. Analysis was undertaken after evaluating the errors and the test–retest reliability of the Physilog device compared with an electronic walkway system (GaitRite®) over the SWD with different walking speeds. While both systems were highly reliable with respect to the SV and GCT parameters (ICC > 0.82), agreement for the gait variability was poor. Interestingly, our data revealed that the measured gait parameters over SWD and LWD were significantly different. LWD trials had a mean increase of 5.2% (p < 0.05) in SV, and a mean decrease of 3.7% (p < 0.05) in GCT compared with SWD trials. Although variability in both the SV and GCT measured during LWD trials decreased by an average of 1% relative to the SWD case, the drop was not significant. Moreover, reliability for gait variability measures was poor, irrespective of the instrument and despite a moderate improvement for LWD trials. Taken together, our findings indicate that for valid and reliable comparisons, test and retest should be performed under identical distance conditions. Furthermore, our findings suggest that the older subjects may choose different walking strategies for SWD and LWD conditions.

Introduction

Gait is usually assessed using laboratory-based systems. Such measurements are considered as gold standard, despite significant limitations [1], [2]. A major disadvantage of such an approach is that laboratory-based measurement of human movement does not replicate the true conditions that the subjects are active in. In addition, unless a treadmill is used, space limitations often limit gait analysis to a few steps.

Advances in the technology of body-worn sensors during the last decade has encouraged investigators to use these sensors for measuring various aspects of human performance. These included spatio-temporal parameters of gait [1], [3], [4], joint and segment angles [5], [6], [7], [8], [9], [10], monitoring of daily physical activity [11], [12], [13], [14], [15], [16], [17], and evaluation of the risk of falling [18], [19] or fear of falling [20]. These studies are based on the use of miniaturized and integrated sensors in combination with lightweight, small measuring devices that can be carried without interfering with normal activity [1], [2], [11]. One of the main advantages of body-worn sensors compared to laboratory-based measuring systems is that they are ambulatory and can be used in free conditions continuously over long periods of time. Despite this key advantage, clinical protocols based on gait analysis in outdoor and long walking distance have not yet been established. On the other hand, since such technologies are not restricted to gait lab environment, there is no existing evidence on whether the extracted gait parameters in different walking distance conditions are comparable, or on the number of strides that should be considered sufficient to extract a reliable estimation of both the mean and variability of the parameters.

Recently, there has been a growing interest in measuring gait and gait variability for evaluation of risk of falling and for fall prevention [1], [2], [21], [22], [23], [24], [25], [26], [27], [28]. Gait measurements over long walking distances (e.g. 20 m) may enable the design of new paradigms for improved evaluation of the risk of falling. Furthermore, using a longer walking distance can enable researchers to accurately identify the length of the gait initiation phase preceding steady-state walking [29]. It must be emphasized that this identification is crucial, if only steady-state gait should be used for gait analysis.

The objective of this study was to investigate whether the walking distance affects spatio-temporal parameters of gait in the older population. To achieve this goal, we used an ambulatory body-worn sensor device (Physilog®) to acquire gait parameters in older individuals over short (SWD < 10 m) and long (LWD > 20 m) walkway distances. In addition, the measurement error and the test–retest reliability of the Physilog system were evaluated, by comparing its results with an electronic walkway (GaitRite®) over different gait speeds.

Section snippets

Subjects recruitment

Participants were enrolled from a sample that had finished participation in a study on vision, gait and balance. The participants were older than 70 years of age. To be included, subjects had a preferred gait speed of at least 0.5 m/s. This allowed them to follow the gait test protocol, which included several walks. Twenty-seven people (18 women and 9 men) with a mean age of 80.3 ± 5.0 years, a mean body height of 162 ± 7.2 cm and a mean body mass of 72.1 ± 13.5 kg participated. The study was approved

Instrument comparison

Some single walking trials (up to four per subject) were removed from the GAITRite database, because of technical errors in system to record the data. In addition, three subjects were removed from the Physilog database due to problems in the sensor attachment. Therefore, a total of 24 subjects, with both Physilog® and GAITRite results available, were included for comparison.

Table 1 summarizes the comparison between the GAITRite and Physilog systems. Agreement between the two systems was

Instrument comparison

In this study the main aim was to evaluate the effect of walking distance on four gait parameters (SV, GCT, CV(SV) and CV(GCT)). While Physilog estimated these parameters over short and long walking distances, the GaitRite system was only able to estimate gait parameters during SWD. Therefore it was considered important to evaluate the consistency of both systems in SWD before comparing SWD and LWD with Physilog.

Good agreement between Physilog® and GAITRite® confirmed the accuracy and precision

Conclusion

Comparison of the Physilog’s results with GaitRite over SWD trials, demonstrated that both systems are consistent for measuring spatio-temporal gait parameters. Moreover, by comparing the SWD and LWD trials, we observed that older people presumably choose a higher gait speed strategy over LWD distance. We can therefore conclude that for valid and reliable comparisons (e.g. between pre- and post-treatment conditions), test and retest should be performed under identical distance condition.

Another

Acknowledgments

This study was performed at the gaitlab at Department of Neuroscience (INM), Medical Faculty at the Norwegian University of Science and Technology in Trondheim, Norway. The authors would like to thank staff members at department of Neuroscience, NTNU who took part in the study; research assistant Kristin Taraldsen who part in planning the study and data collection, Engineer Espen Fredriksen who participated in the data collection and professor Gunnar Leivseth for giving access to the gait lab.

References (41)

  • H.B. Menz et al.

    Reliability of the GAITRite walkway system for the qualification of temporo-spatial parameters of gait in young and older people

    Gait Posture

    (2004)
  • R.G. Cutlip et al.

    Evaluation of an instrumented walkway for measurement of the kinematic parameters of gait

    Gait Posture

    (2000)
  • J.M. Bland et al.

    Regression analysis

    Lancet

    (1986)
  • I. Van den Akker-Scheek et al.

    Recovery of gait after short-stay total hip arthroplasty

    Arch Phys Med Rehabil

    (2007)
  • K. Aminian et al.

    Capturing human motion using body-fixed sensors: Outdoor measurement and clinical applications

    Comp Anim Virtual Worlds

    (2004)
  • W. Zijlstra et al.

    Mobility assessment in older people: new possibilities and challenges

    Eur J Ageing

    (2007)
  • H. Dejnabadi et al.

    Estimation and visualization of sagittal kinematics of lower limbs orientation using body-fixed sensors

    IEEE Trans Biomed Eng

    (2006)
  • H. Dejnabadi et al.

    Joint and segment angles of lower limbs in hip ostheoarthritis and total hip replaced patients measured using physilog system

    EORS

    (2002)
  • H. Dejnabadi et al.

    A new approach to accurate measurement of uniaxial joint angles based on a combination of accelerometers and gyroscopes

    IEEE Trans Biomed Eng

    (2005)
  • J. Favre et al.

    3D joint rotation measurement using MEMs inertial sensors: application to the knee joint

    (2006)
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