Does walking strategy in older people change as a function of walking distance?
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)
- et al.
Spatio-temporal parameters of gait measured by an ambulatory system using miniature gyroscopes
J Biomech
(2002) - et al.
Estimation of gait cycle characteristics by trunk accelerometry
J Biomech
(2004) - et al.
Ambulatory measurement of 3D knee joint angle
J Biomech
(2008) - et al.
Ambulatory system for the quantitative and qualitative analysis of gait and posture in chronic pain patients treated with spinal cord stimulation
Gait Posture
(2004) - et al.
Improved physical activity in patients treated for chronic pain by spinal cord stimulation
Neuromodulation
(2005) - et al.
Relationships between dual-task related changes in stride velocity and stride time variability in healthy older adults
Hum Mov Sci
(2006) Gait dynamics, fractals and falls: finding meaning in the stride-to-stride fluctuations of human walking
Hum Mov Sci
(2007)- et al.
Distance to achieve steady state walking speed in frail elderly persons
Gait Posture
(2008) - et al.
Evaluation of an ambulatory system for gait analysis in hip osteoarthritis and after total hip replacement
Gait Posture
(2004) - et al.
The validity and reliability of the GAITRite system’s measurements: a preliminary evaluation
Arch Phys Med Rehabil
(2001)
Reliability of the GAITRite walkway system for the qualification of temporo-spatial parameters of gait in young and older people
Gait Posture
Evaluation of an instrumented walkway for measurement of the kinematic parameters of gait
Gait Posture
Regression analysis
Lancet
Recovery of gait after short-stay total hip arthroplasty
Arch Phys Med Rehabil
Capturing human motion using body-fixed sensors: Outdoor measurement and clinical applications
Comp Anim Virtual Worlds
Mobility assessment in older people: new possibilities and challenges
Eur J Ageing
Estimation and visualization of sagittal kinematics of lower limbs orientation using body-fixed sensors
IEEE Trans Biomed Eng
Joint and segment angles of lower limbs in hip ostheoarthritis and total hip replaced patients measured using physilog system
EORS
A new approach to accurate measurement of uniaxial joint angles based on a combination of accelerometers and gyroscopes
IEEE Trans Biomed Eng
3D joint rotation measurement using MEMs inertial sensors: application to the knee joint
Cited by (120)
How does weather and climate affect pedestrian walking speed during cool and cold seasons in severely cold areas?
2020, Building and Environment