Gait parameters that can be measured with simple instrumentation may hold promise for identifying individuals at risk of falling. Increased variability of gait is associated with increased risk of falling, but research on additional parameters indicates that local dynamic stability (LDS) of gait may also be a predictor of fall risk. The objective of the present study was to assess the association between gait variability, LDS of gait and fall history in a large sample of elderly subjects. Subjects were recruited and tested at a large national fair. One hundred and thirty four elderly, aged 50-75, who were able to walk without aids on a treadmill, agreed to participate. After subjects walked on a treadmill, LDS (higher values indicate more instability) and variability parameters were calculated from accelerometer signals (trunk worn). Fall history was obtained by self-report of falls in the past 12 months. Gait variability and short-term LDS were, individually and combined, positively associated with fall history. In conclusion, both increased gait variability and increased short-term LDS are possible risk factors for falling in the elderly.
Falls have major consequences both at societal (health-care and economy) and individual (physical and psychological) levels. Questionnaires to assess fall risk are commonly used in the clinic, but their predictive value is limited. Objective methods, suitable for clinical application, are hence needed to obtain a quantitative assessment of individual fall risk. Falls in older adults often occur during walking and trunk position is known to play a critical role in balance control. Therefore, analysis of trunk kinematics during gait could present a viable approach to the development of such methods. In this study, nonlinear measures such as harmonic ratio (HR), index of harmonicity (IH), multiscale entropy (MSE) and recurrence quantification analysis (RQA) of trunk accelerations were calculated. These measures are not dependent on step detection, a potentially critical source of error. The aim of the present study was to investigate the association between the aforementioned measures and fall history in a large sample of subjects (42 fallers and 89 non - fallers) aged 50 or older. Univariate associations with fall history were found for MSE and RQA parameters in the AP direction; the best classification results were obtained for MSE with scale factor τ = 2 and for maximum length of diagonals in RQA (72.5% and 71% correct classifications, respectively). MSE and RQA were found to be positively associated with fall history and could hence represent useful tools in the identification of subjects for fall prevention programs.
Fear of falling (FoF) in elderly frequently leads to decreased quality of life. FoF is suggested to be associated with changes in gait quality and muscle strength with aging. The aim of this study was to determine whether gait quality and maximal voluntary torque (MVT) of knee extensor muscles are associated with FoF. We hypothesized that high between-stride variability and local divergence exponent (LDE) of trunk kinematics in gait are associated with higher FoF in non-fallers, but not in fallers. Moreover, we hypothesized that knee extensor muscle strength is associated with a high variability and LDE of trunk kinematics during gait. 134 four adults, aged 62.4 (SD 6.2) years agreed to participate. FoF was assessed on a 10-point numerical rating scale. Subjects with at least one fall in the past 12 months were considered as fallers. LDE and variability were calculated from data of a trunk-mounted inertial-sensor collected during several minutes of treadmill walking. Maximal voluntary knee extension torque (MVT) was assessed isometrically. Fall history was an effect modifier in the association between LDE and FoF only, i.e. only subjects without fall history and a high LDE had a five times higher chance of reporting FoF. Gait variability was not associated with FoF. Low MVT was associated with FoF. Multivariate analysis demonstrated that LDE was more strongly associated with FoF than MVT. Decreased stability of gait as reflected in a high LDE and low muscle strength are associated with and a potential cause of FoF in subjects without fall history.
BackgroundGait variability and stability measures might be useful to assess gait quality changes after fall prevention programs. However, reliability of these measures appears limited.AimsThe objective of the present study was to assess the effects of measurement strategy in terms of numbers of subjects, measurement days and measurements per day on the power to detect relevant changes in gait variability and stability between conditions among healthy elderly.MethodsSixteen healthy older participants [65.6 (SD 5.9) years], performed two walking trials on each of 2 days. Required numbers of subjects to obtain sufficient statistical power for comparisons between conditions within subjects (paired, repeated-measures designs) were calculated (with confidence intervals) for several gait measures and for different numbers of trials per day and for different numbers of measurement days.ResultsThe numbers of subjects required to obtain sufficient statistical power in studies collecting data from one trial on 1 day in each of the two compared conditions ranged from 7 to 13 for large differences but highly correlated data between conditions, up to 78–192 for data with a small effect and low correlation.DiscussionLow correlations between gait parameters in different conditions can be assumed and relatively small effects appear clinically meaningful. This implies that large numbers of subjects are generally needed.ConclusionThis study provides the analysis tools and underlying data for power analyses in studies using gait parameters as an outcome of interventions aiming to reduce fall risk.
This study assessed effects of unilateral leg muscle fatigue (ULMF) on balance control in gait during the stance and swing phases of the fatigued leg in healthy elderly, to test the assumption that leg muscle strength limits balance control during the stance-phase. Ten subjects (aged 63.4, SD 5.5 years) walked on a treadmill in 4 conditions: unperturbed unfatigued, unperturbed fatigued, perturbed unfatigued, and perturbed fatigued. The perturbations were lateral trunk pulls just before contralateral heel contact. ULMF was evoked by unilateral squat exercise until task failure. Isometric knee extension strength was measured to verify the presence of muscle fatigue. Between-stride standard deviations and Lyapunov exponents of trunk kinematics were used as indicators of balance control. Required perturbation force and the deviation of trunk kinematics from unperturbed gait were used to assess perturbation responses. Knee extension strength decreased considerably (17.3% SD 8.6%) as a result ULMF. ULMF did not affect steady-state gait balance. Less force was required to perturb subjects when the fatigued leg was in the stance-phase compared to the swing-phase. Subjects showed a faster return to the unperturbed gait pattern in the fatigued than in the unfatigued condition, after perturbations in swing and stance of the fatigued leg. The results of this study are not in line with the hypothesized effects of leg muscle fatigue on balance in gait. The healthy elderly subjects were able to cope with substantial ULMF during steady-state gait and demonstrated faster balance recovery after laterally directed mechanical perturbations in the fatigued than in the unfatigued condition.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.