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      Gait variability: methods, modeling and meaning

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          Abstract

          The study of gait variability, the stride-to-stride fluctuations in walking, offers a complementary way of quantifying locomotion and its changes with aging and disease as well as a means of monitoring the effects of therapeutic interventions and rehabilitation. Previous work has suggested that measures of gait variability may be more closely related to falls, a serious consequence of many gait disorders, than are measures based on the mean values of other walking parameters. The Current JNER series presents nine reports on the results of recent investigations into gait variability. One novel method for collecting unconstrained, ambulatory data is reviewed, and a primer on analysis methods is presented along with a heuristic approach to summarizing variability measures. In addition, the first studies of gait variability in animal models of neurodegenerative disease are described, as is a mathematical model of human walking that characterizes certain complex (multifractal) features of the motor control's pattern generator. Another investigation demonstrates that, whereas both healthy older controls and patients with a higher-level gait disorder walk more slowly in reduced lighting, only the latter's stride variability increases. Studies of the effects of dual tasks suggest that the regulation of the stride-to-stride fluctuations in stride width and stride time may be influenced by attention loading and may require cognitive input. Finally, a report of gait variability in over 500 subjects, probably the largest study of this kind, suggests how step width variability may relate to fall risk. Together, these studies provide new insights into the factors that regulate the stride-to-stride fluctuations in walking and pave the way for expanded research into the control of gait and the practical application of measures of gait variability in the clinical setting.

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          Heart Rate Variability : Standards of Measurement, Physiological Interpretation, and Clinical Use

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            Lower Extremity Function and Subsequent Disability: Consistency Across Studies, Predictive Models, and Value of Gait Speed Alone Compared With the Short Physical Performance Battery

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              Lower extremity function and subsequent disability: consistency across studies, predictive models, and value of gait speed alone compared with the short physical performance battery.

              Although it has been demonstrated that physical performance measures predict incident disability in previously nondisabled older persons, the available data have not been fully developed to create usable methods for determining risk profiles in community-dwelling populations. Using several populations and different follow-up periods, this study replicates previous findings by using the Established Populations for the Epidemiologic Study of the Elderly (EPESE) performance battery and provides equations for the prediction of disability risk according to age, sex, and level of performance. Tests of balance, time to walk 8 ft, and time to rise from a chair 5 times were administered to 4,588 initially nondisabled persons in the four sites of the EPESE and to 1,946 initially nondisabled persons in the Hispanic EPESE. Follow-up assessment for activity of daily living (ADL) and mobility-related disability occurred from 1 to 6 years later. In the EPESE, compared with those with the best performance (EPESE summary performance score of 10-12), the relative risks of mobility-related disability for those with scores of 4-6 ranged from 2.9 to 4.9 and the relative risk of disability for those with scores of 7-9 ranged from 1.5 to 2.1, with similar consistent results for ADL disability. The observed rates of incident disability according to performance level in the Hispanic EPESE agreed closely with rates predicted from models developed from the EPESE sites. Receiver operating characteristic curves showed that gait speed alone performed almost as well as the full battery in predicting incident disability. Performance tests of lower extremity function accurately predict disability across diverse populations. Equations derived from models using both the summary score and the gait speed alone allow for the estimation of risk of disability in community-dwelling populations and provide valuable information for estimating sample size for clinical trials of disability prevention.
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                Author and article information

                Journal
                J Neuroengineering Rehabil
                Journal of NeuroEngineering and Rehabilitation
                BioMed Central (London )
                1743-0003
                2005
                20 July 2005
                : 2
                : 19
                Affiliations
                [1 ]Laboratory for Gait & Neurodynamics, Movement Disorders Unit, Department of Neurology, Tel-Aviv Sourasky Medical Center, Tel-Aviv, Israel
                [2 ]Department of Physical Therapy, Sackler School of Medicine, Tel-Aviv University, Tel-Aviv, Israel
                [3 ]Division on Aging, Harvard Medical School, Boston, MA, USA
                Article
                1743-0003-2-19
                10.1186/1743-0003-2-19
                1185560
                16033650
                41a5258b-2e01-4140-b06e-6b1049976a62
                Copyright © 2005 Hausdorff; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 7 July 2005
                : 20 July 2005
                Categories
                Commentary

                Neurosciences
                aging,modeling,cognitive function,fractals,fall risk,dual tasking,parkinson's disease
                Neurosciences
                aging, modeling, cognitive function, fractals, fall risk, dual tasking, parkinson's disease

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