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      ISway: a sensitive, valid and reliable measure of postural control


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          Clinicians need a practical, objective test of postural control that is sensitive to mild neurological disease, shows experimental and clinical validity, and has good test-retest reliability. We developed an instrumented test of postural sway (ISway) using a body-worn accelerometer to offer an objective and practical measure of postural control.


          We conducted two separate studies with two groups of subjects. Study I: sensitivity and experimental concurrent validity. Thirteen subjects with early, untreated Parkinson’s disease (PD) and 12 age-matched control subjects (CTR) were tested in the laboratory, to compare sway from force-plate COP and inertial sensors. Study II: test-retest reliability and clinical concurrent validity. A different set of 17 early-to-moderate, treated PD (tested ON medication), and 17 age-matched CTR subjects were tested in the clinic to compare clinical balance tests with sway from inertial sensors. For reliability, the sensor was removed, subjects rested for 30 min, and the protocol was repeated. Thirteen sway measures (7 time-domain, 5 frequency-domain measures, and JERK) were computed from the 2D time series acceleration (ACC) data to determine the best metrics for a clinical balance test.


          Both center of pressure (COP) and ACC measures differentiated sway between CTR and untreated PD. JERK and time-domain measures showed the best test-retest reliability (JERK ICC was 0.86 in PD and 0.87 in CTR; time-domain measures ICC ranged from 0.55 to 0.84 in PD and from 0.60 to 0.89 in CTR). JERK, all but one time-domain measure, and one frequency measure were significantly correlated with the clinical postural stability score (r ranged from 0.50 to 0.63, 0.01 < p < 0.05).


          Based on these results, we recommend a subset of the most sensitive, reliable, and valid ISway measures to characterize posture control in PD: 1) JERK, 2) RMS amplitude and mean velocity from the time-domain measures, and 3) centroidal frequency as the best frequency measure, as valid and reliable measures of balance control from ISway.

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          Most cited references38

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          Measures of postural steadiness: differences between healthy young and elderly adults.

          Measures of postural steadiness are used to characterize the dynamics of the postural control system associated with maintaining balance during quiet standing. The objective of this study was to evaluate the relative sensitivity of center-of-pressure (COP)-based measures to changes in postural steadiness related to age. A variety of time and frequency domain measures of postural steadiness were compared between a group of twenty healthy young adults (21-35 years) and a group of twenty healthy elderly adults (66-70 years) under both eyes-open and eyes-closed conditions. The measures that identified differences between the eyes-open and eyes-closed conditions in the young adult group were different than those that identified differences between the eye conditions in the elderly adult group. Mean velocity of the COP was the only measure that identified age-related changes in both eye conditions, and differences between eye conditions in both groups. The results of this study will be useful to researchers and clinicians using COP-based measures to evaluate postural steadiness.
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            The Balance Evaluation Systems Test (BESTest) to differentiate balance deficits.

            Current clinical balance assessment tools do not aim to help therapists identify the underlying postural control systems responsible for poor functional balance. By identifying the disordered systems underlying balance control, therapists can direct specific types of intervention for different types of balance problems. The goal of this study was to develop a clinical balance assessment tool that aims to target 6 different balance control systems so that specific rehabilitation approaches can be designed for different balance deficits. This article presents the theoretical framework, interrater reliability, and preliminary concurrent validity for this new instrument, the Balance Evaluation Systems Test (BESTest). The BESTest consists of 36 items, grouped into 6 systems: "Biomechanical Constraints," "Stability Limits/Verticality," "Anticipatory Postural Adjustments," "Postural Responses," "Sensory Orientation," and "Stability in Gait." In 2 interrater trials, 22 subjects with and without balance disorders, ranging in age from 50 to 88 years, were rated concurrently on the BESTest by 19 therapists, students, and balance researchers. Concurrent validity was measured by correlation between the BESTest and balance confidence, as assessed with the Activities-specific Balance Confidence (ABC) Scale. Consistent with our theoretical framework, subjects with different diagnoses scored poorly on different sections of the BESTest. The intraclass correlation coefficient (ICC) for interrater reliability for the test as a whole was .91, with the 6 section ICCs ranging from .79 to .96. The Kendall coefficient of concordance among raters ranged from .46 to 1.00 for the 36 individual items. Concurrent validity of the correlation between the BESTest and the ABC Scale was r=.636, P<.01. Further testing is needed to determine whether: (1) the sections of the BESTest actually detect independent balance deficits, (2) other systems important for balance control should be added, and (3) a shorter version of the test is possible by eliminating redundant or insensitive items. The BESTest is easy to learn to administer, with excellent reliability and very good validity. It is unique in allowing clinicians to determine the type of balance problems to direct specific treatments for their patients. By organizing clinical balance test items already in use, combined with new items not currently available, the BESTest is the most comprehensive clinical balance tool available and warrants further development.
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              The relevance of clinical balance assessment tools to differentiate balance deficits.

              Control of balance is complex and involves maintaining postures, facilitating movement, and recovering equilibrium. Balance control consists of controlling the body center of mass over its limits of stability. Clinical balance assessment can help to assess fall risk and/or determine the underlying reasons for balance disorders. Most functional balance assessment scales assess fall risk and the need for balance rehabilitation but do not differentiate types of balance deficits. A system approach to clinical balance assessment can differentiate different kinds of balance disorders and a physiological approach can determine underlying sensorimotor mechanisms contributing to balance disorders. Objective measures of balance using computerized systems and wearable inertial sensors can bring more sensitive, specific and responsive balance testing to clinical practice.

                Author and article information

                J Neuroeng Rehabil
                J Neuroeng Rehabil
                Journal of NeuroEngineering and Rehabilitation
                BioMed Central
                22 August 2012
                : 9
                : 59
                [1 ]Department of Neurology, School of Medicine, Oregon Health & Science University, 505 NW 185th Avenue, Beaverton, OR, 97006, USA
                [2 ]Biomedical Engineering Unit, Department of Electronics, Computer Science & Systems, Alma Mater Studiorum-Universita’ di Bologna, Viale Risorgimento 2, 40136, Bologna, Italy
                [3 ]Functional and Applied Biomechanics Laboratory, Rehabilitation Medicine Department, National Institutes of Health, Clinical Center, Building 10, MSC 1604, Bethesda, MD, 20892, USA
                Copyright ©2012 Mancini et al.; 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.


                parkinson’s disease,accelerometers,postural control,inertial sensors
                parkinson’s disease, accelerometers, postural control, inertial sensors


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