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ISway: a sensitive, valid and reliable measure of postural control
Open accessAbstract
BACKGROUND: 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. METHODS: 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. RESULTS: 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). CONCLUSIONS: 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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In the citing paper
“In addition, good agreement was found between sway and spatiotemporal gait measures from wearables and other established technologies [23, 31, 32].”
From Wearable sensors for clinical applications in epilepsy, Parkinson’s disease, and stroke: A mixed-methods systematic review (2018) · cites this paper as [23]
Experimental — accuracy not yet measuredIn the citing paper
“In PD, wearables were used to detect and quantify cardinal motor symptoms including bradykinesia [19], tremor [20, 21], and postural sway [22, 23] as well as medication-evoked adverse symptoms such as dyskinesia [24–27] and motor fluctuations [28, 29].”
From Wearable sensors for clinical applications in epilepsy, Parkinson’s disease, and stroke: A mixed-methods systematic review (2018) · cites this paper as [23]
In the citing paper
“Postural sway measures derived from wearables have been examined for test–retest reliability (ICC 0.55–0.86) [23] and the mediolateral sway and jerk were shown to be sensitive to detect progression of postural instability in PD over time [22].”
From Wearable sensors for clinical applications in epilepsy, Parkinson’s disease, and stroke: A mixed-methods systematic review (2018) · cites this paper as [23]
In the citing paper
“For example, the postural sway measures in PD have been shown to be reliable and sensitive to longitudinal changes in laboratory settings [22, 23].”
From Wearable sensors for clinical applications in epilepsy, Parkinson’s disease, and stroke: A mixed-methods systematic review (2018) · cites this paper as [23]
In the citing paper
“Predominantly acceleration signals were used in hospital and free-living settings, even though gyroscope signals have shown promise for increasing the sensitivity and specificity when measuring dyskinesia and postural instability in laboratory settings [23–26].”
From Wearable sensors for clinical applications in epilepsy, Parkinson’s disease, and stroke: A mixed-methods systematic review (2018) · cites this paper as [23]
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Metadata
- Authors
- Mancini, M., Salarian, A., Carlson-Kuhta, P., Zampieri, C., King, L., Chiari, L., & Horak, F. B.
- Affiliations
- Oregon Health & Science University (US)
- National Institutes of Health (US)
- University of Bologna (IT)
- Corresponding author
- Mancini, Martina
- Venue
- Journal of NeuroEngineering and Rehabilitation
- Published
- 2012
- Volume
- 9
- Issue
- 1
- Pages
- 59
- ISSN
- 1743-0003 (ISSN-L)
- PMC
- PMC3481400
- OpenAlex
- W2093375256
- Cited by
- 499
- References
- 48
- Citations by year
- 2026: 29 · 2025: 32 · 2024: 39 · 2023: 34 · 2022: 56 · 2021: 43 · 2020: 50 · 2019: 46 · 2018: 36 · 2017: 33 · 2016: 35 · 2015: 35 · 2014: 21 · 2013: 9 · 2012: 1
- FWCI
- 52.06
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Journal of NeuroEngineering and Rehabilitation (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna) (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Funders
- Kinetics Foundation
- National Institutes of Health (AG006457, 5r37ag006457-28)
- National Institute on Aging (R37-AG006457, R01AG006457)
- National Institute of Neurological Disorders and Stroke (RC1NS068678)
- NIH Clinical Center
- Topics
- Health Sciences › Health Professions › Physical Therapy, Sports Therapy and Rehabilitation › Balance, Gait, and Falls Prevention
- Life Sciences › Neuroscience › Cognitive Neuroscience › Motor Control and Adaptation
- Health Sciences › Medicine › Rehabilitation › Stroke Rehabilitation and Recovery
- Keywords
- postural sway, postural control, Parkinson's disease, wearable accelerometers, inertial sensors, balance assessment, test-retest reliability, concurrent validity, center of pressure, frequency domain analysis
- MeSH terms
- Acceleration, Aged, Algorithms, Biomechanical Phenomena, Data Interpretation, Statistical, Postural Balance, Female, Humans, Male, Middle Aged, Parkinson Disease, Reproducibility of Results
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