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Automatic Quantification of Tandem Walking Using a Wearable Device: New Insights Into Dynamic Balance and Mobility in Older Adults

Natalie Ganz, Eran Gazit, Nir Giladi, Robert J. Dawe, Anat Mirelman, Aron S. Buchman, Jeffrey M. Hausdorff

2020The Journals of Gerontology Series A11 citationsDOIOpen Access PDF

Abstract

BACKGROUND: Wearable sensors are increasingly employed to quantify diverse aspects of mobility. We developed novel tandem walking (TW) metrics, validated these measures using data from community-dwelling older adults, and evaluated their association with mobility disability and measures of gait and postural control. METHODS: Six hundred ninety-three community-dwelling older adults (age: 78.69 ± 7.12 years) wore a 3D accelerometer on their lower back while performing 3 tasks: TW, usual-walking, and quiet standing. Six new measures of TW were extracted from the sensor data along with the clinician's conventional assessment of TW missteps (ie, trip other loss of balance in which recovery occurred to prevent a fall) and duration. Principal component analysis transformed the 6 new TW measures into 2 summary TW composite factors. Logistic regression models evaluated whether these TW factors were independently associated with mobility disability. RESULTS: Both TW factors were moderately related to the TW conventional measures (r < 0.454, p < .001) and were mildly correlated with usual-walking (r < 0.195, p < .001) and standing, postural control (r < 0.119, p < .001). The TW frequency composite factor (p = .008), but not TW complexity composite factor (p = .246), was independently associated with mobility disability in a model controlling for age, sex, body mass index, race, conventional measures of TW, and other measures of gait and postural control. CONCLUSIONS: Sensor-derived TW metrics expand the characterization of gait and postural control and suggest that they reflect a relatively independent domain of mobility. Further work is needed to determine if these metrics improve risk stratification for other adverse outcomes (eg, falls and incident disability) in older adults.

Topics & Concepts

Wearable computerBalance (ability)Dynamic balanceWearable technologyTandemComputer scienceGaitPhysical medicine and rehabilitationHuman–computer interactionPsychologyMedicineEngineeringEmbedded systemMechanical engineeringAerospace engineeringBalance, Gait, and Falls PreventionProsthetics and Rehabilitation RoboticsContext-Aware Activity Recognition Systems
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