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

Abstract

Background Wearable sensors are increasingly employed to quantify diverse aspects of mobility. We developed novel tandem walk (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 693 community-dwelling older adults (age: 78.69±7.12 yrs) wore a 3D-accelerometer on their lower back while performing three 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 (i.e., trip other loss of balance in which recovery occurred to prevent a fall) and duration. Principal component analysis (PCA) transformed the 6 new TW measures into two 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<0.001) and were mildly correlated with usual-walking (r<0.195, p<0.001) and standing, postural control (r<0.119, p<0.001). The TW frequency composite factor (p=0.008), but not TW complexity composite factor (p=0.246), 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 tandem walk 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 (e.g., falls and incident disability) in older adults.

RGB-Depth Camera-Based Assessment of Motor Capacity: Normative Data for Six Standardized Motor Tasks

“…Ganz et al, on the other hand, provide rather synoptic parameters derived from a single wearable that describe postural corrections, overall movement, as well as regularity and complexity. They reported composite factors of these parameters to be associated with age, sex, and BMI in older adults [ 8 ]. However, time-to-complete was reported not to be associated with age, sex, or BMI [ 36 ], which is more in line with our results that yielded no robust model describing associations between spatiotemporal parameters and respective confounders.…”

“…Large normative datasets of gait parameters ranging from gait speed to arm swing asymmetry continue to be of high interest to the scientific community and are comparatively prevalent [ 3 , 4 , 5 , 6 , 7 ]. Few larger databases exist for other motor tasks, such as tandem gait and postural control [ 8 , 9 , 10 ]. However, most reported parameter values from healthy controls stem from small case-control or proof-of-concept studies and comprise around 30 healthy subjects or less [ 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 ].…”

Effectiveness Effectiveness of Wearable Electronic Device for Fall Risk Prevention in Community Elderly: A Literature Review

“…Sementara terdapat satu artikel yang menggunakan Balance Tracking System (BT TrackS) yang digunakan sebagai alat ukur dalam memantau kesimbangan dalam mencegah kejadian jatuh pada lansia di komunitas (Levy et al, 2018). Accelerometer banyak digunakan di punggung (Ganz et al, 2021;Qiu et al, 2018), pinggang (Rosenberg et al, 2021;Yu et al, 2021), pergelangan tangan (Chan et al, 2023;Urbanek et al, 2023) untuk menilai risiko jatuh pada lansia. Berbeda dengan sensor inertial yang ditempelkan pada tulang dada, mediolateral, anterior posterior, dan longitudinal axes untuk melakukan tes gerakan dan berjalan untuk melihat algoritma aktivitas sehari-hari lansia dalam mencegah jatuh (Hauth et al, 2021;Lockhart et al, 2021;Qiu et al, 2018).…”

Walking on a Balance Beam as a New Measure of Dynamic Balance to Predict Falls in Older Adults and Patients with Neurological Conditions

“…Because ~ 40-50% of falls occur while walking [13] and up to 33% of falls occur to the side probably due to age-impaired mediolateral balance [14], measuring dynamic balance while walking on a narrow, low-lying beam appears a reasonable alternative to 'functional tests' relying on walking speed [2,10,11,[15][16][17][18][19][20][21]. Beam walking could complement linear and circular tandem gait tests that still often end without an actual loss of balance due to censored distance or duration of those tests [22][23][24]. Beam walking could measure dynamic balance because the reduction in the base of support can strongly but transiently augment instability as the center of mass pivots over the stance leg.…”