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Sandra C. Webber and Michelle M. Porter

This exploratory study examined the feasibility of using Garmin global positioning system (GPS) watches and ActiGraph accelerometers to monitor walking and other aspects of community mobility in older adults. After accuracy at slow walking speeds was initially determined, 20 older adults (74.4 ± 4.2 yr) wore the devices for 1 day. Steps, distances, and speeds (on foot and in vehicle) were determined. GPS data acquisition varied from 43 min to over 12 hr, with 55% of participants having more than 8 hr between initial and final data-collection points. When GPS data were acquired without interruptions, detailed mobility information was obtained regarding the timing, distances covered, and speeds reached during trips away from home. Although GPS and accelerometry technology offer promise for monitoring community mobility patterns, new GPS solutions are required that allow for data collection over an extended period of time between indoor and outdoor environments.

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Sandra C. Webber and Philip D. St. John

Activity monitors may not accurately detect steps in hospitalized older adults who walk slowly. We compared ActiGraph GT3X+ step counts (hip and ankle locations, default and low frequency extension [LFE] analyses) to the StepWatch monitor (ankle) during a hallway walk in 38 geriatric rehabilitation patients (83.2 ± 7.1 years of age, 0.4 ± 0.2 m/s gait speed). Absolute percent error values were low (<3%) and did not differ for the StepWatch and the GT3X+ (ankle, LFE); however, error values were high (19–97%) when the GT3X+ was worn at the hip and/ or analyzed with the default filter. Although these finding suggest the GT3X+ (ankle, LFE) functions as well as the StepWatch in detecting steps during walking in older adults with slow gait speeds, further research is needed to determine whether the GT3X+ is also able to disregard other body movements (e.g., fidgeting) that occur when full day monitoring is utilized.

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Sandra C. Webber, Sheila M. Magill, Jenessa L. Schafer and Kaylie C.S. Wilson

The purpose was to compare step count accuracy of an accelerometer (ActiGraph GT3X+), a mechanical pedometer (Yamax SW200), and a piezoelectric pedometer (SC-StepMX). Older adults (n = 13 with walking aids, n = 22 without; M = 81.5 years old, SD = 5.0) walked 100 m wearing the devices. Device-detected steps were compared with manually counted steps. We found no significant differences among monitors for those who walked without aids (p = .063). However, individuals who used walking aids exhibited slower gait speeds (M = 0.83 m/s, SD = 0.2) than non–walking aid users (M = 1.21 m/s, SD = 0.2, p < .001), and for them the SC-StepMX demonstrated a significantly lower percentage of error (Mdn = 1.0, interquartile range [IQR] = 0.5−2.0) than the other devices (Yamax SW200, Mdn = 68.9, IQR = 35.9−89.3; left GT3X+, Mdn = 52.0, IQR = 37.1−58.9; right GT3X+, Mdn = 51.0, IQR = 32.3−66.5; p < .05). These results support using a piezoelectric pedometer for measuring steps in older adults who use walking aids and who walk slowly.

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Sheila M. Korpan, Jenessa L. Schafer, Kaylie C.S. Wilson and Sandra C. Webber

Accelerometer step count accuracy may be affected by gait speed, device positioning, and analysis algorithm selection. We assessed ActiGraph GT3X+ step count accuracy related to device placement and analysis algorithm in older adults with walking aids (n = 13) and without walking aids (n = 22). Participants (81.5 ± 5.0 years of age) completed a timed 100-m walk wearing five GT3X+ monitors (hips, ankles, lumbar spine). Individuals with walking aids had slower gait speeds (0.8 ± 0.20 m/s versus 1.2 ± 0.20 m/s without walking aids, p < .001). Intraclass correlation coefficient values for observed versus monitored steps were highest when ankle placement and the low frequency extension (LFE) algorithm were used (left ankle ICC = .989, right ankle ICC = .998). Using the GT3X+ ankle placement and analyzing data with the LFE algorithm resulted in the most accurate step counts in older adults.