Yuri Feito

Evaluation of activity monitors in controlled and free-living environments.

UNLABELLED Numerous studies have established the usefulness of pedometers and accelerometers as objective activity monitors. Under laboratory conditions, some of these devices have been shown to provide accurate and reliable measures of steps. However, limited data exist on the performance of these devices under free-living conditions. PURPOSE This study aimed 1) to compare the effects of speed and body mass index (BMI) on the step count accuracy of five different accelerometer-based activity monitors and a pedometer during treadmill walking, 2) to compare the performance of these devices in a free-living environment, and 3) to compare the step counts of three generations of a single device (ActiGraph) against a criterion method. METHODS Fifty-six individuals wore six activity monitors while performing treadmill walking (40, 54, 67, 80, and 94 m·min⁻¹) and during 1 d of free-living activity. The criterion measure of steps during treadmill walking was investigator-determined steps, whereas the criterion measure of steps during the free-living condition was the StepWatch. RESULTS BMI had no effect on step count accuracy during treadmill walking. The StepWatch, activPAL™, and the AG7164 were the most accurate across all speeds, whereas the remaining devices were only accurate at 67 m·min⁻¹ and faster. In the free-living environment, the AG7164 recorded 99.5% ± 27% (mean ± SD) of StepWatch-determined steps. CONCLUSIONS We demonstrated that BMI does not affect the step output of commonly used activity monitors during walking. In addition, 67 m·min⁻¹ seems to be the minimum speed required for accurate step counting, at least for most waist-mounted activity monitors. Finally, the StepWatch, AG7164, and activPAL™ were the most accurate devices on the TM, but only the AG7164 yielded comparable step counts to the StepWatch in the free-living environment.

Effects of body mass index and step rate on pedometer error in a free-living environment.

UNLABELLED Pedometers could provide great insights into walking habits if they are found to be accurate for people of all weight categories. PURPOSE the purposes of this study were to determine whether the New Lifestyles NL-2000 (NL) and the Digi-Walker SW-200 (DW) yield similar daily step counts as compared with the StepWatch 3 (SW) in a free-living environment and to determine whether pedometer error is influenced by body mass index (BMI) and speed of walking. The SW served as the criterion because of its accuracy across a range of speeds and BMI categories. Slow walking was defined as ≤80 steps per minute. METHODS fifty-six adults (mean ± SD: age = 32.7 ± 14.5 yr) wore the devices for 7 d. There were 20 normal weight, 18 overweight, and 18 obese participants. A two-way repeated-measures ANOVA was performed to determine whether BMI and device were related to number of steps counted per day. Stepwise linear regressions were performed to determine what variables contributed to NL and DW error. RESULTS both the NL and the DW recorded fewer steps than the SW (P < 0.001). In the normal weight and overweight groups, error was similar for the DW and NL. In the obese group, the DW underestimated steps more than the NL (P < 0.01). DW error was positively related to BMI and percentage of slow steps, whereas NL error was linearly related to percentage of slow steps. A surprising finding was that many healthy, community-dwelling adults accumulated a large percentage of steps through slow walking. CONCLUSIONS the NL is more accurate than the DW for obese individuals, and neither pedometer is accurate for people who walk slowly. Researchers and practitioners must weigh the strengths and limitations of step counters before making an informed decision about which device to use.

Effects of body mass index and tilt angle on output of two wearable activity monitors.

UNLABELLED Accelerometer-based activity monitors have been used to provide objective measures of physical activity and energy expenditure (EE) in free-living individuals. However, output from these devices has not been compared among normal, overweight, and obese individuals. PURPOSE The purpose of this study was to examine the effects of body mass index (BMI) and device tilt angle on activity counts recorded by wearable monitors in a controlled laboratory setting. A secondary aim was to examine the effects of these variables on estimated EE. METHODS Seventy-one healthy adults wore an Actical and an ActiGraph GT1M on the right and left hip, respectively, while walking at 40, 67, and 94 m·min. EE was measured by indirect calorimetry and compared with estimated values using published equations. Three-way repeated-measures ANOVA were used to examine differences in outcome variables (activity counts and EE) between speeds, BMI, and tilt angle for each device. RESULTS No significant differences in activity counts were observed among BMI categories for either the Actical or ActiGraph (P>0.05). For the Actical, however, among those with an absolute tilt angle <10°, the obese group recorded higher activity counts than the normal weight group (P=0.01). Using the Heil two-regression model, the Actical overestimated EE by up to 35% at the intermediate speed and up to 12% at the fastest speed (P<0.001). The Freedson METs regression equation yielded closer estimates of EE than the Freedson kilocalorie regression equation. CONCLUSIONS Our findings indicate that the Actical has limitations when comparing individuals with varying BMI and tilt angles in a controlled laboratory environment. The ActiGraph seems to be a more suitable device for making these comparisons.