The ActiGraph counts processing and the assessment of vigorous activity

Abstract

Summary The purpose of this study was to investigate the effect of different band‐pass filters on the measurement bias with ActiGraph counts during high speed running and for estimating free‐living vigorous physical activity (VPA). Two alternative band‐pass filters were designed, extending the original frequency range from 0·29 to 1·66 Hz (AG) to 0·29–4 Hz (AC4) and 0·29–10 Hz (AC10). Sixty‐two subjects in three age groups participated in a structured locomotion protocol consisting of multiple walking and running speeds. The time spent in free‐living VPA using the three different band‐pass filters were evaluated in 1121 children. Band‐pass filter specific intensity cut‐points from both linear regression and ROC analysis was identified from a calibration experiment using indirect calorimetry. The ActiGraph GT3X+ device recording raw acceleration at 30 Hz was used in all experiments. The linear association between counts and running speed was negative for AG but positive for AC4 and AC10 across all age groups. The time spent in free‐living VPA was similar for all band‐pass filters. Considering higher frequency information in the generation of ActiGraph counts with a hip/waist worn device reduces the measurement bias with running above 10 km·h−1. However, additional developments are required to accurately capture all VPA, including intermittent activities.

Reexamination of Accelerometer Calibration with Energy Expenditure as Criterion: VO2net Instead of MET for Age-Equivalent Physical Activity Intensity

“…The novelty of this study is to propose a criterion method (VO 2net , mL⋅kg −1 ⋅min −1 ) to calibrate accelerometer PA intensity measures equivalent by age based on data collected at the hip and at the thigh. It was applied to our improved processing of acceleration data [16,17,18,19] to generate new cut-points for LPA, MPA, VPA and VVPA in children, adolescents and adults. These outcomes were supported by the finding that the relationship between Speed eq and VO 2net (VO 2gross − VO 2stand ) was similar in children, adolescents and adults, indicating that VO 2net is a measure of similar effort in the three age-groups, in contrast to the more commonly used MET in accelerometer calibration which was not a measure of PA intensity equivalent by age.…”

“…Consequently, higher demands were required from the children to reach MPA or VPA than in the adults. Further, the acceleration data was processed to the original ActiGraph counts with its limitations to assess PA intensity [16,17,18,19]. In addition, the aggregation of the acceleration data was performed into 60 s epochs, which would be insensitive to the movement pattern of children [1].…”

“…These different outcomes would have contributed to different calibration equations and cut-points for PA intensity. While the comparability of accelerometer measures of PA intensity by age has been investigated for the hip placement, less is known about the thigh placement [17,18,19]. The thigh placement offers additional possibilities for assessment of sedentary time (sitting, standing), biking (i.e., cadence) as well as non-wear time.…”

Resemblance in accelerometer-assessed physical activity in families with children: the Lolland-Falster Health Study

“…PA intensity was determined by generating ActiGraph counts using 10 s-epochs from the raw acceleration measured at the back [20]. The PA intensity estimated using counts with intermittent activities is known to be underestimated [21,22] and in order to account for this measurement error, we identified high intensity bouts using vector magnitude acceleration separated with no movements of less than 10 s and used interpolation to account for the elevated post oxygen consumption between bouts [23]. The known measurement error with intermittent activities [21,22] was reduced by interpolating the non-moving activity between closely related (< 10 s distance) bouts of high intensity (vigorous) activity bouts (Brønd JC, Andersen LB, Grøntved A, Pedersen HA, Arvidsson D: Accurate assessment of intermittent activity with accelerometry, submitted).…”

“…The PA intensity estimated using counts with intermittent activities is known to be underestimated [21,22] and in order to account for this measurement error, we identified high intensity bouts using vector magnitude acceleration separated with no movements of less than 10 s and used interpolation to account for the elevated post oxygen consumption between bouts [23]. The known measurement error with intermittent activities [21,22] was reduced by interpolating the non-moving activity between closely related (< 10 s distance) bouts of high intensity (vigorous) activity bouts (Brønd JC, Andersen LB, Grøntved A, Pedersen HA, Arvidsson D: Accurate assessment of intermittent activity with accelerometry, submitted). This method is similar to the two-regression method originally proposed by Crouter et al [24], however avoiding the use of multiple regressions equations and improving the resolution by correcting the measurement error in the second-by-second data [24][25][26].…”