Browse

You are looking at 101 - 110 of 172 items for :

  • Journal for the Measurement of Physical Behaviour x
  • Sport and Exercise Science/Kinesiology x
  • Psychology and Behavior in Sport/Exercise x
  • Refine by Access: All Content x
Clear All
Restricted access

Volume 4 (2021): Issue S1 (Oct 2021)

Restricted access

Impact of Reduced Sampling Rate on Accelerometer-Based Physical Activity Monitoring and Machine Learning Activity Classification

Scott Small, Sara Khalid, Paula Dhiman, Shing Chan, Dan Jackson, Aiden Doherty, and Andrew Price

Purpose: Lowering the sampling rate of accelerometers in physical activity research can dramatically increase study monitoring periods through longer battery life; however, the effect of reduced sampling rate on activity metric validity is poorly documented. We therefore aimed to assess the effect of reduced sampling rate on measuring physical activity both overall and by specific behavior types. Methods: Healthy adults wore sets of two Axivity AX3 accelerometers on the dominant wrist and hip for 24 hr. At each location one accelerometer recorded at 25 Hz and the other at 100 Hz. Overall acceleration magnitude, time in moderate to vigorous activity, and behavioral activities were calculated and processed using both linear and nearest neighbor resampling. Correlation between acceleration magnitude and activity classifications at both sampling rates was calculated and linear regression was performed. Results: Of the 54 total participants, 45 contributed >20 hr of hip wear time and 51 contributed >20 hr of wrist wear time. Strong correlation was observed between 25- and 100-Hz sampling rates in overall activity measurement (r = .97–.99), yet consistently lower activity was observed in data collected at 25 Hz (3.1%–13.9%). Reduced sleep and light activity and increased sedentary time was classified in 25-Hz data by machine learning models. Discrepancies were greater when linear interpolation resampling was used in postprocessing. Conclusions: The 25- and 100-Hz accelerometer data are highly correlated with predictable differences, which can be accounted for in interstudy comparisons. Sampling rate and resampling methods should be consistently reported in physical activity studies, carefully considered in study design, and tailored to the outcome of interest.

Restricted access

Impact of ActiGraph Sampling Rate and Intermonitor Comparability on Measures of Physical Activity in Adults

Kimberly A. Clevenger, Jan Christian Brønd, Daniel Arvidsson, Alexander H.K. Montoye, Kelly A. Mackintosh, Melitta A. McNarry, and Karin A. Pfeiffer

Background: ActiGraph is a commonly used, research-grade accelerometer brand, but there is little information regarding intermonitor comparability of newer models. In addition, while sampling rate has been shown to influence accelerometer metrics, its influence on measures of free-living physical activity has not been directly studied. Purpose: To examine differences in physical activity metrics due to intermonitor variability and chosen sampling rate. Methods: Adults (n = 20) wore two hip-worn ActiGraph wGT3X-BT monitors for 1 week, with one accelerometer sampling at 30 Hz and the other at 100 Hz, which was downsampled to 30 Hz. Activity intensity was classified using vector magnitude, Euclidean Norm Minus One (ENMO), and mean amplitude deviation (MAD) cut points. Equivalence testing compared outcomes. Results: There was a lack of intermonitor equivalence for ENMO, time in sedentary/light- or moderate-intensity activity according to ENMO cut points, and time in moderate-intensity activity according to MAD cut points. Between sampling rates, differences existed for time in moderate-intensity activity according to vector magnitude, ENMO, and MAD cut points, and time in sedentary/light-intensity activity according to ENMO cut points. While mean differences were small (0.1–1.7 percentage points), this would equate to differences in moderate-to vigorous-intensity activity over a 10-hr wear day of 3.6 (MAD) to 10.8 (ENMO) min/day for intermonitor comparisons or 3.6 (vector magnitude) to 5.4 (ENMO) min/day for sampling rate. Conclusions: Epoch-level intermonitor differences were larger than differences due to sampling rate, but both may impact outcomes such as time spent in each activity intensity. ENMO was the least comparable metric between monitors or sampling rates.

Open access

The 7th International Conference on Ambulatory Monitoring of Physical Activity and Movement

Restricted access

Volume 4 (2021): Issue 3 (Sep 2021)

Restricted access

Correlates of the Adherence to a 24-hr Wrist-Worn Accelerometer Protocol in a Sample of High School Students

Marcus V.V. Lopes, Bruno G.G. da Costa, Luis E.A. Malheiros, Rafael M. Costa, Ana C.C. Souza, Inacio Crochemore-Silva, and Kelly S. Silva

This study (a) compared accelerometer wear time and compliance between distinct wrist-worn accelerometer data collection plans, (b) analyzed participants’ perception of using accelerometers, and (c) identified sociodemographic and behavioral correlates of accelerometer compliance. A sample of high school students (n = 143) wore accelerometers attached to the wrist by a disposable polyvinyl chloride (PVC) wristband or a reusable fabric wristband for 24 hr over 6 days. Those who wore the reusable fabric band, but not their peers, were instructed to remove the device during water-based activities. Participants answered a questionnaire about sociodemographic and behavioral characteristics and reported their experience wearing the accelerometer. We computed non-wear time and checked participants’ compliance with wear-time criteria (i.e., at least three valid weekdays and one valid weekend day) considering two valid day definitions separately (i.e., at least 16 and 23 hours of accelerometer data). Participants who wore a disposable band had greater compliance compared with those who wore a reusable band for both 16-hr (93% vs. 76%, respectively) and 23-hr valid day definitions (91% vs. 50%, respectively). High schoolers with the following characteristics were less likely to comply with wear time criteria if they (a) engaged in labor-intensive activities, (b) perceived that wearing the monitor hindered their daily activities, or (c) felt ashamed while wearing the accelerometer. In conclusion, the data collection plan composed of using disposable wristbands and not removing the monitor resulted in greater 24-hr accelerometer wear time and compliance. However, a negative experience in using the accelerometer may be a barrier to high schoolers’ adherence to rigorous protocols.

Restricted access

Association Between Accelerometer and Parental Reported Weekend and Weekday Sleeping Patterns and Adiposity Among Preschool-Aged Children

Bridget Coyle-Asbil, Hannah J. Coyle-Asbil, David W.L. Ma, Jess Haines, and Lori Ann Vallis

Sleep is vital for healthy development of young children; however, it is not understood how the quality and quantity vary between the weekends and weekdays (WE–WD). Research focused on older children has demonstrated that there is significant WE–WD variability and that this is associated with adiposity. It is unclear how this is experienced among preschoolers. This study explored: (a) the accuracy of WE–WD sleep as reported in parental logbooks compared with accelerometers; (b) the difference between WE and WD total sleep time, sleep efficiency, and timing, as assessed by accelerometers; and (c) the association between the variability of these metrics and adiposity. Eighty-seven preschoolers (M = 46; 4.48 ± 0.89 years) wore an accelerometer on their right hip for 7 days. Parents were given logbooks to track “lights out” times (sleep onset) and out of bed time (sleep offset). Compared with accelerometers, parental logbook reports indicated earlier sleep onset and later sleep offset times on both WEs and WDs. Accelerometer-derived total sleep time, sleep efficiency, and onset/offset were not significantly different on the WEs and WDs; however, a sex effect was observed, with males going to bed and waking up earlier than females. Correlation analyses revealed that variability of sleep onset times throughout the week was positively correlated with percentage of fat mass in children. Results suggest that variability of sleep onset may be associated with increased adiposity in preschool children. Additional research with larger and more socioeconomically and racially diverse samples is needed to confirm these findings.

Restricted access

Comparison of Fitbit One and ActivPAL3TM in Adults With Multiple Sclerosis in a Free-Living Environment

Golnoush Mehrabani, Douglas P. Gross, Saeideh Aminian, and Patricia J. Manns

Walking is the most common and preferred way for people with multiple sclerosis (MS) to be active. Consumer-grade wearable activity monitors may be used as a tool to assist people with MS to track their walking by counting the number of steps. The authors evaluated the validity of Fitbit One activity tracker in individuals with MS by comparing step counts measured over a 7-day period against ActivPAL3TM (AP). Twenty-five ambulatory adults with MS with an average age 51.7 (10.2) years and gait speed 0.98 (0.47) m/s, median Expanded Disability Status Scale 5.5 (2.5–6.5), and 15 years post-MS diagnosis wore Fitbit One (using both waist and ankle placement) and AP for 7 consecutive days. Validity of Fitbit One for measuring step counts against AP was assessed using intraclass correlation coefficients (ICCs), Bland–Altman plots, and t tests. Regardless of wearing location (waist or ankle), there was good agreement between steps recorded by Fitbit One and AP (ICC: .86 [.82, .90]). The ankle-worn Fitbit measured steps more accurately (ICC: .91 [.81, .95]) than the waist-worn Fitbit (ICC: .81 [.62, .85]) especially in individuals (n = 12) who walked slowly (gait speed = 0.74 m/s). Fitbit One as a user-friendly, inexpensive, consumer-grade activity tracker can accurately record steps in persons with MS in a free-living environment.

Open access

Calibration of the Online Youth Activity Profile Assessment for School-Based Applications

Gregory J. Welk, Pedro F. Saint-Maurice, Philip M. Dixon, Paul R. Hibbing, Yang Bai, Gabriella M. McLoughlin, and Michael Pereira da Silva

A balance between the feasibility and validity of measures is an important consideration for physical activity (PA) research—particularly in school-based research with youth. The present study extends previously tested calibration methods to develop and test new equations for an online version of the youth activity profile (YAP) tool, a self-report tool designed for school applications. Data were collected across different regions and seasons to develop more robust, generalizable equations. The study involved a total of 717 youth from 33 schools (374 elementary [ages 9–11 years], 224 middle [ages 11–14 years], and 119 high school [ages 14–18 years]) in two different states in the United States. Participants wore a Sensewear monitor for a full week and then completed the online YAP at school to report PA and sedentary behaviors in school and at home. Accelerometer data were processed using an R-based segmentation program to compute PA and sedentary behavior levels. Quantile regression models were used with half of the sample to develop item-specific YAP calibration equations, and these were cross validated with the remaining half of the sample. Computed values of mean absolute percentage error ranged from 15 to 25% with slightly lower error observed for the middle school sample. The new equations had improved precision compared with the previous versions when tested on the same sample. The online version of the YAP provides an efficient and effective way to capture school level estimates of PA and sedentary behaviors in youth.

Open access

Changes in Device-Measured Physical Activity Patterns in U.K. Adults Related to the First COVID-19 Lockdown

Andrew P. Kingsnorth, Mhairi Patience, Elena Moltchanova, Dale W. Esliger, Nicola J. Paine, and Matthew Hobbs

The response to COVID-19 resulted in behavioral restrictions to tackle the spread of infection. Initial data indicates that step counts were impacted by lockdown restrictions; however, there is little evidence regarding changes of light and moderate to vigorous physical activity (MVPA) behavioral intensities. In this study, participants were asked to provide longitudinal wearable data from Fitbit devices over a period of 30 weeks, from December 2019 to June 2020. Self-assessed key worker status was captured, along with wearable estimates of steps, light activity, and MVPA. Bayesian change point analyses of data from 97 individuals found that there was a sharp decrease of 1,473 steps (95% credible interval [CI] [−2,218, −709]) and light activity minutes (41.9; 95% CI [−54.3, −29.3]), but an increase in MVPA minutes (11.7; 95% CI [2.9, 19.4]) in the mean weekly totals for nonkey workers. For the key workers, the total number of steps (207; 95% CI [−788, 1,456]) and MVPA minutes increased (20.5; 95% CI [12.6, 28.3]) but light activity decreased by an average of 46.9 min (95% CI [−61.2, −31.8]). Interestingly, the change in steps was commensurate with that observed during Christmas (1,458; 95% CI [−2,286, −554]) for nonkey workers and behavioral changes occurred at different time points and rates depending on key worker status. Results indicate that there were clear behavioral modifications before and during the initial COVID-19 lockdown period, and future research should assess whether any behavioral modifications were sustained over time.