We assessed the validity of the Computer Science and Applications, Inc. (CSA) accelerometer as a measure of energy expenditure during wheelchair pushing. Participants completed three timed pushes over an indoor course at three different speeds while wearing a CSA accelerometer on both wrists. Pushing speeds were assigned in a random order and separated by a 5–10 min rest. Heart rate and energy expenditure were measured using an Aerosport TEEM 100. Results indicated pushing speed, heart rate, and oxygen consumption increased significantly over the three conditions (p < .01). Significant associations (p < .01) were noted between CSA readings from both wrists and energy expenditure over the three pushing speeds (left wrist, r = .66, right wrist r = .52). These results suggest that the CSA accelerometer worn at the wrist may provide a useful measure of physical activity in persons who use wheelchairs as their primary mode of locomotion.
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Assessing Physical Activity during Wheelchair Pushing: Validity of a Portable Accelerometer
Richard A. Washburn and Anne G. Copay
Measuring Physical Activity in Children with Cystic Fibrosis: Comparison of Four Methods
David M. Orenstein, Patricia A. Nixon, Richard A. Washburn, and Sheryl F. Kelsey
Since physical fitness and activity may affect prognosis in patients with cystic fibrosis (CF), it is important to be able to measure physical activity in these individuals. Fifty-two such patients younger than 20 years were studied with two electronic activity monitors (LSI and Caltrac monitors) and two activity recall questionnaires (Paffenbarger’s Harvard Alumni Survey and Kriska’s Physical Activity Survey). Spearman rank correlation was used to examine relationships among activity levels as assessed by these tools. There was significant correlation between 3-day activity levels as assessed by the two electronic monitors at each of three measurement periods, and between the activity questionnaires: Kriska’s questionnaire correlated with Paffenbarger’s survey. The monitors correlated less closely with the questionnaires. In this study, two standard physical activity questionnaires correlate with each other and two electronic monitors also correlate with each other in their estimates of physical activity in patients with CF. Since the monitor-questionnaire correlation was substantially less than the monitor-monitor correlation or the questionnaire-questionnaire correlation, it appears that these types of instruments may capture different aspects of activity in children with CF.
The Relationship between Peak Oxygen Uptake and Physical Activity in 6- to 8-Year-Old Children
Juliane R. Fenster, Patty S. Freedson, Richard A. Washburn, and R. Curtis Ellison
The relationship between physical activity measured using the LSI (Large Scale Integrated Activity Monitor), and questionnaire, with physical work capacity 170 (PWC 170) and aerobic capacity (peak V̇O2) was evaluated in 6- to 8-year-old children (n = 18). The mean (± SD) peak V̇O2 was 44.1 ± 5.6 ml • kg−1 • min−1. Peak V̇O2 was not significantly different for children (n = 8) who had completed two treadmill trials (45.4 vs. 43.5 ml • kg−1 • min−1; R = 0.67, p<0.05). The log LSI expressed as counts per hour (M ± SD = 2.1 ±.22 cts/hr) was the only activity method significantly related to peak V̇O2 (r = 0.59, p<0.05). The correlation between peak V̇O2 with the questionnaire was positive but nonsignificant (r = 0.20). PWC 170 was not related to peak V̇O2 (r = 0.21) or the activity variables (r = 0.12 questionnaire; r = 0.18 log LSI). When the group was divided into high and low peak V̇O2 groups (high: M = 48.8 ml • kg−1 • min−1; low: M = 39.5 ml • kg−1 • min−1), the log LSI was able to distinguish significant differences in activity levels (high: 2.23 ±. 19 cts/hr; low: 1.99±.19 cts/hr). This study suggests that activity measured with the LSI and aerobic capacity are related in this sample of 6- to 8-year-old children.
Energy Expenditure and Intensity of Classroom Physical Activity in Elementary School Children
Jeffery J. Honas, Erik A. Willis, Stephen D. Herrmann, Jerry L. Greene, Richard A. Washburn, and Joseph E. Donnelly
Background:
There is limited data regarding objectively measured energy cost and intensity of classroom instruction. Therefore, the purpose of current study was to objectively measure energy cost and subsequently calculate MET values using a portable indirect calorimeter (IC) for both normal classroom instruction (NCI) and active classroom instruction (ACI).
Methods:
We assessed energy expenditure (EE) and intensity levels (METs) in elementary school children (17 boys and 15 girls) using an IC (COSMED K4b2). Independent t-tests were used to evaluate potential sex and grade level differences for age, BMI, VO2, EE, and METs.
Results:
The average EE for NCI and ACI were 1.8 ± 0.4 and 3.9 ± 1.0, respectively. The average intensity level for NCI and ACI were 1.9 ± 0.4 and 4.2 ± 0.9 METs, respectively.
Conclusions:
PA delivered through ACI can elicit EE at a moderate intensity level. These results provide evidence for ACI as a convenient/feasible avenue for increasing PA in youth without decreasing instruction time.
Energy Expenditure and Intensity of Group-Based High-Intensity Functional Training: A Brief Report
Erik A. Willis, Amanda N. Szabo-Reed, Lauren T. Ptomey, Jeffery J. Honas, Felicia L. Steger, Richard A. Washburn, and Joseph E. Donnelly
Background: High-intensity functional training (HIFT) may offer an attractive, time-efficient alternative to traditional aerobic exercise. However, limited information is available in the literature regarding HIFT meeting exercise guidelines for energy expenditure (improve health outcomes: ≥1000 kcal/wk; weight management: ≥2000 kcal/wk) and level of intensity (moderate: 3–6 metabolic equivalents [METs], vigorous: ≥6 METs) elicited by this approach. Thus, the primary aim was to objectively measure energy expenditure and intensity of HIFT sessions. Methods: Energy expenditure was assessed in 20 adults (18–50 y, 50% females). The HIFT session format included the following segments: warm-up (∼5 min), exercise (∼35 min), and cooldown (∼5 min). Participant oxygen consumption (COSMED, L/min and mL/kg/min), heart rate (Polar RS400), and physical activity (ActiGraph GT3X+) were collected in 15-second intervals. Average kcal per minute, METs, total kcal per session, and percent maximum heart rate (HRmax) were calculated. Results: METs ranged from 5.5 to 11.6 for the complete session (including warm-up and cooldown). Participant’s HRmax was ∼80% (range: 69%–100%). Average energy expenditure was ∼485 kcal per session (∼1400 kcal/wk). The vigorous-intensity exercise portion (∼35 min) contributed to 80% of total energy expenditure. Conclusions: HIFT has the potential to meet the recommendations for exercise to improve health outcomes.
The System for Observing Fitness Instruction Time (SOFIT) as a Measure of Energy Expenditure during Classroom-Based Physical Activity
Jeffery J. Honas, Richard A. Washburn, Bryan K. Smith, Jerry L. Greene, Galen Cook-Wiens, and Joseph E. Donnelly
The aim of this investigation was to develop an equation to estimate physical activity energy expenditure (PAEE) during a 10-min physically active academic lesson using The System for Observing Fitness Instruction Time (SOFIT) and demographic information. PAEE (portable indirect calorimeter) and physical activity (SOFIT) were simultaneously assessed in 38, 2nd through 5th grade children. PAEE and SOFIT were 3.04 ± 1.1 (kcal/min) and 3.8 ± 0.4 (score), respectively. PAEE was predicted from SOFIT score and body weight [PAEE (kcal/min) = (1.384*SOFIT + 0.084*weight (kg)—5.126), R = .81, SEE = 1.23 kcal/min]. PAEE measured by indirect calorimeter and predicted from SOFIT and body weight were 3.04 ± 1.1 (kcal/min) and 3.04 ± 0.9 kcal/min) respectively. SOFIT and body weight may provide a useful measure of PAEE associated with classroom based physical activity.
agcounts: An R Package to Calculate ActiGraph Activity Counts From Portable Accelerometers
Brian C. Helsel, Paul R. Hibbing, Robert N. Montgomery, Eric D. Vidoni, Lauren T. Ptomey, Jonathan Clutton, and Richard A. Washburn
Portable accelerometers are used to capture physical activity in free-living individuals with the ActiGraph being one of the most widely used device brands in physical activity and health research. Recently, in February 2022, ActiGraph published their activity count algorithm and released a Python package for generating activity counts from raw acceleration data for five generations of ActiGraph devices. The nonproprietary derivation of the ActiGraph count improved the transparency and interpretation of accelerometer device-measured physical activity, but the Python release of the count algorithm does not integrate with packages developed by the physical activity research community using the R Statistical Programming Language. In this technical note, we describe our efforts to create an R-based translation of ActiGraph’s Python package with additional extensions to make data processing easier and faster for end users. We call the resulting R package agcounts and provide an inside look at its key functionalities and extensions while discussing its prospective impacts on collaborative open-source software development in physical behavior research. We recommend that device manufacturers follow ActiGraph’s lead by providing open-source access to their data processing algorithms and encourage physical activity researchers to contribute to the further development and refinement of agcounts and other open-source software.
The Feasibility of Remotely Delivered Exercise Session in Adults With Alzheimer’s Disease and Their Caregivers
Lauren T. Ptomey, Eric D. Vidoni, Esteban Montenegro-Montenegro, Michael A. Thompson, Joseph R. Sherman, Anna M. Gorczyca, Jerry L. Greene, Richard A. Washburn, and Joseph E. Donnelly
Adults with Alzheimer’s disease (AD) and their caregivers represent a segment of the population with low levels of moderate-intensity physical activity (MPA) and limited options for increasing MPA. The purpose of this study was to evaluate the feasibility of a group video conference approach for increasing MPA in adults with AD and their caregivers. Adults with AD and their caregivers attended 30-min group exercise sessions three times per week for 12 weeks. Exercise sessions and support sessions were delivered in their homes on a tablet computer over video conferencing software. Nine adults with AD/caregiver dyads enrolled, and seven completed the 12-week intervention. Adults with AD attended 77.3% of the group exercise sessions, and caregivers attended 79.2% of group exercise sessions. Weekly MPA increased in both adults with AD (49%) and caregivers (30%). Exercise delivered by group video conferencing is a feasible and potentially effective approach for increasing MPA in adults with AD and their caregivers.