Accuracy and precision of the StepWatch in stride counting and oxygen consumption

Accuracy and precision of the StepWatch in stride counting and oxygen consumption
K BJORNSON PHD PT 1, D YUNG MD 2, R BURR MSEE PHD 3, K JACQUES RRT NPS 2, D CHRISTAKIS MD 4
1 Developmental Medicine, Seattle Children’s Research Institute, University of Washington, Seattle, WA;
2 Pediatric Cardiology, Seattle Children’s University of Washington, Seattle, WA;
3 School of Nursing, University of Washington, Seattle, WA;
4 Pediatric, Seattle Children’s Research Institute, University of Washington, Seattle, WA, USA

Background/Objectives: Studies testing methods to promote physical activity require accurate and precise measurements of both physical activity and energy expenditure in children. StepWatch (SW) accelerometer data has been found to accurately count strides across speeds and predict oxygen costs of walking in lean and obese adults. This project aims to test the accuracy and precision of the SW across walking speeds against the gold standard of manual stride counting and to pilot the prediction of oxygen consumption modeled from SW counts in youth developing typically (YDT).
Design: Instrument development and validation with a clinical case series.
Participants and Setting: A volunteer sample of ten YDT (5 boys, 5 girls), average age of 14.1 (SD 2.2) years, average leg length 86.2 (SD 7.5) cm, weight 50.2 (SD 11.2) kg and BMI 18.3 (SD 2.2) participated with recruitment through (children of) employees of a tertiary care children’s hospital.
Materials/Methods; Two SW monitors were calibrated to individual walking patterns using SW software and leg length. A self-selected walking (100 + stride) sample with the SW was compared to manual count with accuracy of 99% (SD 0.47). Participants underwent treadmill cardiopulmonary exercise testing (CPET) wearing two SW monitors (outside right, inside left ankles) at 1, 2, 3 and 4 mph for 3 minutes. Absolute disagreement, with a ratio and interclass coefficients (ICC) to manual counts were employed with hierarchical linear regression to develop a prediction equation.
Results: Average sign-corrected disagreement for strides counted between the two SW monitors was 0.4 (0.51), 0.2 (0.42), 0.1 (0.32) and 0.1 (0.32) for 1, 2, 3 and 4 mph respectively. SW stride counts to manual counts (accuracy ratio) averaged 100.03 (0.10) with ICC=0.995 (precision) cross the four walking speeds. The derived prediction equation for oxygen consumption was: VO2= -1.2 * gender + -0.58* age (years) + 0.31 * SW strides + 8.35 with r2 =0.84.
Conclusions/Significance: The SW data demonstrates excellent accuracy and precision for treadmill walking across speeds in YDT. With SW data corrected for gender and age, acceptable prediction of walking oxygen consumption in youth 10-16 years of age appears possible within the context of day to day life versus the current lab based measures. Future work will explore prediction of oxygen consumption with the SW during self-selected walking speeds, with varying terrain and community based activity. Such information will allow testing of interventions to improve walking efficiency, physical activity and/or energy expenditure in children and youth.

 
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