Moving Beyond the Characterization of Activity Intensity Bouts as Square Waves Signals

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Myles W. O’Brien School of Physiotherapy & Division of Geriatric Medicine, Dalhousie University, Halifax, NS, Canada
Geriatric Medicine Research, Dalhousie University & Nova Scotia Health, Halifax, NS, Canada

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Jennifer L. Petterson School of Physiotherapy & Division of Geriatric Medicine, Halifax, NS, Canada

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Liam P. Pellerine School of Physiotherapy & Division of Geriatric Medicine, Halifax, NS, Canada

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Madeline E. Shivgulam School of Physiotherapy & Division of Geriatric Medicine, Halifax, NS, Canada

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Derek S. Kimmerly School of Physiotherapy & Division of Geriatric Medicine, Halifax, NS, Canada

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Ryan J. Frayne School of Physiotherapy & Division of Geriatric Medicine, Halifax, NS, Canada

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Pasan Hettiarachchi Department of Medical Sciences, Occupational and Environmental Medicine, Uppsala University, Uppsala, Sweden

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Peter J. Johansson Department of Medical Sciences, Occupational and Environmental Medicine, Uppsala University, Uppsala, Sweden
Occupational and Environmental Medicine, Uppsala University Hospital, Uppsala, Sweden

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Wearable activity monitors provide objective estimates of time in different physical activity intensities. Each continuous stepping period is described by its length and a corresponding single intensity (in metabolic equivalents of task [METs]), creating square wave–shaped signals. We argue that physiological responses do not resemble square waves, with the purpose of this technical report to challenge this idea and use experimental data as a proof of concept and direct potential solutions to better characterize activity intensity. Healthy adults (n = 43, 19♀; 23 ± 5 years) completed 6-min treadmill stages (five walking and five jogging/running) where oxygen consumption (3.5 ml O2·kg−1·min−1 = 1 MET) was recorded throughout and following the cessation of stepping. The time to steady state was ∼1–1.5 min, and time back to baseline following exercise was ∼1–2 min, with faster stepping stages generally exhibiting longer durations. Instead of square waves, the duration intensity signal reflected a trapezoid shape for each stage. The METs per minute during the rise to steady state (upstroke slopes; average: 1.7–6.3 METs/min for slow walking to running) may be used to better characterize activity intensity for shorter activity bouts where steady state is not achieved (within ∼90 s). While treating each activity bout as a single intensity is a much simpler analytical procedure, characterizing each bout in a continuous manner may better reflect the true physiological responses to movement. The information provided herein may be used to improve the characterization of activity intensity, definition of bout breaks, and act as a starting point for researchers and software developers interested in using wearables to measure activity intensity.

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