Abstract
Dryft: A Python and MATLAB package to correct drifting ground reaction force signals during treadmill running
Highlights
Ground reaction forces (GRFs) are exerted by the body on the ground during running, measured by treadmills instrumented with force transducers, and are used to calculate a variety of clinical and performance-related biomechanical variables (Kram, Griffin, Donelan, & Chang, 1998)
I introduce dryft, an open source Python and MATLAB package that takes a simple approach to identifying and correcting linear or non-linear drift in GRF signals produced during treadmill running
The body exerts no force on the ground during the aerial phase of running and dryft assumes that any ground reaction force measured during an aerial phase is due to noise or drift in the signal. dryft implements a user-defined force threshold to approximate the start and end of each stance phase and identify aerial phases in a filtered vertical GRF signal (Figure 1)
Summary
Ground reaction forces (GRFs) are exerted by the body on the ground during running, measured by treadmills instrumented with force transducers, and are used to calculate a variety of clinical and performance-related biomechanical variables (Kram, Griffin, Donelan, & Chang, 1998). Signal drift can cause more (or less) of the vertical GRF signal to fall below the threshold, affecting one’s ability to identify stance phase (Riley et al, 2008) or calculate time-dependent GRF metrics. Zeroing force transducers may not be feasible for protocols requiring extended periods of continuous running on an instrumented treadmill. Dryft: A Python and MATLAB package to correct drifting ground reaction force signals during treadmill running. I introduce dryft, an open source Python and MATLAB package that takes a simple approach to identifying and correcting linear or non-linear drift in GRF signals produced during treadmill running
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