The prediction of speed and incline in outdoor running in humans using accelerometry

Purpose: To explore whether triaxial accelerometric measurements can be uti lized to accurately assess speed and incline of running in free-living cond itions. Methods: Body accelerations during running were recorded at the low er back and at the heel by a portable data logger in 20 human subjects, 10 men, and 10 women. After parameterizing body accelerations, two neural netw orks were designed to recognize each running pattern and calculate speed an d incline. Each subject ran 18 times on outdoor roads at various speeds and inclines; 12 runs were used to calibrate the neural networks whereas the 6 other runs were used to validate the model. Results: A small difference be tween the estimated and the actual values was observed: the square root of the mean square error (RMSE) was 0.12 m . s(-1) for speed and 0.014 radiant (rad) (or 1.4% in absolute value) for incline. Multiple regression analysi s allowed accurate prediction of speed (RMSE = 0.14 m . s(-1)) but not of i ncline (RMSE = 0.026 rad or 2.6% slope). Conclusion: Triaxial accelerometri c measurements allows an accurate estimation of speed of running and inclin e of terrain (the latter with more uncertainty). This will permit the valid ation of the energetic results generated on the treadmill as applied to mor e physiological unconstrained running conditions.