Supplementary Material for: Validation of a Wearable Sensor for Measuring Running Biomechanics
datasetposted on 02.08.2018 by Koldenhoven R.M., Hertel J.
Datasets usually provide raw data for analysis. This raw data often comes in spreadsheet form, but can be any collection of data, on which analysis can be performed.
Background: Running biomechanics have traditionally been analyzed in laboratory settings, but this may not reflect natural running gait. Wearable sensors may offer an alternative. Methods: A concurrent validation study to determine agreement between the RunScribeTM wearable sensor (triaxial accelerometer and gyroscope) and the 3D motion capture system was conducted. Twelve injury-free participants (6 males, 6 females; age = 23.1 ± 5.5 years, weekly mileage = 16.1 ± 9.3) ran 1.5 miles on a treadmill. Ten consecutive strides from each limb were collected, and the mean values were analyzed. Pronation excursion, maximum pronation velocity, contact time, and cycle time were compared between measurement platforms using intraclass correlation coefficients (ICC) and Bland-Altman analyses. Results: Excellent ICC estimates were found for maximum pronation velocity, contact time, and cycle time. Pronation excursion demonstrated fair ICC estimates. The mean differences between platforms were small with limits of agreement clustered around zero, except for contact time measures which were consistently higher with the RunScribe compared to the camera-based system. Conclusion: Our study revealed that the RunScribe wearable device showed good to excellent concurrent validity for maximum pronation velocity, contact time, and cycle time; however, direct comparisons or results between the two platforms should not be used.