Sprint mechanics evaluation using inertial sensor‐based technology: A laboratory validation study

Abstract

Advances in micro-electromechanical systems have turned magnetic inertial measurement units (MIMUs) into a suitable tool for vertical jumping biomechanical evaluation. Thus, this study aimed to determine whether appropriate reliability and agreement reports could also be obtained when analyzing 20-m sprint mechanics. Four bouts of 20-m sprints were evaluated to determine whether the data provided by a MIMU placed at the lumbar spine could reliably assess sprint mechanics and to examine the validity of the MIMU sensor compared to force plate recordings. Maximal power (P ), force (F ), and velocity (V ), as well as other mechanical determinants of sprint performance associated with the force-velocity, power-velocity, and ratio of forces-velocity, such as applied horizontal force loss (S ) and decrease in ratio of forces (D ), were calculated and compared between instrumentations. Extremely large-to-very large correlation levels between MIMU sensor-based sprint mechanics variables and force plate recordings were obtained (mean±SD, force plate vs MIMU; V 8.61±0.85 vs 8.42±0.69; F , 383±110 vs 391±103; P , 873±246 vs 799±241; S -44.6±12.7 vs -46.2±10.7), ranging from 0.88 to 0.94, except for D which showed weak-to-moderate correlation level (r=.45; -6.32±1.08 vs -5.76±0.68). Step-averaged force values measured with both systems were highly correlated (r=.88), with a regression slope close to the identity (1.01). Bland and Altman graphical representation showed a no random distribution of measured force values. Finally, very large-to-extremely large retest correlation coefficients were found for the intertrial reliability of MIMU measurements of sprint performance variables (r value ranging from .72 to .96). Therefore, MIMUs showed appropriate validity and reliability values for 20-m sprint performance variables.

Hurdle Clearance Detection and Spatiotemporal Analysis in 400 Meters Hurdles Races Using Shoe-Mounted Magnetic and Inertial Sensors

“…These studies differ in terms of sensor configuration, sensor location, and type of parameter measured [1]. Several groups have used inertial sensors in sprint running to characterize temporal parameters [2][3][4], body-segment orientation [5,6], ground reaction forces [7,8], and speed [9][10][11]. Surprisingly, only a few studies used MIMU to quantify spatiotemporal parameters in hurdle races.…”

In-Field Validation of an Inertial Sensor-Based System for Movement Analysis and Classification in Ski Mountaineering

“…In running, many studies show IMUs can be an alternative solution to cumbersome video analysis [ 9 ] for obtaining movement data in the field, and even obtain acceptable results compared to force platforms when estimating force and power. Setuain et al [ 10 ] estimate running power with IMUs in the field. Xu et al [ 11 ] calculates movement efficiency from IMUs in cycling so coaches can monitor and analyse performance, showing satisfactory results from real-time validation.…”

A Sensor Fusion Approach to the Estimation of Instantaneous Velocity Using Single Wearable Sensor During Sprint

“…Thus, the velocity estimation algorithm based on GNSS and IMU fusion is robust in terms of accuracy and precision, despite the inaccuracies in the GNSS velocity. None of the previous works on estimation of sprint mechanics ( Samozino et al, 2016 ; Stanton et al, 2016 ; Gurchiek et al, 2018 ; Setuain et al, 2018 ) conducted a validation of the instantaneous velocity or the overall profile with respect to a speed radar. Stanton et al (2016) validated the mean velocity over an entire sprint, while ( Gurchiek et al, 2018 ) validated the mean velocity over 10 m intervals.…”

“…This is a result of the minor underestimation of velocity caused by the residual drift in the IMU strapdown integration and the inaccuracies of the GNSS velocity. While the work by Setuain et al (2018) used photocells for drift estimation, only the research from Stanton et al (2016) considered a validation with respect to the photocell data. The mean error reported in the latter case (2.6%) for 10 m sprint was higher than the median (IQR) error presented here i.e., 0.1 (−1.7 to 1.9) ( Table 1 ) for a 30 m sprint.…”

“…While wearable inertial sensors have shown promising results in the assessment of temporal gait parameters in running and sprinting ( Leitch et al, 2011 ; Bergamini et al, 2012 ; Norris et al, 2014 ; Falbriard et al, 2018 ; Macadam et al, 2019 ), their use for analysis of instantaneous sprint velocity and other sprint mechanics has been rather rare. Recently, a magnetic and inertial measurement unit (MIMU) based algorithm ( Setuain et al, 2018 ) has been developed to assess sprint mechanics with various parameters such as maximal velocity, maximal horizontal force and power, velocity at zero horizontal force, etc., for 20 m sprints. Though this work allows the measurement of sprint mechanics using a single MIMU mounted on the trunk, the algorithm relies on the use of split times from photocells at specific distances to remove the accumulated drift in the velocity.…”