Assessment of Ground Contact Time in the Field: Evaluation of Validity and Reliability

Abstract Weber, JA, Hart, NH, Rantalainen, T, Connick, M, and Newton, RU. Assessment of ground contact time in the field: evaluation of validity and reliability. J Strength Cond Res 38(1): e34–e39, 2024—The capacity to measure the kinetic and kinematic components of running has been extensively investigated in laboratory settings. Many authors have produced work that is of high value to practitioners within sporting environments; however, the lack of field-based technology to assess features of running gait validly and reliably has prevented the application of these valuable works. This paper examines the validity and reliability of a practical field-based methodology for using commercial inertial measurement units (IMUs) to assess ground contact time (GCT). Validity was examined in the comparison of GCT measured from ground reaction force by a force plate and that determined by a lumbar mounted commercial IMU and analyzed using a commercially available system (SPEEDSIG). Reliability was assessed by a field-based examination of within and between-session variability in GCT measured using a commercially available system (SPEEDSIG). Significance was set at p ≤ 0.05. Results for validity (intraclass correlation [ICC] 0.83) and reliability (ICC 0.91) confirm that the described field-based methodology is qualified for use to determine GCT in a practical setting. The implications of this study are important as they offer sport practitioners (S&C coaches, rehab specialists, and physios) a scalable method to assess GCT in the field to develop greater understanding of their athletes and improve performance, injury prevention, and rehabilitation interventions. Furthermore, these results provide the foundation for further work that could provide greater detail describing individual running gait in the field.

[1]  D. Habibi,et al.  Assessment of a Novel Algorithm to Determine Change-of-Direction Angles While Running Using Inertial Sensors. , 2020, Journal of strength and conditioning research.

[2]  T. Stellingwerff,et al.  “Question Your Categories”: the Misunderstood Complexity of Middle-Distance Running Profiles With Implications for Research Methods and Application , 2019, Front. Sports Act. Living.

[3]  B. Elfving,et al.  Intraclass correlation – A discussion and demonstration of basic features , 2019, PloS one.

[4]  Dustin P. Joubert,et al.  Running Economy Strongly Related to Ground Contact Time Imbalances , 2019, Medicine & Science in Sports & Exercise.

[5]  J. Vanrenterghem,et al.  The feasibility of predicting ground reaction forces during running from a trunk accelerometry driven mass-spring-damper model , 2018, PeerJ.

[6]  Christian A. Clermont,et al.  The use of wearable devices for walking and running gait analysis outside of the lab: A systematic review. , 2018, Gait & posture.

[7]  Valentina Camomilla,et al.  Trends Supporting the In-Field Use of Wearable Inertial Sensors for Sport Performance Evaluation: A Systematic Review , 2018, Sensors.

[8]  D. Kerwin,et al.  Sprint Running Performance and Technique Changes in Athletes During Periodized Training: An Elite Training Group Case Study. , 2017, International journal of sports physiology and performance.

[9]  Akifumi Matsuo,et al.  Association of Sprint Performance With Ground Reaction Forces During Acceleration and Maximal Speed Phases in a Single Sprint. , 2017, Journal of applied biomechanics.

[10]  M. Provencher,et al.  ACL Return to Sport Guidelines and Criteria , 2017, Current Reviews in Musculoskeletal Medicine.

[11]  K. Hébert-Losier,et al.  Similar Running Economy With Different Running Patterns Along the Aerial-Terrestrial Continuum. , 2017, International journal of sports physiology and performance.

[12]  J. Vanrenterghem,et al.  The Relationship Between Whole-Body External Loading and Body-Worn Accelerometry During Team-Sport Movements. , 2017, International journal of sports physiology and performance.

[13]  Peter Blanch,et al.  Training loads and injury risk in Australian football—differing acute: chronic workload ratios influence match injury risk , 2016, British Journal of Sports Medicine.

[14]  S. Dorel,et al.  A simple method for measuring power, force, velocity properties, and mechanical effectiveness in sprint running , 2016, Scandinavian journal of medicine & science in sports.

[15]  N. Gill,et al.  Field monitoring of sprinting power–force–velocity profile before, during and after hamstring injury: two case reports , 2016, Journal of sports sciences.

[16]  Alice J. Sweeting,et al.  Inertial sensors to estimate the energy expenditure of team-sport athletes. , 2016, Journal of science and medicine in sport.

[17]  D. Berckmans,et al.  Wireless Tri-Axial Trunk Accelerometry Detects Deviations in Dynamic Center of Mass Motion Due to Running-Induced Fatigue , 2015, PloS one.

[18]  S. Brown,et al.  Mechanical Properties of Sprinting in Elite Rugby Union and Rugby League. , 2015, International journal of sports physiology and performance.

[19]  Tim J Gabbett,et al.  Accelerometer and GPS-Derived Running Loads and Injury Risk in Elite Australian Footballers , 2014, Journal of strength and conditioning research.

[20]  Reed Ferber,et al.  Classification accuracy of a single tri-axial accelerometer for training background and experience level in runners. , 2014, Journal of biomechanics.

[21]  H. Jullien,et al.  Locomotor Performance in Highly-Trained Young Soccer Players: Does Body Size Always Matter? , 2013, International Journal of Sports Medicine.

[22]  Brad Aisbett,et al.  Validity of an upper-body-mounted accelerometer to measure peak vertical and resultant force during running and change-of-direction tasks , 2013, Sports biomechanics.

[23]  J. Mendiguchia,et al.  Hamstring exercises for track and field athletes: injury and exercise biomechanics, and possible implications for exercise selection and primary prevention , 2012, British Journal of Sports Medicine.

[24]  Hélène Pillet,et al.  Estimation of temporal parameters during sprint running using a trunk-mounted inertial measurement unit. , 2012, Journal of biomechanics.

[25]  M. Bourdin,et al.  Mechanical determinants of 100-m sprint running performance , 2012, European Journal of Applied Physiology.

[26]  J. Morin,et al.  Technical ability of force application as a determinant factor of sprint performance. , 2011, Medicine and science in sports and exercise.

[27]  D. Kerwin,et al.  Elite sprinting: are athletes individually step-frequency or step-length reliant? , 2011, Medicine & Science in Sports & Exercise.

[28]  A. Chaouachi,et al.  Effects of Running Velocity on Running Kinetics and Kinematics , 2011, Journal of strength and conditioning research.

[29]  J. Mendiguchia,et al.  Contralateral Leg Deficits in Kinetic and Kinematic Variables During Running in Australian Rules Football Players With Previous Hamstring Injuries , 2010, Journal of strength and conditioning research.

[30]  Giovanni A. Cavagna,et al.  Symmetry and Asymmetry in Bouncing Gaits , 2010, Symmetry.

[31]  Erik M. Bollt,et al.  High Resolution MEMS Accelerometers to Estimate VO2 and Compare Running Mechanics between Highly Trained Inter-Collegiate and Untrained Runners , 2009, PloS one.

[32]  Robyn L. Jones,et al.  An in-depth assessment of expert sprint coaches' technical knowledge , 2009, Journal of sports sciences.

[33]  Franco M Impellizzeri,et al.  Test validation in sport physiology: lessons learned from clinimetrics. , 2009, International journal of sports physiology and performance.

[34]  T. Keränen,et al.  Factors related to top running speed and economy. , 2007, International journal of sports medicine.

[35]  Heikki Kyröläinen,et al.  A simple method for measuring stiffness during running. , 2005, Journal of applied biomechanics.

[36]  A. Hof,et al.  Assessment of spatio-temporal gait parameters from trunk accelerations during human walking. , 2003, Gait & posture.

[37]  P. Weyand,et al.  Faster top running speeds are achieved with greater ground forces not more rapid leg movements. , 2000, Journal of applied physiology.

[38]  Joseph Foss,et al.  Comparing Methods of Clinical Measurement: Reporting Standards for Bland and Altman Analysis , 2000, Anesthesia and analgesia.

[39]  R. Moe-Nilssen,et al.  A new method for evaluating motor control in gait under real-life environmental conditions. Part 2: Gait analysis. , 1998, Clinical biomechanics.

[40]  D. Altman,et al.  Statistics notes: The normal distribution , 1995, BMJ.

[41]  D. Winter Biomechanics and Motor Control of Human Movement , 1990 .

[42]  Marcela Munera,et al.  Intra and Inter Test Repeatability of Accelerometric Indicators Measured While Running , 2016 .

[43]  Jorunn L Helbostad,et al.  Estimation of gait cycle characteristics by trunk accelerometry. , 2004, Journal of biomechanics.