Literature DB >> 31525171

Relationship of Foot Strike Pattern and Landing Impacts during a Marathon.

Matthew Ruder1,2, Steve T Jamison1,2, Adam Tenforde1,2, Francis Mulloy3, Irene S Davis1,2.   

Abstract

PURPOSE: Foot strike patterns (FSP) influence landing mechanics, with rearfoot strike (RFS) runners exhibiting higher impact loading than forefoot strike (FFS) runners. The few studies that included midfoot strike (MFS) runners have typically grouped them together with FFS. In addition, most running studies have been conducted in laboratories. Advances in wearable technology now allow the measurement of runners' mechanics in their natural environment. The purpose of this study was to examine the relationship between FSP and impacts across a marathon race.
METHODS: A total of 222 healthy runners (119 males, 103 females; age, 44.1 ± 10.8 yr) running a marathon race were included. A treadmill assessment was undertaken to determine FSP. An ankle-mounted accelerometer recorded tibial shock (TS) over the course of the marathon. TS was compared between RFS, MFS, and FFS. Correlations between speed and impacts were examined between FSP. TS was also compared at the 10- and 40-km race points.
RESULTS: RFS and MFS runners exhibited similar TS (12.24g ± 3.59g vs 11.82g ± 2.68g, P = 0.46) that was significantly higher (P < 0.001 and P < 0.01, respectively) than FFS runners (9.88g ± 2.51g). In addition, TS increased with speed for both RFS (r = 0.54, P = 0.01) and MFS (r = 0.42, P = 0.02) runners, but not FFS (r = 0.05, P = 0.83). Finally, both speed (P < 0.001) and TS (P < 0.001) were reduced between the 10- and the 40-km race points. However, when normalized for speed, TS was not different (P = 0.84).
CONCLUSIONS: RFS and MFS exhibit higher TS than FFS. In addition, RFS and MFS increase TS with speed, whereas FFS do not. These results suggest that the impact loading of MFS is more like RFS than FFS. Finally, TS, when normalized for speed, is similar between the beginning and the end of the race.

Entities:  

Mesh:

Year:  2019        PMID: 31525171     DOI: 10.1249/MSS.0000000000002032

Source DB:  PubMed          Journal:  Med Sci Sports Exerc        ISSN: 0195-9131            Impact factor:   5.411


  13 in total

1.  Wearables for Running Gait Analysis: A Systematic Review.

Authors:  Rachel Mason; Liam T Pearson; Gillian Barry; Fraser Young; Oisin Lennon; Alan Godfrey; Samuel Stuart
Journal:  Sports Med       Date:  2022-10-15       Impact factor: 11.928

Review 2.  From barefoot hunter gathering to shod pavement pounding. Where to from here? A narrative review.

Authors:  Peter Francis; Grant Schofield
Journal:  BMJ Open Sport Exerc Med       Date:  2020-04-21

3.  Sacral acceleration can predict whole-body kinetics and stride kinematics across running speeds.

Authors:  Ryan S Alcantara; Evan M Day; Michael E Hahn; Alena M Grabowski
Journal:  PeerJ       Date:  2021-04-12       Impact factor: 2.984

4.  Predicting continuous ground reaction forces from accelerometers during uphill and downhill running: a recurrent neural network solution.

Authors:  Ryan S Alcantara; W Brent Edwards; Guillaume Y Millet; Alena M Grabowski
Journal:  PeerJ       Date:  2022-01-04       Impact factor: 2.984

5.  Drift-Free 3D Orientation and Displacement Estimation for Quasi-Cyclical Movements Using One Inertial Measurement Unit: Application to Running.

Authors:  Marit A Zandbergen; Jasper Reenalda; Robbert P van Middelaar; Romano I Ferla; Jaap H Buurke; Peter H Veltink
Journal:  Sensors (Basel)       Date:  2022-01-26       Impact factor: 3.576

6.  Estimation of Fine-Grained Foot Strike Patterns with Wearable Smartwatch Devices.

Authors:  Hyeyeoun Joo; Hyejoo Kim; Jeh-Kwang Ryu; Semin Ryu; Kyoung-Min Lee; Seung-Chan Kim
Journal:  Int J Environ Res Public Health       Date:  2022-01-24       Impact factor: 3.390

7.  Concurrent Evolution of Biomechanical and Physiological Parameters With Running-Induced Acute Fatigue.

Authors:  Gäelle Prigent; Salil Apte; Anisoara Paraschiv-Ionescu; Cyril Besson; Vincent Gremeaux; Kamiar Aminian
Journal:  Front Physiol       Date:  2022-02-11       Impact factor: 4.566

8.  Differences in Peak Impact Accelerations Among Foot Strike Patterns in Recreational Runners.

Authors:  Christopher Napier; Lauren Fridman; Paul Blazey; Nicholas Tran; Tom V Michie; Amy Schneeberg
Journal:  Front Sports Act Living       Date:  2022-03-04

9.  Towards Machine Learning-Based Detection of Running-Induced Fatigue in Real-World Scenarios: Evaluation of IMU Sensor Configurations to Reduce Intrusiveness.

Authors:  Luca Marotta; Jaap H Buurke; Bert-Jan F van Beijnum; Jasper Reenalda
Journal:  Sensors (Basel)       Date:  2021-05-15       Impact factor: 3.576

Review 10.  Is This the Real Life, or Is This Just Laboratory? A Scoping Review of IMU-Based Running Gait Analysis.

Authors:  Lauren C Benson; Anu M Räisänen; Christian A Clermont; Reed Ferber
Journal:  Sensors (Basel)       Date:  2022-02-23       Impact factor: 3.576

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.