Literature DB >> 29842825

Accuracy and precision of loadsol® insole force-sensors for the quantification of ground reaction force-based biomechanical running parameters.

Wolfgang Seiberl1, Elisabeth Jensen2,3, Josephine Merker1, Marco Leitel1, Ansgar Schwirtz1.   

Abstract

Force plates represent the "gold standard" in measuring running kinetics to predict performance or to identify the sources of running-related injuries. As these measurements are generally limited to laboratory analyses, wireless high-quality sensors for measuring in the field are needed. This work analysed the accuracy and precision of a new wireless insole forcesensor for quantifying running-related kinetic parameters. Vertical ground reaction force (GRF) was simultaneously measured with pit-mounted force plates (1 kHz) and loadsol® sensors (100 Hz) under unshod forefoot and rearfoot running-step conditions. GRF data collections were repeated four times, each separated by 30 min treadmill running, to test influence of extended use. A repeated-measures ANOVA was used to identify differences between measurement devices. Additionally, mean bias and Bland-Altman limits of agreement (LoA) were calculated. We found a significant difference (p < .05) in ground contact time, peak force, and force rate, while there was no difference in parameters impulse, time to peak, and negative force rate. There was no influence of time point of measurement. The mean bias of ground contact time, impulse, peak force, and time to peak ranged between 0.6% and 3.4%, demonstrating high accuracy of loadsol® devices for these parameters. For these same parameters, the LoA analysis showed that 95% of all measurement differences between insole and force plate measurements were less than 12%, demonstrating high precision of the sensors. However, highly dynamic behaviour of GRF, such as force rate, is not yet sufficiently resolved by the insole devices, which is likely explained by the low sampling rate.

Keywords:  Foot pressure measurement; force insoles; force plate; running-related injury; validation; wireless sensors

Mesh:

Year:  2018        PMID: 29842825     DOI: 10.1080/17461391.2018.1477993

Source DB:  PubMed          Journal:  Eur J Sport Sci        ISSN: 1536-7290            Impact factor:   4.050


  5 in total

1.  Ski Position during the Flight and Landing Preparation Phases in Ski Jumping Detected with Inertial Sensors.

Authors:  Veronica Bessone; Johannes Petrat; Ansgar Schwirtz
Journal:  Sensors (Basel)       Date:  2019-06-06       Impact factor: 3.576

2.  Foot Strike Angle Prediction and Pattern Classification Using LoadsolTM Wearable Sensors: A Comparison of Machine Learning Techniques.

Authors:  Stephanie R Moore; Christina Kranzinger; Julian Fritz; Thomas Stӧggl; Josef Krӧll; Hermann Schwameder
Journal:  Sensors (Basel)       Date:  2020-11-25       Impact factor: 3.576

3.  Effect of speed and gradient on plantar force when running on an AlterG® treadmill.

Authors:  Athol Thomson; Rodney Whiteley; Clint Hansen; Julius Welzel; Sebastien Racinais; Mathew G Wilson
Journal:  BMC Sports Sci Med Rehabil       Date:  2021-03-30

4.  The Recovery of Weight-Bearing Symmetry After Total Hip Arthroplasty Is Activity-Dependent.

Authors:  Sónia A Alves; Marco Preuße; Hagen Hommel; Georg N Duda; Alison N Agres
Journal:  Front Bioeng Biotechnol       Date:  2022-02-24

5.  The grade of instability in fragility fractures of the pelvis correlates with impaired early mobilization.

Authors:  Leon Marcel Faust; Alexander Martin Keppler; Eduardo Suero; Johannes Gleich; Leonard Lisitano; Wolfgang Böcker; Carl Neuerburg; Daniel Pfeufer
Journal:  Eur J Trauma Emerg Surg       Date:  2022-03-13       Impact factor: 2.374

  5 in total

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