The use of IMU-based human motion capture to assess kinematic parameters of specific exercises performed by 400 m hurdlers

(Einsatz von IMU-basierter Bewegungserfassung zur Bewertung kinematischer Parameter bei spezifischen Übungen von 400-m-Hürdenläufern)

The 400 m hurdles is a difficult track and field event, in which the hurdle clearing technique is of crucial importance. In this work, we analyse hurdle clearance while performing two specific exercises: marching and running. We evaluated the kinematic parameters (bending angle and movement speed) of the knee joint and movement trajectory (of the thigh and shank) when performing exercises with the left ("stronger") and right ("weaker") lead leg. Two 400 m hurdlers of the Polish National Athletic Team participated in the analysis. The exercises were performed on five 91 cm high hurdles; the third hurdle was filmed using a Motion Capture (Perception Neuron) system with Axis Neuron Pro software consisting of 18 IMU sensors operating at a frequency of 120 Hz. The analysis demonstrated significant difference in the angle parameters of the "stronger" and "weaker" trail leg knee (1), no differences in the movement speed during exercises performed with alternate legs (2) and individual chara cteristics of movement trajectory in both exercises (3). The results may be used to optimise of the hurdle training process.
© Copyright 2019 Proceedings of the 7th International Conference on Sport Sciences Research and Technology Support icSPORTS - Volume 1. Veröffentlicht von Science and Technology Publications. Alle Rechte vorbehalten.

Bibliographische Detailangaben
Schlagworte:
Notationen:Kraft-Schnellkraft-Sportarten Naturwissenschaften und Technik
Tagging:Kinematik
Veröffentlicht in:Proceedings of the 7th International Conference on Sport Sciences Research and Technology Support icSPORTS - Volume 1
Sprache:Englisch
Veröffentlicht: Setúbal Science and Technology Publications 2019
Online-Zugang:http://doi.org/10.5220/0008363602090216
Seiten:209-216
Dokumentenarten:Artikel
Level:hoch