Application of a Full Body Inertial Measurement System in Alpine Skiing: A Comparison with an Optical Video Based System

Krüger, Andreas; Edelmann‐Nusser, Jürgen

doi:10.1123/jab.26.4.516

Cited by 46 publications

(63 citation statements)

References 7 publications

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“…In order to analyze technique of the throw, that is kinematic parameters of the basketball jump shot, we used the MVN inertial suit MVN Biomech Pro-Inertial motion capture (Xsense, Enschede, The Netherlands). Previous studies have showed that this kind of equipment is appropriate for the analysis of sports movements when it comes to short physical actions, such as the jump shot (Krüger & Edelmann-Nusser, 2010;Supej, 2010;2011). The moment when the ball is released from the hand cannot be determined by the MVN program, so we also used a Casio Exilim -F1 camera that takes up to 300 photos per second.…”

Section: Methodsmentioning

confidence: 99%

The effect of shooting range on the dynamics of limbs angular velocities of the basketball shot

Podmenik

Supej

Čoh

et al. 2017

Kinesiology (Zagreb, Online)

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The aim of our research was to describe the joint angular velocities of young basketball players (U16) during their performance of jump shots and to find out what is the effect of increasing shooting range on these velocities. Our sample included 14 players that performing the function of guards. Their average age (±SD) was 15.43±0.51 years. The analysis contemplated 370 field goals, which were performed from three different distances (3.75 m, 5.25 m and 6.75 m) perpendicular to the hoop board. The measurements were performed using an Xsens MVN inertial suit. The results showed that the maximum angular velocity in the shoulder and elbow joint became greater with the increase of shooting range. In the throw from the shortest distance, the segments were integrated into the movement of the shooting arm according to the proximaldistal principle. The temporal sequences of maxima velocities in legs were preserved in throws from all the three distances. The findings are important for young basketball players and their coaches. They have to be aware of the needed adjustments to the techniques of throws from various ranges and they must take them into account when practicing.

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Section: Methodsmentioning

confidence: 99%

The effect of shooting range on the dynamics of limbs angular velocities of the basketball shot

Podmenik

Supej

Čoh

et al. 2017

Kinesiology (Zagreb, Online)

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“…To measure kinematic variables we used Xsens MVN inertial suit system with 17 three dimensional accelerometers /gyroscopes/ magnetometers placed on each foot, calf, thigh, hand, forearm, upper arm, shoulder, sternum, lower back and head. Xsens MVN system showed high validity and reliability in previous research (Brennan et al, 2011;Krüger and Edelmann-Nusser, 2010;Zhang, 2013) with error of up to 3 degrees for all axis. Result of shot put was measured according to IAAF rules (http://www.iaaf.org/about-iaaf/documents/rulesregulations/ IAAF Competition Rules 2016-2017 in force from 1 November 2015.pdf).…”

Section: Methodsmentioning

confidence: 55%

Untitled

2018

JPES

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The purpose of research was to determine important kinematic variables, which determine result in shot put of international level athlete. Athlete used rotational technique of shot put, which is very demanding from movement coordination point of view. Methods: With MVN Xsens dress with 17 accelerometers (data acquisition 120 Hz) we measured 36 shot puts in 3D and used 276 variables. Result of shot put was measured with IAAF judge's method. All joint and segment variables-trajectories, velocities, angels and angular velocities in all 3 axis we analysed and the differences between release moment and 0.1 second before release were calculated. Results: With series of regression analysis, we extracted the best predictors and with final stepwise regression explained 47.4% of shotput result, and what is the most important, the best predictors are low (negative) difference of angular velocity in y axe of left upper leg, low (negative) difference of angular velocity in y axe of T12 vertebra, and high difference of left ankle angle to x axe. Conclusion: Importance of opposite throw hand body side, which should be fast deaccelerated and stopped turning in order to give throw arm a rock support for its activity as an open side kinetic chain.

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“…More details about the GNSS system can be found in [ 14 ]. The GNSS measurement setup was combined with an IMU motion capture suit (Xsens MVN , Xsens Technologies, Enschede, The Netherlands) for capturing the full-body skier's posture as in previous studies [ 4 , 15 ]. The IMU motion capture suit (MVN) had 17 motion-tracking sensors.…”

Section: Methodsmentioning

confidence: 99%

Estimation of Alpine Skier Posture Using Machine Learning Techniques

Nemec

Petrič

Babič

et al. 2014

Sensors

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High precision Global Navigation Satellite System (GNSS) measurements are becoming more and more popular in alpine skiing due to the relatively undemanding setup and excellent performance. However, GNSS provides only single-point measurements that are defined with the antenna placed typically behind the skier's neck. A key issue is how to estimate other more relevant parameters of the skier's body, like the center of mass (COM) and ski trajectories. Previously, these parameters were estimated by modeling the skier's body with an inverted-pendulum model that oversimplified the skier's body. In this study, we propose two machine learning methods that overcome this shortcoming and estimate COM and skis trajectories based on a more faithful approximation of the skier's body with nine degrees-of-freedom. The first method utilizes a well-established approach of artificial neural networks, while the second method is based on a state-of-the-art statistical generalization method. Both methods were evaluated using the reference measurements obtained on a typical giant slalom course and compared with the inverted-pendulum method. Our results outperform the results of commonly used inverted-pendulum methods and demonstrate the applicability of machine learning techniques in biomechanical measurements of alpine skiing.

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Application of a Full Body Inertial Measurement System in Alpine Skiing: A Comparison with an Optical Video Based System

Cited by 46 publications

References 7 publications

The effect of shooting range on the dynamics of limbs angular velocities of the basketball shot

The effect of shooting range on the dynamics of limbs angular velocities of the basketball shot

Untitled

Estimation of Alpine Skier Posture Using Machine Learning Techniques

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