From big data to rich data: The key features of athlete wheelchair mobility performance

R.M.A. van der Slikke, M.A.M. Berger, D.J.J. Bregman, H.E.J. Veeger

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

Quantitative assessment of an athlete׳s individual wheelchair mobility performance is one prerequisite needed to evaluate game performance, improve wheelchair settings and optimize training routines. Inertial Measurement Unit (IMU) based methods can be used to perform such quantitative assessment, providing a large number of kinematic data. The goal of this research was to reduce that large amount of data to a set of key features best describing wheelchair mobility performance in match play and present them in meaningful way for both scientists and athletes. To test the discriminative power, wheelchair mobility characteristics of athletes with different performance levels were compared. The wheelchair kinematics of 29 (inter-)national level athletes were measured during a match using three inertial sensors mounted on the wheelchair. Principal component analysis was used to reduce 22 kinematic outcomes to a set of six outcomes regarding linear and rotational movement; speed and acceleration; average and best performance. In addition, it was explored whether groups of athletes with known performance differences based on their impairment classification also differed with respect to these key outcomes using univariate general linear models. For all six key outcomes classification showed to be a significant factor (p<0.05). We composed a set of six key kinematic outcomes that accurately describe wheelchair mobility performance in match play. The key kinematic outcomes were displayed in an easy to interpret way, usable for athletes, coaches and scientists. This standardized representation enables comparison of different wheelchair sports regarding wheelchair mobility, but also evaluation at the level of an individual athlete. By this means, the tool could enhance further development of wheelchair sports in general.
Original languageEnglish
Pages (from-to)3340-3346
JournalJournal of Biomechanics
Volume49
Issue number14
DOIs
Publication statusPublished - 2016

Fingerprint

Wheelchairs
Athletes
Biomechanical Phenomena
Kinematics
Sports
Big data
Units of measurement
Principal Component Analysis
Principal component analysis
Linear Models

Cite this

van der Slikke, R.M.A. ; Berger, M.A.M. ; Bregman, D.J.J. ; Veeger, H.E.J. / From big data to rich data: The key features of athlete wheelchair mobility performance. In: Journal of Biomechanics. 2016 ; Vol. 49, No. 14. pp. 3340-3346.
@article{edde279e1c884484a9ca83ec3b12e232,
title = "From big data to rich data: The key features of athlete wheelchair mobility performance",
abstract = "Quantitative assessment of an athlete׳s individual wheelchair mobility performance is one prerequisite needed to evaluate game performance, improve wheelchair settings and optimize training routines. Inertial Measurement Unit (IMU) based methods can be used to perform such quantitative assessment, providing a large number of kinematic data. The goal of this research was to reduce that large amount of data to a set of key features best describing wheelchair mobility performance in match play and present them in meaningful way for both scientists and athletes. To test the discriminative power, wheelchair mobility characteristics of athletes with different performance levels were compared. The wheelchair kinematics of 29 (inter-)national level athletes were measured during a match using three inertial sensors mounted on the wheelchair. Principal component analysis was used to reduce 22 kinematic outcomes to a set of six outcomes regarding linear and rotational movement; speed and acceleration; average and best performance. In addition, it was explored whether groups of athletes with known performance differences based on their impairment classification also differed with respect to these key outcomes using univariate general linear models. For all six key outcomes classification showed to be a significant factor (p<0.05). We composed a set of six key kinematic outcomes that accurately describe wheelchair mobility performance in match play. The key kinematic outcomes were displayed in an easy to interpret way, usable for athletes, coaches and scientists. This standardized representation enables comparison of different wheelchair sports regarding wheelchair mobility, but also evaluation at the level of an individual athlete. By this means, the tool could enhance further development of wheelchair sports in general.",
author = "{van der Slikke}, R.M.A. and M.A.M. Berger and D.J.J. Bregman and H.E.J. Veeger",
year = "2016",
doi = "10.1016/j.jbiomech.2016.08.022",
language = "English",
volume = "49",
pages = "3340--3346",
journal = "Journal of Biomechanics",
issn = "0021-9290",
publisher = "Elsevier Limited",
number = "14",

}

From big data to rich data: The key features of athlete wheelchair mobility performance. / van der Slikke, R.M.A.; Berger, M.A.M.; Bregman, D.J.J.; Veeger, H.E.J.

In: Journal of Biomechanics, Vol. 49, No. 14, 2016, p. 3340-3346.

Research output: Contribution to JournalArticleAcademicpeer-review

TY - JOUR

T1 - From big data to rich data: The key features of athlete wheelchair mobility performance

AU - van der Slikke, R.M.A.

AU - Berger, M.A.M.

AU - Bregman, D.J.J.

AU - Veeger, H.E.J.

PY - 2016

Y1 - 2016

N2 - Quantitative assessment of an athlete׳s individual wheelchair mobility performance is one prerequisite needed to evaluate game performance, improve wheelchair settings and optimize training routines. Inertial Measurement Unit (IMU) based methods can be used to perform such quantitative assessment, providing a large number of kinematic data. The goal of this research was to reduce that large amount of data to a set of key features best describing wheelchair mobility performance in match play and present them in meaningful way for both scientists and athletes. To test the discriminative power, wheelchair mobility characteristics of athletes with different performance levels were compared. The wheelchair kinematics of 29 (inter-)national level athletes were measured during a match using three inertial sensors mounted on the wheelchair. Principal component analysis was used to reduce 22 kinematic outcomes to a set of six outcomes regarding linear and rotational movement; speed and acceleration; average and best performance. In addition, it was explored whether groups of athletes with known performance differences based on their impairment classification also differed with respect to these key outcomes using univariate general linear models. For all six key outcomes classification showed to be a significant factor (p<0.05). We composed a set of six key kinematic outcomes that accurately describe wheelchair mobility performance in match play. The key kinematic outcomes were displayed in an easy to interpret way, usable for athletes, coaches and scientists. This standardized representation enables comparison of different wheelchair sports regarding wheelchair mobility, but also evaluation at the level of an individual athlete. By this means, the tool could enhance further development of wheelchair sports in general.

AB - Quantitative assessment of an athlete׳s individual wheelchair mobility performance is one prerequisite needed to evaluate game performance, improve wheelchair settings and optimize training routines. Inertial Measurement Unit (IMU) based methods can be used to perform such quantitative assessment, providing a large number of kinematic data. The goal of this research was to reduce that large amount of data to a set of key features best describing wheelchair mobility performance in match play and present them in meaningful way for both scientists and athletes. To test the discriminative power, wheelchair mobility characteristics of athletes with different performance levels were compared. The wheelchair kinematics of 29 (inter-)national level athletes were measured during a match using three inertial sensors mounted on the wheelchair. Principal component analysis was used to reduce 22 kinematic outcomes to a set of six outcomes regarding linear and rotational movement; speed and acceleration; average and best performance. In addition, it was explored whether groups of athletes with known performance differences based on their impairment classification also differed with respect to these key outcomes using univariate general linear models. For all six key outcomes classification showed to be a significant factor (p<0.05). We composed a set of six key kinematic outcomes that accurately describe wheelchair mobility performance in match play. The key kinematic outcomes were displayed in an easy to interpret way, usable for athletes, coaches and scientists. This standardized representation enables comparison of different wheelchair sports regarding wheelchair mobility, but also evaluation at the level of an individual athlete. By this means, the tool could enhance further development of wheelchair sports in general.

U2 - 10.1016/j.jbiomech.2016.08.022

DO - 10.1016/j.jbiomech.2016.08.022

M3 - Article

VL - 49

SP - 3340

EP - 3346

JO - Journal of Biomechanics

JF - Journal of Biomechanics

SN - 0021-9290

IS - 14

ER -