Discrimination of gender-, speed-, and shoe-dependent movement patterns in runners using full-body kinematics

Maurer, Christian; Federolf, Peter; Tscharner, Vinzenz von; Stirling, Lisa M.; Nigg, Benno M.

doi:10.1016/j.gaitpost.2011.12.023

Cited by 70 publications

(95 citation statements)

References 27 publications

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This file was dowloaded from the institutional repository Brage NIH -brage.bibsys.no/nih Nigg, B., Baltich, J., Maurer, C., Federolf, P. (2012)

AbstractPrevious studies investigating the effects of shoe midsole hardness on running kinematics have often used male subjects from within a narrow age range. It is unknown whether shoe midsole hardness has the same kinematic effect on male and female runners as well as runners from different age categories.

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confidence: 99%

“…This file was dowloaded from the institutional repository Brage NIH -brage.bibsys.no/nih Nigg, B., Baltich, J., Maurer, C., Federolf, P. (2012) …”

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confidence: 99%

“…Additionally, 21 most kinematic evaluations of the effects of footwear, sex, and age have focused on 22 biomechanical variables evaluated at discrete time points (Butler et al, 2006;Fukuchi 23 and Duarte, 2008;Hardin et al, 2004;Keenan et al, 2011 (Daffertshofer et al, 2004;Epifanio et al, 2008;Maurer et al, 2012; 31 Moore et al, 2009;Troje, 2002) and support vector machine (SVM) (Begg et al, 2005;32 Vapnik, 1995;Weston, 1999). The kinematic marker data from an entire stance phase 33 can then be used in one analysis step to determine lower-extremity differences for 34 certain groups.…”

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Shoe midsole hardness, sex and age effects on lower extremity kinematics during running

Nigg¹,

Baltich²,

Maurer³

et al. 2012

Journal of Biomechanics

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102

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This file was dowloaded from the institutional repository Brage NIH -brage.bibsys.no/nih Nigg, B., Baltich, J., Maurer, C., Federolf, P. (2012) AbstractPrevious studies investigating the effects of shoe midsole hardness on running kinematics have often used male subjects from within a narrow age range. It is unknown whether shoe midsole hardness has the same kinematic effect on male and female runners as well as runners from different age categories. As sex and age have an effect on running kinematics, it is important to understand if shoe midsole hardness affects the kinematics of these groups in a similar fashion. However, current literature on the effects of sex and age on running kinematics are also limited to a narrow age range distribution in their study population. Therefore, this study tested the influence of three different midsole hardness conditions, sex and age on the lower extremity kinematics during heel-toe running. A comprehensive analysis approach was used to analyze the lower-extremity kinematic gait variables for 93 runners (male and female) aged 16-75 years. Participants ran at 3.33 ± 0.15 m/s on a 30 m-long runway with soft, medium and hard midsoles. A principal component analysis combined with a support vector machine showed that running kinematics based on shoe midsole hardness, sex, and age were separable and classifiable. Shoe midsole hardness demonstrated a subjectindependent effect on the kinematics of running. Additionally, it was found that age differences affected the more dominant movement components of running compared to differences due to the sex of a runner.

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This file was dowloaded from the institutional repository Brage NIH -brage.bibsys.no/nih Nigg, B., Baltich, J., Maurer, C., Federolf, P. (2012)

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mentioning

confidence: 99%

“…This file was dowloaded from the institutional repository Brage NIH -brage.bibsys.no/nih Nigg, B., Baltich, J., Maurer, C., Federolf, P. (2012) …”

mentioning

confidence: 99%

mentioning

confidence: 99%

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Shoe midsole hardness, sex and age effects on lower extremity kinematics during running

Nigg¹,

Baltich²,

Maurer³

et al. 2012

Journal of Biomechanics

Self Cite

116

102

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“…[3] Several studies in the gait analysis domain have applied variations of this approach and various marker sets have been used across these studies. [1,[3][4][5][6][7][8][9][10][11][12] The marker sets can be differentiated based on two major aspects. Firstly, whether the marker set covers the full body or body parts; full body marker sets were used most frequently.…”

Section: Introductionmentioning

confidence: 99%

“…Firstly, whether the marker set covers the full body or body parts; full body marker sets were used most frequently. [1,[3][4][5][6]11] Body part marker sets include unilateral placement on the lower extremity, [7,10,12] unilateral placement on the upper and lower extremity [9] and bilateral placement on the lower body and thorax. [8] Secondly, marker sets can be differentiated based on whether the markers are placed exclusively on specific anatomical landmarks.…”

Section: Introductionmentioning

confidence: 99%

Comparison of different marker sets for marker trajectory and principal component analysis based classification of simulated gait impairments

Christian

Kluge

Eskofier

et al. 2016

JBEI

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Objective: Many different marker sets have been used in marker trajectory based gait classification approaches. Little knowledge exists about the effects of specific marker sets on the subsequent statistical modeling. Such analysis is often based on principal component analysis. The aim of this study was to test the effect of marker set choice on marker trajectory and principal component analysis based gait classification. Methods: This study tested the performance of principal component analysis based gait classification models with various marker sets on the basis of simulated gait impairments. Simulated gait impairments were used to enable a high level of control of the gait patterns. Results: Classification accuracies were similar across most tested marker sets. Improved performance could be detected for some marker sets depending on the type of impairment. Conclusion: Several potentially valid marker sets exist for a specific gait classification task even though trends could be found suggesting that optimal marker set choice is dependent on functional aspects of the movement.

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Extraction of basic movement from whole-body movement, based on gait variability

et al. 2013

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The aim of this study was to quantify the step-to-step variability (SSV) in speed-variant and speed-invariant movement components of the whole-body gait pattern during running. These separate aspects of variability can be used to gain insight into the neuromuscular control strategies that are engaged during running. Ten healthy, physically active, male recreational athletes performed five treadmill running trials at five different speeds (range: 1.3–4.9 m/sec). The whole-body movement was separated into principal movements (PM) using a principal component analysis. The PMs were split into two groups: a speed-variant group, where the range of motion (amplitude of PMs) changed with running speed; and a speed-invariant group, where the range of motion was constant across various speeds. The step-to-step variability (SSV) of the two groups was then quantified. The absolute SSV was the summed variability across all gait cycles, whereas the relative SSV was the summed variability divided by the magnitude of the movement. The absolute SSV of the speed-variant movements increased with running speed. By contrast, the relative SSV of the speed-variant group (as normalized to the PM amplitude) decreased asymptotically toward a minimal level as running speed increased. Both the absolute and relative SSV of the speed-invariant movements revealed a minimum at 3.1 m/sec. The whole-body gait pattern during running can be subdivided into speed-variant and speed-invariant movements. An interpretation of the SSV based on minimal intervention theory suggests that speed-variant movements are more tightly controlled, as evidenced by a lower degree of variability compared to the speed-invariant movements.

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Discrimination of gender-, speed-, and shoe-dependent movement patterns in runners using full-body kinematics

Cited by 70 publications

References 27 publications

Shoe midsole hardness, sex and age effects on lower extremity kinematics during running

Shoe midsole hardness, sex and age effects on lower extremity kinematics during running

Comparison of different marker sets for marker trajectory and principal component analysis based classification of simulated gait impairments

Extraction of basic movement from whole-body movement, based on gait variability

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