Predicting cumulative load during running using field-based measures

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review

Standard

Predicting cumulative load during running using field-based measures. / Backes, Anne; Skejø, Sebastian Deisting; Gette, Paul; Nielsen, Rasmus Østergaard; Sørensen, Henrik; Morio, Cédric; Malisoux, Laurent.

In: Scandinavian Journal of Medicine & Science in Sports, Vol. 30, No. 12, 12.2020, p. 2399-2407.

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review

Harvard

Backes, A, Skejø, SD, Gette, P, Nielsen, RØ, Sørensen, H, Morio, C & Malisoux, L 2020, 'Predicting cumulative load during running using field-based measures', Scandinavian Journal of Medicine & Science in Sports, vol. 30, no. 12, pp. 2399-2407. https://doi.org/10.1111/sms.13796

APA

Backes, A., Skejø, S. D., Gette, P., Nielsen, R. Ø., Sørensen, H., Morio, C., & Malisoux, L. (2020). Predicting cumulative load during running using field-based measures. Scandinavian Journal of Medicine & Science in Sports, 30(12), 2399-2407. https://doi.org/10.1111/sms.13796

CBE

Backes A, Skejø SD, Gette P, Nielsen RØ, Sørensen H, Morio C, Malisoux L. 2020. Predicting cumulative load during running using field-based measures. Scandinavian Journal of Medicine & Science in Sports. 30(12):2399-2407. https://doi.org/10.1111/sms.13796

MLA

Backes, Anne et al. "Predicting cumulative load during running using field-based measures". Scandinavian Journal of Medicine & Science in Sports. 2020, 30(12). 2399-2407. https://doi.org/10.1111/sms.13796

Vancouver

Backes A, Skejø SD, Gette P, Nielsen RØ, Sørensen H, Morio C et al. Predicting cumulative load during running using field-based measures. Scandinavian Journal of Medicine & Science in Sports. 2020 Dec;30(12):2399-2407. https://doi.org/10.1111/sms.13796

Author

Backes, Anne ; Skejø, Sebastian Deisting ; Gette, Paul ; Nielsen, Rasmus Østergaard ; Sørensen, Henrik ; Morio, Cédric ; Malisoux, Laurent. / Predicting cumulative load during running using field-based measures. In: Scandinavian Journal of Medicine & Science in Sports. 2020 ; Vol. 30, No. 12. pp. 2399-2407.

Bibtex

@article{53f411149c014e309131d0050416eea6,
title = "Predicting cumulative load during running using field-based measures",
abstract = "The main objective was to investigate whether the cumulative load of the lower limbs, defined as the product of external load and step rate, could be predicted using spatiotemporal variables gathered with a commercially available wearable device in running. Therefore, thirty-nine runners performed two running tests at 10 and 12 km/h, respectively. Spatiotemporal variables (step rate, ground contact time, and vertical oscillation) were collected using a commercially available wearable device. Kinetic variables, measured with gold standard equipment (motion capture system and instrumented treadmill) and used for the calculation of a set of variables representing cumulative load, were peak vertical ground reaction force (peak vGRF), vertical instantaneous loading rate (VILR), vertical impulse, braking impulse, as well as peak extension moments and angular impulses of the ankle, knee and hip joints. Separate linear mixed-effects models were built to investigate the prediction performance of the spatiotemporal variables for each measure of cumulative load. BMI, speed, and sex were included as covariates. Predictive precision of the models ranged from .11 to .66 (R2m) and .22 to .98 (R2c), respectively. Greatest predictive performance was obtained for the cumulative peak vGRF (R2m = .66, R2c = .97), VILR (R2m = .43, R2c = .97), braking impulse (R2m = .52, R2c = .98), and peak hip extension moment (R2m = .54, R2c = .90). In conclusion, certain variables representing cumulative load of the lower limbs in running can be predicted using spatiotemporal variables gathered with a commercially available wearable device.",
keywords = "biomechanics, injury prevention, running, sports injury, wearables",
author = "Anne Backes and Skej{\o}, {Sebastian Deisting} and Paul Gette and Nielsen, {Rasmus {\O}stergaard} and Henrik S{\o}rensen and C{\'e}dric Morio and Laurent Malisoux",
note = "{\textcopyright} 2020 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.",
year = "2020",
month = dec,
doi = "10.1111/sms.13796",
language = "English",
volume = "30",
pages = "2399--2407",
journal = "Scandinavian Journal of Medicine & Science in Sports",
issn = "0905-7188",
publisher = "Wiley-Blackwell Publishing Ltd.",
number = "12",

}

RIS

TY - JOUR

T1 - Predicting cumulative load during running using field-based measures

AU - Backes, Anne

AU - Skejø, Sebastian Deisting

AU - Gette, Paul

AU - Nielsen, Rasmus Østergaard

AU - Sørensen, Henrik

AU - Morio, Cédric

AU - Malisoux, Laurent

N1 - © 2020 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

PY - 2020/12

Y1 - 2020/12

N2 - The main objective was to investigate whether the cumulative load of the lower limbs, defined as the product of external load and step rate, could be predicted using spatiotemporal variables gathered with a commercially available wearable device in running. Therefore, thirty-nine runners performed two running tests at 10 and 12 km/h, respectively. Spatiotemporal variables (step rate, ground contact time, and vertical oscillation) were collected using a commercially available wearable device. Kinetic variables, measured with gold standard equipment (motion capture system and instrumented treadmill) and used for the calculation of a set of variables representing cumulative load, were peak vertical ground reaction force (peak vGRF), vertical instantaneous loading rate (VILR), vertical impulse, braking impulse, as well as peak extension moments and angular impulses of the ankle, knee and hip joints. Separate linear mixed-effects models were built to investigate the prediction performance of the spatiotemporal variables for each measure of cumulative load. BMI, speed, and sex were included as covariates. Predictive precision of the models ranged from .11 to .66 (R2m) and .22 to .98 (R2c), respectively. Greatest predictive performance was obtained for the cumulative peak vGRF (R2m = .66, R2c = .97), VILR (R2m = .43, R2c = .97), braking impulse (R2m = .52, R2c = .98), and peak hip extension moment (R2m = .54, R2c = .90). In conclusion, certain variables representing cumulative load of the lower limbs in running can be predicted using spatiotemporal variables gathered with a commercially available wearable device.

AB - The main objective was to investigate whether the cumulative load of the lower limbs, defined as the product of external load and step rate, could be predicted using spatiotemporal variables gathered with a commercially available wearable device in running. Therefore, thirty-nine runners performed two running tests at 10 and 12 km/h, respectively. Spatiotemporal variables (step rate, ground contact time, and vertical oscillation) were collected using a commercially available wearable device. Kinetic variables, measured with gold standard equipment (motion capture system and instrumented treadmill) and used for the calculation of a set of variables representing cumulative load, were peak vertical ground reaction force (peak vGRF), vertical instantaneous loading rate (VILR), vertical impulse, braking impulse, as well as peak extension moments and angular impulses of the ankle, knee and hip joints. Separate linear mixed-effects models were built to investigate the prediction performance of the spatiotemporal variables for each measure of cumulative load. BMI, speed, and sex were included as covariates. Predictive precision of the models ranged from .11 to .66 (R2m) and .22 to .98 (R2c), respectively. Greatest predictive performance was obtained for the cumulative peak vGRF (R2m = .66, R2c = .97), VILR (R2m = .43, R2c = .97), braking impulse (R2m = .52, R2c = .98), and peak hip extension moment (R2m = .54, R2c = .90). In conclusion, certain variables representing cumulative load of the lower limbs in running can be predicted using spatiotemporal variables gathered with a commercially available wearable device.

KW - biomechanics

KW - injury prevention

KW - running

KW - sports injury

KW - wearables

UR - http://www.scopus.com/inward/record.url?scp=85089993116&partnerID=8YFLogxK

U2 - 10.1111/sms.13796

DO - 10.1111/sms.13796

M3 - Journal article

C2 - 32767716

VL - 30

SP - 2399

EP - 2407

JO - Scandinavian Journal of Medicine & Science in Sports

JF - Scandinavian Journal of Medicine & Science in Sports

SN - 0905-7188

IS - 12

ER -