Zobrazeno 1 - 10
of 29
pro vyhledávání: '"Stephan van der Zwaard"'
Autor:
Fábio Juner Lanferdini, Fernando Diefenthaeler, Andressa Germann Ávila, Antônio Renato Pereira Moro, Stephan van der Zwaard, Marco Aurélio Vaz
Publikováno v:
Sports, Vol 11, Iss 2, p 22 (2023)
The aim of this study was to determine if quadriceps morphology [muscle volume (MV); cross-sectional area (CSA)], vastus lateralis (VL) muscle architecture, and muscle quality [echo intensity (ECHO)] can explain differences in knee extensor maximal v
Externí odkaz:
https://doaj.org/article/975fabdc517b4b0e960cb26e98c036a2
Autor:
Stephan van der Zwaard, Tommie F. P. Koppens, Guido Weide, Koen Levels, Mathijs J. Hofmijster, Jos J. de Koning, Richard T. Jaspers
Publikováno v:
Frontiers in Sports and Active Living, Vol 3 (2021)
Training-induced adaptations in muscle morphology, including their magnitude and individual variation, remain relatively unknown in elite athletes. We reported changes in rowing performance and muscle morphology during the general and competitive pre
Externí odkaz:
https://doaj.org/article/a517a487583f4974bec633375c574d0d
Autor:
Jos Goudsmit, Ruby T. A. Otter, Inge Stoter, Berry van Holland, Stephan van der Zwaard, Johan de Jong, Steven Vos
Publikováno v:
Sensors, Vol 22, Iss 23, p 9073 (2022)
Athlete development depends on many factors that need to be balanced by the coach. The amount of data collected grows with the development of sensor technology. To make data-informed decisions for training prescription of their athletes, coaches coul
Externí odkaz:
https://doaj.org/article/61d568ef78f34a7a8d581accbc6afd49
Publikováno v:
Sensors, Vol 22, Iss 20, p 7996 (2022)
In this study, we investigated the relationships between training load, perceived wellness and match performance in professional volleyball by applying the machine learning techniques XGBoost, random forest regression and subgroup discovery. Physical
Externí odkaz:
https://doaj.org/article/40b03fb6fbc94649898a4cec40811c33
Publikováno v:
Frontiers in Sports and Active Living, Vol 3 (2021)
In the past decades, researchers have extensively studied (elite) athletes' physiological responses to understand how to maximize their endurance performance. In endurance sports, whole-body measurements such as the maximal oxygen consumption, lactat
Externí odkaz:
https://doaj.org/article/a7a72908ce2a4d2ebcb1f967d392f0ad
Publikováno v:
Frontiers in Physiology, Vol 10 (2019)
Do athletes specialize toward sports disciplines that are well aligned with their anthropometry? Novel machine-learning algorithms now enable scientists to cluster athletes based on their individual anthropometry while integrating multiple anthropome
Externí odkaz:
https://doaj.org/article/329136bed1844f4d83602b8e711f6d38
Autor:
Stephan van der Zwaard, Richard T Jaspers, Ilse J Blokland, Chantal Achterberg, Jurrian M Visser, Anne R den Uil, Mathijs J Hofmijster, Koen Levels, Dionne A Noordhof, Arnold de Haan, Jos J de Koning, Willem J van der Laarse, Cornelis J de Ruiter
Publikováno v:
PLoS ONE, Vol 11, Iss 9, p e0162914 (2016)
BACKGROUND:Near-infrared spectroscopy (NIRS) measurements of oxygenation reflect O2 delivery and utilization in exercising muscle and may improve detection of a critical exercise threshold. PURPOSE:First, to detect an oxygenation breakpoint (Δ[O2HbM
Externí odkaz:
https://doaj.org/article/ce90e12598234c3281acdc1e04c8a982
Autor:
Nina Jacobs, Daniek Mos, Frank W. Bloemers, Willem J. van der Laarse, Richard T. Jaspers, Stephan van der Zwaard
Publikováno v:
European Journal of Applied Physiology. Springer Verlag
Jacobs, N, Mos, D, Bloemers, F W, van der Laarse, W J, Jaspers, R T & van der Zwaard, S 2023, ' Low myoglobin concentration in skeletal muscle of elite cyclists is associated with low mRNA expression levels ', European Journal of Applied Physiology, vol. 123, no. 7, pp. 1469-1478 . https://doi.org/10.1007/s00421-023-05161-z
Jacobs, N, Mos, D, Bloemers, F W, van der Laarse, W J, Jaspers, R T & van der Zwaard, S 2023, ' Low myoglobin concentration in skeletal muscle of elite cyclists is associated with low mRNA expression levels ', European Journal of Applied Physiology, vol. 123, no. 7, pp. 1469-1478 . https://doi.org/10.1007/s00421-023-05161-z
Myoglobin is essential for oxygen transport to the muscle fibers. However, measurements of myoglobin (Mb) protein concentrations within individual human muscle fibers are scarce. Recent observations have revealed surprisingly low Mb concentrations in
Publikováno v:
International Journal of Sports Physiology and Performance, 1-9. Human Kinetics Publishers Inc.
STARTPAGE=1;ENDPAGE=9;ISSN=1555-0265;TITLE=International Journal of Sports Physiology and Performance
van der Zwaard, S, Otter, R T A, Kempe, M, Knobbe, A & Stoter, I K 2023, ' Capturing the Complex Relationship Between Internal and External Training Load : A Data-Driven Approach ', International Journal of Sports Physiology and Performance, vol. 18, no. 6, pp. 634-642 . https://doi.org/10.1123/ijspp.2022-0493
International Journal of Sports Physiology and Performance, 18(6), 634-642. Human Kinetics Publishers Inc.
STARTPAGE=1;ENDPAGE=9;ISSN=1555-0265;TITLE=International Journal of Sports Physiology and Performance
van der Zwaard, S, Otter, R T A, Kempe, M, Knobbe, A & Stoter, I K 2023, ' Capturing the Complex Relationship Between Internal and External Training Load : A Data-Driven Approach ', International Journal of Sports Physiology and Performance, vol. 18, no. 6, pp. 634-642 . https://doi.org/10.1123/ijspp.2022-0493
International Journal of Sports Physiology and Performance, 18(6), 634-642. Human Kinetics Publishers Inc.
Background: Training load is typically described in terms of internal and external load. Investigating the coupling of internal and external training load is relevant to many sports. Here, continuous kernel-density estimation (KDE) may be a valuable
Publikováno v:
de Leeuw, A W, van Baar, R, Knobbe, A & van der Zwaard, S 2022, ' Modeling Match Performance in Elite Volleyball Players : Importance of Jump Load and Strength Training Characteristics ', Sensors, vol. 22, no. 20, 7996, pp. 1-13 . https://doi.org/10.3390/s22207996
Sensors
Sensors, 22(20):7996, 1-13. Multidisciplinary Digital Publishing Institute (MDPI)
Sensors; Volume 22; Issue 20; Pages: 7996
Sensors, 22(20), 7996. MDPI
Sensors
Sensors, 22(20):7996, 1-13. Multidisciplinary Digital Publishing Institute (MDPI)
Sensors; Volume 22; Issue 20; Pages: 7996
Sensors, 22(20), 7996. MDPI
In this study, we investigated the relationships between training load, perceived wellness and match performance in professional volleyball by applying the machine learning techniques XGBoost, random forest regression and subgroup discovery. Physical
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9a03afbcc15aa2dc9d470c30d7ce49fe
https://research.vu.nl/en/publications/b4bfb4f6-51bd-4973-86fc-5d2339c4584a
https://research.vu.nl/en/publications/b4bfb4f6-51bd-4973-86fc-5d2339c4584a