A Mathematical Model for the Take-Off in Platform Diving Article Swipe
Niklas Noth
,
Thomas Köthe
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.2478/hukin-2021-0097
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.2478/hukin-2021-0097
In platform diving the take-off phase is of outstanding importance in order to achieve both a high level of performing quality and a high degree of difficulty. The diver has to produce the right forces and direction of the center of mass (COM) in order to attain the required angular momentum and dive height. To support the development of an optimum take-off technique, the Institute for Applied Training Science designed a dryland measuring and feedback system. Using the example of the dive back 1¼ somersault tucked in preparation for the dive back 3½ somersault tucked (207 C) from the 10-m-platform, kinematic and kinetic reference values for key positions were determined. Therefore, we developed a mathematical model using a multi-step examination plan with the following parts: (1) variables defined using nonparametric correlation analyses rs of the motion parameters, (2) statistical modelling to predict values of the parameters, (3) stochastic modelling. The model is based on a selection of 18 dives from 10 different elite divers of the German Swimming Federation (DSV). The approach presented provides helpful insights into the mechanisms of an optimal take-off, enables a target-performance comparison with objective motion parameters and therefore, enables individualized feedback to guide the training process more efficiently.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.2478/hukin-2021-0097
- OA Status
- diamond
- References
- 20
- Related Works
- 10
- OpenAlex ID
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Raw OpenAlex JSON
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https://openalex.org/W3216917576Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.2478/hukin-2021-0097Digital Object Identifier
- Title
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A Mathematical Model for the Take-Off in Platform DivingWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2021Year of publication
- Publication date
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2021-10-31Full publication date if available
- Authors
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Niklas Noth, Thomas KötheList of authors in order
- Landing page
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https://doi.org/10.2478/hukin-2021-0097Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
-
diamondOpen access status per OpenAlex
- OA URL
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https://doi.org/10.2478/hukin-2021-0097Direct OA link when available
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Computer science, Kinematics, Process (computing), Simulation, Motion (physics), Marine engineering, Operations research, Industrial engineering, Artificial intelligence, Mathematics, Engineering, Physics, Operating system, Classical mechanicsTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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20Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.diving | 2 |
| abstract_inverted_index.forces | 34 |
| abstract_inverted_index.motion | 135, 189 |
| abstract_inverted_index.parts: | 124 |
| abstract_inverted_index.tucked | 85, 94 |
| abstract_inverted_index.values | 104, 142 |
| abstract_inverted_index.Applied | 66 |
| abstract_inverted_index.Science | 68 |
| abstract_inverted_index.achieve | 13 |
| abstract_inverted_index.angular | 49 |
| abstract_inverted_index.defined | 127 |
| abstract_inverted_index.dryland | 71 |
| abstract_inverted_index.enables | 183, 193 |
| abstract_inverted_index.example | 78 |
| abstract_inverted_index.height. | 53 |
| abstract_inverted_index.helpful | 174 |
| abstract_inverted_index.kinetic | 102 |
| abstract_inverted_index.optimal | 181 |
| abstract_inverted_index.optimum | 60 |
| abstract_inverted_index.predict | 141 |
| abstract_inverted_index.process | 200 |
| abstract_inverted_index.produce | 31 |
| abstract_inverted_index.quality | 20 |
| abstract_inverted_index.support | 55 |
| abstract_inverted_index.system. | 75 |
| abstract_inverted_index.Swimming | 167 |
| abstract_inverted_index.Training | 67 |
| abstract_inverted_index.analyses | 131 |
| abstract_inverted_index.approach | 171 |
| abstract_inverted_index.designed | 69 |
| abstract_inverted_index.feedback | 74, 195 |
| abstract_inverted_index.insights | 175 |
| abstract_inverted_index.momentum | 50 |
| abstract_inverted_index.platform | 1 |
| abstract_inverted_index.provides | 173 |
| abstract_inverted_index.required | 48 |
| abstract_inverted_index.take-off | 4, 61 |
| abstract_inverted_index.training | 199 |
| abstract_inverted_index.Institute | 64 |
| abstract_inverted_index.developed | 112 |
| abstract_inverted_index.different | 161 |
| abstract_inverted_index.direction | 36 |
| abstract_inverted_index.following | 123 |
| abstract_inverted_index.kinematic | 100 |
| abstract_inverted_index.measuring | 72 |
| abstract_inverted_index.modelling | 139 |
| abstract_inverted_index.objective | 188 |
| abstract_inverted_index.positions | 107 |
| abstract_inverted_index.presented | 172 |
| abstract_inverted_index.reference | 103 |
| abstract_inverted_index.selection | 155 |
| abstract_inverted_index.take-off, | 182 |
| abstract_inverted_index.variables | 126 |
| abstract_inverted_index.Federation | 168 |
| abstract_inverted_index.Therefore, | 110 |
| abstract_inverted_index.comparison | 186 |
| abstract_inverted_index.importance | 9 |
| abstract_inverted_index.mechanisms | 178 |
| abstract_inverted_index.modelling. | 148 |
| abstract_inverted_index.multi-step | 118 |
| abstract_inverted_index.parameters | 190 |
| abstract_inverted_index.performing | 19 |
| abstract_inverted_index.somersault | 84, 93 |
| abstract_inverted_index.stochastic | 147 |
| abstract_inverted_index.technique, | 62 |
| abstract_inverted_index.therefore, | 192 |
| abstract_inverted_index.correlation | 130 |
| abstract_inverted_index.determined. | 109 |
| abstract_inverted_index.development | 57 |
| abstract_inverted_index.difficulty. | 26 |
| abstract_inverted_index.examination | 119 |
| abstract_inverted_index.outstanding | 8 |
| abstract_inverted_index.parameters, | 136, 145 |
| abstract_inverted_index.preparation | 87 |
| abstract_inverted_index.statistical | 138 |
| abstract_inverted_index.efficiently. | 202 |
| abstract_inverted_index.mathematical | 114 |
| abstract_inverted_index.nonparametric | 129 |
| abstract_inverted_index.10-m-platform, | 99 |
| abstract_inverted_index.individualized | 194 |
| abstract_inverted_index.target-performance | 185 |
| abstract_inverted_index.r<sub>s</sub> | 132 |
| cited_by_percentile_year | |
| corresponding_author_ids | https://openalex.org/A5026781756 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 2 |
| corresponding_institution_ids | https://openalex.org/I4210145753 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/14 |
| sustainable_development_goals[0].score | 0.8100000023841858 |
| sustainable_development_goals[0].display_name | Life below water |
| citation_normalized_percentile.value | 0.21646705 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |