Intelligent Analysis and Evaluation Method of Athletics Running Data Based on Big Data Statistical Model
To investigate the effectiveness of pedometry in athletics at different running speeds and on different walking surfaces, and to test whether it can be used for running for fitness and for pedometry on hardened concrete surfaces in daily life. The steps were measured under laboratory conditions usin...
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| Vydáno v: | Mathematical problems in engineering Ročník 2022; s. 1 - 8 |
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| Hlavní autor: | |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
New York
Hindawi
29.03.2022
John Wiley & Sons, Inc |
| Témata: | |
| ISSN: | 1024-123X, 1563-5147 |
| On-line přístup: | Získat plný text |
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| Abstract | To investigate the effectiveness of pedometry in athletics at different running speeds and on different walking surfaces, and to test whether it can be used for running for fitness and for pedometry on hardened concrete surfaces in daily life. The steps were measured under laboratory conditions using a running platform at 5 min at 5 speeds of 3.2 km/h, 4.8 km/h, 6.4 km/h, 8.0 km/h, and 9.6 km/h (actual steps were accurately determined by video playback), followed by 300 steps each at low, normal and fast speeds on an outdoor plastic athletics track. There were significant differences between the smart bracelet and the mobile phone sports app at low running speeds on four different surfaces: outdoor plastic track, dirt, concrete and mountainous terrain. The difference was not significant in normal pace and fast walking. |
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| AbstractList | To investigate the effectiveness of pedometry in athletics at different running speeds and on different walking surfaces, and to test whether it can be used for running for fitness and for pedometry on hardened concrete surfaces in daily life. The steps were measured under laboratory conditions using a running platform at 5 min at 5 speeds of 3.2 km/h, 4.8 km/h, 6.4 km/h, 8.0 km/h, and 9.6 km/h (actual steps were accurately determined by video playback), followed by 300 steps each at low, normal and fast speeds on an outdoor plastic athletics track. There were significant differences between the smart bracelet and the mobile phone sports app at low running speeds on four different surfaces: outdoor plastic track, dirt, concrete and mountainous terrain. The difference was not significant in normal pace and fast walking. |
| Author | Ge, Yushan |
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| Cites_doi | 10.1016/j.datak.2017.01.001 10.1016/j.jclepro.2018.02.129 10.1080/23270012.2016.1141332 10.1287/isre.2014.0546 10.1109/access.2014.2332453 10.24840/2183-0606_004.001_0003 10.1007/s11227-017-2222-4 10.1109/access.2018.2806881 10.17705/1cais.03623 10.2481/dsj.14-041 10.1561/1500000033 10.1186/s40064-016-3108-2 10.1080/02640414.2018.1521769 10.1007/s40595-013-0001-6 10.1016/j.future.2018.08.003 10.1111/1467-8551.12340 10.17705/1jais.00423 10.1016/j.tourman.2018.03.009 |
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| Copyright | Copyright © 2022 Yushan Ge. Copyright © 2022 Yushan Ge. This is an open access article distributed under the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. https://creativecommons.org/licenses/by/4.0 |
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| SubjectTerms | Accuracy Algorithms Big Data Exercise Physical fitness Running Sensors Smartphones Social research Sports Statistical models Walking |
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| Title | Intelligent Analysis and Evaluation Method of Athletics Running Data Based on Big Data Statistical Model |
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