Energetic Parameters of Rowing Performance: Will the Distance Change in the 2028 Los Angeles Olympic Games Matter?

赛艇 冲刺 灵敏度(控制系统) 数学 模拟 动物科学 物理医学与康复 计算机科学 地理 医学 统计 物理疗法 生物 工程类 电子工程 考古
作者
Alice Boillet,Laurent A. Messonnier,Caroline Cohen
出处
期刊:Medicine and Science in Sports and Exercise [Lippincott Williams & Wilkins]
卷期号:57 (10): 2294-2306 被引量:2
标识
DOI:10.1249/mss.0000000000003759
摘要

PURPOSE: The study aimed to model rowing in a single scull, considering individual physiological characteristics of rowers, to determine the optimal pacing strategy over 2000 m (current Olympic distance) and 1500 m (future Olympic distance for 2028), as well as the sensitivity of performance to specific physiological factors at these distances. METHODS: A validated mechanical model of rowing was coupled with an athlete-specific physiological model (digital twin) to determine optimal pacing strategies for two model athletes (a female and a male rower). Energy production was analyzed using both oxidative ( ) and non-oxidative ( Enon - ox ) sources, using numerical and analytical approaches. RESULTS: For the 2000-m distance, the optimal pacing strategy involved a gradual deceleration over the first 1500 m, followed by a final sprint over the last 500 m, similar to current observed trends. For the 1500-m distance, the optimal pacing strategy lacked this final sprint. Reducing the distance increased the proportion of non-oxidative energy by 5%. Sensitivity of performance to was consistent across both distances, showing a 1% performance gain for every 3% increase in . In contrast, the sensitivity of Enon - ox increased as distance decreased (a 1% performance gain requiring an 11% increase for 2000 m vs a 13% increase for 1500 m in non-oxidative capacity). CONCLUSIONS: Optimal pacing strategies differ between 2000 and 1500 m, with the latter requiring a less even pace with a faster start and without a final sprint. Sensitivity to is consistently higher than that of Enon - ox at both distances, highlighting the critical role of oxidative capacity in rowing performance.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
wealthdxy发布了新的文献求助10
刚刚
armen完成签到,获得积分10
刚刚
NillKiggers228完成签到,获得积分10
1秒前
Akim的应助被专一的访卉采纳,获得10
2秒前
小二郎的应助被好久不见采纳,获得10
3秒前
kopp发布了新的文献求助30
3秒前
3秒前
科研通AI2S的应助被洁净雨采纳,获得10
6秒前
传奇3的应助被淡定的银耳汤采纳,获得10
7秒前
皮皮宁发布了新的文献求助10
8秒前
guxi发布了新的文献求助30
10秒前
狂灵与安卓95完成签到 ,获得积分10
10秒前
英姑的应助被tim采纳,获得10
11秒前
深情安青的应助被心落失采纳,获得10
11秒前
special的应助被沉静蛟凤采纳,获得10
12秒前
weiwei发布了新的文献求助20
14秒前
14秒前
14秒前
15秒前
16秒前
打打的应助被HH采纳,获得10
16秒前
小朱完成签到 ,获得积分10
16秒前
17秒前
舒适沛珊完成签到 ,获得积分10
18秒前
lucky完成签到 ,获得积分10
18秒前
友好的中蓝完成签到,获得积分10
18秒前
zzw发布了新的文献求助30
18秒前
慕青的应助被沉静蛟凤采纳,获得10
19秒前
19秒前
20秒前
天天快乐的应助被GAP采纳,获得10
20秒前
四旬完成签到,获得积分10
20秒前
怡宝发布了新的文献求助10
21秒前
zx完成签到,获得积分10
21秒前
急着青春完成签到,获得积分10
21秒前
21秒前
22秒前
科研通AI6.4的应助被kopp采纳,获得10
22秒前
科研通AI6.2的应助被kopp采纳,获得10
22秒前
22秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Linear Model and Extensions 5000
Essentials of Carbohydrate Chemistry and Biochemistry, 4th Edition 1000
Электротехническая система магнитожидкостной герметизации валов регулируемых электродвигателей 800
Holistic Discourse Analysis, Second Edition by Robert E. Longacre 666
Guidelines for fracture-safe and fatigue-reliable design of steel structures 600
The Basics of Practical Optimization, Second Edition 600
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 计算机科学 工程类 有机化学 化学工程 生物化学 物理 复合材料 内科学 催化作用 光电子学 人工智能 细胞生物学 无机化学 物理化学 数学
热门帖子
关注 科研通微信公众号,转发送积分 7983374
求助须知:如何正确求助?哪些是违规求助? 9443654
关于积分的说明 21087072
捐赠科研通 7558216
什么是DOI,文献DOI怎么找? 3376505
关于科研通互助平台的介绍 2510685
邀请新用户注册赠送积分活动 2409716