The accuracy of measuring velocity during weightlifting movements with five velocity-based training devices

同心的 培训(气象学) 模拟 职位(财务) 线性回归 计算机科学 统计 数学 物理医学与康复 物理 医学 气象学 几何学 财务 经济
作者
Sergio A. Lemus,Mallory Volz,Avery Blasdale,F. J. Beron‐Vera,Cheng‐Bang Chen,Bryan J. Mann,Francesco Travascio
出处
期刊:International Journal of Sports Science & Coaching [SAGE Publishing]
卷期号:19 (6): 2501-2512 被引量:1
标识
DOI:10.1177/17479541241266248
摘要

The use of weightlifting exercises is prevalent in competitive and recreational environments, as well as sport-specific training. Traditionally, weightlifting coaches prescribe specific training loads based on an individual's maximal ability. Velocity-based training offers an alternative method that promises to quantify strength based on velocity and provides information that increases competitiveness through real-time feedback. Various velocity measurement devices are available on the market. Their precision is critical for the adequate implementation of velocity-based training. The aim of the present study was to compare the concentric peak velocity measurements of five of these devices during two weightlifting movements, the snatch and clean, to data collected with a 12-camera motion capture system, which was considered as gold standard. It was hypothesized that the velocity measurement devices used in this study would vary in accuracy based on their retail prices. Velocity readings associated with light and moderate (40% and 70% of one-repetition max) loads were measured for both the snatch and clean performed by 12 competitive weightlifters. A least products regression was used to assess validity by comparing five devices against a criterion measure. A general linear model showed statistical differences in the velocities measured with these five devices ( p < 0.001). Specifically, the GymAware RS linear position transducer was the most accurate device, demonstrating no fixed or proportional bias when used to quantify velocity during the snatch and clean. The remaining four devices significantly underestimated peak velocity, which would directly impact the daily planning of lifters’ training. Practitioners must consider the error and bias of each device before implementing velocity-based training.
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
小丸子博士完成签到 ,获得积分10
刚刚
科研完成签到 ,获得积分10
2秒前
独孤磕盐完成签到,获得积分10
2秒前
Focus完成签到,获得积分20
2秒前
爱喝饮料的刺猬完成签到,获得积分10
5秒前
Guo完成签到,获得积分10
6秒前
阿龙完成签到,获得积分10
7秒前
勤奋完成签到 ,获得积分10
7秒前
Linnaeus完成签到,获得积分10
8秒前
六六发布了新的文献求助20
8秒前
MrRaBB完成签到 ,获得积分10
9秒前
Jasper应助科研通管家采纳,获得10
10秒前
10秒前
章鱼小丸子完成签到 ,获得积分10
11秒前
xiaofenzi完成签到,获得积分10
11秒前
11秒前
13秒前
15秒前
ccx完成签到,获得积分10
15秒前
LHL完成签到,获得积分10
15秒前
晨光完成签到,获得积分10
16秒前
bingbing完成签到,获得积分10
16秒前
今天要早睡完成签到,获得积分10
16秒前
研值爆表完成签到,获得积分10
17秒前
杜嘟嘟完成签到,获得积分10
17秒前
苏逸完成签到,获得积分10
19秒前
轻松盼山完成签到 ,获得积分10
20秒前
zzzzz完成签到,获得积分10
20秒前
123...完成签到,获得积分10
20秒前
苦哈哈完成签到,获得积分0
22秒前
乐空思应助晨光采纳,获得60
22秒前
福林古斯完成签到 ,获得积分10
23秒前
西红柿完成签到,获得积分10
24秒前
LYCc_完成签到 ,获得积分10
25秒前
狂跳的脉搏完成签到,获得积分10
25秒前
Jam完成签到,获得积分10
26秒前
椰子完成签到,获得积分10
27秒前
月月完成签到,获得积分10
27秒前
红雨灰衣完成签到,获得积分10
27秒前
小七2022完成签到,获得积分10
28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
Rosenblum, Global Change Biology 800
自動車の空力技術 800
Essentials of Carbohydrate Chemistry and Biochemistry, 4th Edition 800
Organizational Behavior 510
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
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 化学工程 工程类 有机化学 物理 复合材料 生物化学 内科学 细胞生物学 基因 遗传学 免疫学 冶金 光电子学 癌症研究
热门帖子
关注 科研通微信公众号,转发送积分 7778504
求助须知:如何正确求助?哪些是违规求助? 9318853
关于积分的说明 20366411
捐赠科研通 7365581
什么是DOI,文献DOI怎么找? 3319214
关于科研通互助平台的介绍 2467181
邀请新用户注册赠送积分活动 2334693