Suppr超能文献

量化跑步暴露量以获得与跑步相关损伤的有意义见解。

Quantifying exposure to running for meaningful insights into running-related injuries.

作者信息

Davis Iv John J, Gruber Allison H

机构信息

Department of Kinesiology, School of Public Health, Indiana University, Bloomington, Indiana, USA.

出版信息

BMJ Open Sport Exerc Med. 2019 Oct 13;5(1):e000613. doi: 10.1136/bmjsem-2019-000613. eCollection 2019.

Abstract

The very term 'running-related overuse injury' implies the importance of 'use', or exposure, to running. Risk factors for running-related injury can be better understood when exposure to running is quantified using either external or internal training loads. The advent of objective methods for quantifying exposure to running, such as global positioning system watches, smartphones, commercial activity monitors and research-grade wearable sensors, make it possible for researchers, coaches and clinicians to track exposure to running with unprecedented detail. This viewpoint discusses practical issues surrounding the use and analysis of data from such devices, including how wearable devices can be used to assess both internal and external training loads. We advocate for an integrative approach where data from multiple sources are used in combination to directly measure exposure to running in diverse settings.

摘要

“跑步相关过度使用损伤”这一术语本身就意味着“使用”或接触跑步的重要性。当使用外部或内部训练负荷来量化接触跑步的程度时,与跑步相关损伤的风险因素就能得到更好的理解。诸如全球定位系统手表、智能手机、商业活动监测器和研究级可穿戴传感器等用于量化接触跑步程度的客观方法的出现,使得研究人员、教练和临床医生能够以前所未有的详细程度追踪接触跑步的情况。本文观点讨论了围绕此类设备数据的使用和分析的实际问题,包括可穿戴设备如何用于评估内部和外部训练负荷。我们提倡一种综合方法,即结合使用来自多个来源的数据,以直接测量在不同环境下接触跑步的程度。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cffc/6797407/7dd32d1e19b2/bmjsem-2019-000613f01.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验