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从大数据挖掘到体育技术报告:以惯性测量单元为例。

From big data mining to technical sport reports: the case of inertial measurement units.

作者信息

Rojas-Valverde Daniel, Gómez-Carmona Carlos D, Gutiérrez-Vargas Randall, Pino-Ortega Jose

机构信息

Centro de Investigación y Diagnóstico en Salud y Deporte, Escuela Ciencias del Movimiento Humano y Calidad de Vida, Universidad Nacional de Costa Rica, Heredia, Costa Rica.

Physical Activity and Sport Department, University of Extremadura, Caceres, Spain.

出版信息

BMJ Open Sport Exerc Med. 2019 Oct 1;5(1):e000565. doi: 10.1136/bmjsem-2019-000565. eCollection 2019.

Abstract

The inertial measurement units (IMU) are instruments used to quantify the external load of athletes; they are increasingly common in assessing team and individual sports. This type of instruments has several sensors, such as accelerometers, gyroscopes and magnetometers; this allows access to a large amount of information and analysis possibilities. Due to the complexity of synthesising this data, it is necessary to create a flow for collecting, analysing and presenting the collected data in a simple way and present it as quickly as possible to the technical staff. This report aims to present new methods of reduction of the data and propose a new approach method for the analysis of the IMU's outcomes.

摘要

惯性测量单元(IMU)是用于量化运动员外部负荷的仪器;它们在评估团队和个人运动中越来越普遍。这类仪器有多个传感器,如加速度计、陀螺仪和磁力计;这使得能够获取大量信息并提供多种分析可能性。由于合成这些数据的复杂性,有必要创建一个流程,以便以简单的方式收集、分析和呈现所收集的数据,并尽快将其呈现给技术人员。本报告旨在介绍新的数据简化方法,并提出一种分析IMU结果的新方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac76/6797247/7cb859d24091/bmjsem-2019-000565f01.jpg

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