体育科学中的机器学习：挑战与机遇。

IF 2 3区医学 Q3 ENGINEERING, BIOMEDICAL

Sports Biomechanics Pub Date : 2024-08-01 Epub Date: 2021-04-20 DOI:10.1080/14763141.2021.1910334

Chris Richter, Martin O'Reilly, Eamonn Delahunt

引用次数: 0

摘要

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Machine learning in sports science: challenges and opportunities.

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来源期刊

Sports Biomechanics 医学-工程：生物医学

CiteScore

5.70

自引率

9.10%

发文量

135

审稿时长

>12 weeks

期刊介绍： Sports Biomechanics is the Thomson Reuters listed scientific journal of the International Society of Biomechanics in Sports (ISBS). The journal sets out to generate knowledge to improve human performance and reduce the incidence of injury, and to communicate this knowledge to scientists, coaches, clinicians, teachers, and participants. The target performance realms include not only the conventional areas of sports and exercise, but also fundamental motor skills and other highly specialized human movements such as dance (both sport and artistic). Sports Biomechanics is unique in its emphasis on a broad biomechanical spectrum of human performance including, but not limited to, technique, skill acquisition, training, strength and conditioning, exercise, coaching, teaching, equipment, modeling and simulation, measurement, and injury prevention and rehabilitation. As well as maintaining scientific rigour, there is a strong editorial emphasis on ''reader friendliness''. By emphasising the practical implications and applications of research, the journal seeks to benefit practitioners directly. Sports Biomechanics publishes papers in four sections: Original Research, Reviews, Teaching, and Methods and Theoretical Perspectives.