Design and Analysis of a Pitch Fatigue Detection System for Adaptive Baseball Learning.

Yi-Wei Ma, Jiann-Liang Chen, Chia-Chi Hsu, Ying-Hsun Lai

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Article in Frontiers in psychology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 authors.

Yi-Wei MaDepartment of Electrical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan.

Jiann-Liang ChenDepartment of Electrical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan.

Chia-Chi HsuDepartment of Electrical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan.

Ying-Hsun LaiDepartment of Computer Science and Information Engineering, National Taitung University, Taitung, Taiwan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Owing to the rapid development of information and communication technologies, such as the Internet of Things, artificial intelligence, and computer vision, in recent years, the concept of smart sports has been proposed. A pitch fatigue detection method that includes acquisition, analysis, quantification, aggregation, learning, and public layers for adaptive baseball learning is proposed herein. The learning determines the fatigue index of the pitcher based on the angle of the pitcher's elbow and back as the number of pitches increases. The coach uses this auxiliary information to avoid baseball injuries during baseball learning. Results show a test accuracy rate of 89.1%, indicating that the proposed method effectively provides reference information for adaptive baseball learning.

Indexed as

adaptive baseball learningcomputer visionsmachine learningpitch fatigue detectionsmart sports

Identifiers

PMID34966320

DOI10.3389/fpsyg.2021.741805

PMCPMC8711585

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.