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

Copyright © 2021 Ma, Chen, Hsu and Lai..

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.

Medienart:

E-Artikel

Erscheinungsjahr:

2021

Erschienen:

2021

Enthalten in:

Zur Gesamtaufnahme - volume:12

Enthalten in:

Frontiers in psychology - 12(2021) vom: 01., Seite 741805

Sprache:

Englisch

Beteiligte Personen:

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

Links:

Volltext

Themen:

Adaptive baseball learning
Computer visions
Journal Article
Machine learning
Pitch fatigue detection
Smart sports

Anmerkungen:

Date Revised 31.12.2021

published: Electronic-eCollection

Citation Status PubMed-not-MEDLINE

doi:

10.3389/fpsyg.2021.741805

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM335021328