高爾夫揮桿動作電腦化學習系統雛形之建構

Translated title of the contribution: A Preliminary Model of the Computer-Based Instructional System for Golf Swing

賀 育民(Yu-Min Ho), 莊 翰伯(Han-Bo Zhuang), Hsiang-Ho Chen

Research output: Contribution to journalArticle

Abstract

Over the years, golf has been a popular competitive sport and recreational pastime in the wor1d. Along with these jumps in technology, researchers have contributed to the basic understanding of how a proper swing is orchestrated and how this swing may be altered to either enhance or hamper performance. The purpose of this study is to collect professional golfers', kinematics during their golf swing. Using the technique of neural network is hoped to identify the motion pattern of golf swing. This study developed a computer-aided learning interface, there were twelve input nodes in the input layer, including anthropometric variables, club type and club speed. It can predict an optimal posture and show your learning strategy individually. This preliminary system might provide beginners a basic model to improve their learning for swing
Original languageTraditional Chinese
Pages (from-to)25-30
Number of pages6
Journal人因工程學刊
Volume7
Issue number1
Publication statusPublished - 2005

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Sports
Interfaces (computer)
Kinematics
Neural networks

Cite this

賀育民(Yu-Min H, 莊翰伯(Han-Bo Z, & Chen, H-H. (2005). 高爾夫揮桿動作電腦化學習系統雛形之建構. 人因工程學刊, 7(1), 25-30.

高爾夫揮桿動作電腦化學習系統雛形之建構. / 賀育民(Yu-Min Ho); 莊翰伯(Han-Bo Zhuang); Chen, Hsiang-Ho.

In: 人因工程學刊, Vol. 7, No. 1, 2005, p. 25-30.

Research output: Contribution to journalArticle

賀育民(Yu-MinH, 莊翰伯(Han-BoZ & Chen, H-H 2005, '高爾夫揮桿動作電腦化學習系統雛形之建構', 人因工程學刊, vol. 7, no. 1, pp. 25-30.
賀育民(Yu-MinH, 莊翰伯(Han-BoZ, Chen H-H. 高爾夫揮桿動作電腦化學習系統雛形之建構. 人因工程學刊. 2005;7(1):25-30.
賀育民(Yu-Min Ho) ; 莊翰伯(Han-Bo Zhuang) ; Chen, Hsiang-Ho. / 高爾夫揮桿動作電腦化學習系統雛形之建構. In: 人因工程學刊. 2005 ; Vol. 7, No. 1. pp. 25-30.
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abstract = "高爾夫球運動近年來在世界各地已經發展成爲熱門的休閒活動,有許多針對基本揮桿知識及單一選手揮桿動作之研究。爲提供一科學性的訓練方式,使學習者的動作能協調正確,因此本研究發展-高爾夫電腦輔助學習系統,以類神經倒傳遞網路爲基礎,預測在不同的球桿、桿速與人體測計值條件下各關節最適角度,並設計一教學介面程式,使初學者能透過此介面輸入自身的變數,預測自己的關節角度與搜尋最佳的揮桿學習策略,藉自觀察動畫強化其認知學習效果。",
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KW - 高爾夫

KW - 動作分析

KW - 類神經網路

KW - 電腦輔助學習

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KW - motion analysis

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