Title: iGolf : 一個基於體感網路與雲端服務之高爾夫球揮桿學習系統
iGolf : A BSN-based and Cloud-Assisted Golf Swing Training System
Authors: 黃怡箴
Huang, Yi-Chen
Yi, Chih-Wei
Keywords: 高爾夫;體感網路;慣性感測元件;運動學習;golf;body sensor network;IMU;sport learning
Issue Date: 2013
Abstract: 在運動學習的過程中,養成正確的姿勢得以達到最佳的學習效果並避免運動傷害,但若未能及時發現姿勢的錯誤,將付出更多的時間及代價來校正於無形中養成的壞習慣。以高爾夫運動為例,球友往往容易被錯誤的肢體動作影響了擊球結果,在金錢考量上,也不是每位球友都可以負荷聘請教練的花費;因此在此以高爾夫揮桿的學習為例,提出一個基於體感測網路技術與雲端服務的系統,本論文中將慣性感測元件依附於身體部位如腰、手腕,以及高爾夫球桿桿頭上,在建構好的體感測網路環境中收集使用者的揮桿感測資訊,將分析感測資訊的動作作為雲端服務之一,進行資料處理,最後本系統將提供球具軌跡偵測、揮桿狀態如揮桿速度、揮桿節奏等資訊,甚至該次揮桿的改善建議,輔助初學者的高爾夫球揮桿訓練。
In the process of sport learning, learners spend a lot of time on practicing in order to develop correct action habit. Take golf practice as an example. Without the supervising of coaches, novices may keep practicing wrong swing actions, and that will cost more time later on to correct the wrong habit. It would be helpful to let learners can be aware of incorrect swing actions in self-training. In this work, we propose an IMU-based solution to help learners by allowing them to review their swing trajectories and also learn key features of the swings. In the proposed system, we build a BSN-based environment and there are IMUs composed of an accelerometer, a magnetometer and a gyroscope used and attached on the human body like wrist and waist, and also installed on the golf club to collect inertial motion data. We give the algorithm as cloud services to processing the collected data thus that swing trajectories can be calculated and more swing features can also be extracted to assist learning process of golfers.
Appears in Collections:Thesis

Files in This Item:

  1. 653301.pdf