手腕穿戴式智能分析器對不同差點大專高爾夫球選手一號木桿揮桿動作表現之評估

Wrist-worn smart analyzer to evaluate the driver's swing action of college golf players with different handicaps

10.6634/JPSS-CCU.202204_(34).0004

陳錦偉(Chin-Wei Chen)

分數 ； 上桿 ； 揮桿速度 ； 桿頭速度 ； score ； backswing ； swing speed ； head speed

文化體育學刊

34輯（2022 / 04 / 01）

73 - 85

繁體中文

目的：本研究旨意為利用手腕穿載式智能分析器（Zepp）產生的數據，對不同差點大專高爾夫球選手揮桿動作的表現，作即早檢測修正揮桿動作的釐清與評估。方法：研究徵召13名男性大專選手，分為高差點組（6-10; n=7）及低差點組（0-5; n=6）等二種組別。各受試者在靜態立位站姿情境下，接受連續10次木桿的揮桿，並以10次成績的平均值，作為揮桿的紀錄。受試者手腕穿載高爾夫智能分析器，與智慧型平版電腦同步，進行整體表現分數與各項指標項目的數據分析。獲得資料，以SPSS 14.0描述統計彙整，進行獨立t檢定考驗兩組間的各項差異，及以多元逐步回歸模式預測不同差點選手，整體表現分數之揮桿代表性項目。結果：低差點組在整體表現分數、上桿角度及手腕速度的值，顯著優於高差點組。高差點組與低差點組，在回歸模式預測中，被選入的有上桿角度與手腕速度等二項代表性項目，都有顯著的解釋力。結論：本研究使用手腕穿載式高爾夫智能分析器，有效檢證不同差點選手擊球時揮桿動作的指標差異。藉由穿載智能分析器的感應對揮桿動作量測所呈現的表現，可以提升與間接轉換作為高爾夫球選手及愛好者，揮桿動作時的即時回饋參考。

Purpose: The purpose of this study was to use data generated by a wrist-worn smart analyzer (Zepp) to clarify and evaluate the swing action of college golf players with different handicaps and to identify early swing patterns. Methods: Thirteen male college athletes were recruited for the study and divided into two groups: the high handicap group (6-10; n=7) and the low handicap group (0-5; n=6). Each trial participant had the opportunity to perform 10 consecutive swings with a wood (wooden club) in a static standing posture, and the average of the 10 swings was used as the record of the swing. All the subjects wore a golf smart analyzer on their wrists, which were synchronized with a smart tablet computer to analyze overall performance scores and data for each metric item. The data was compiled using SPSS 14.0 descriptive statistics, and independent sample t-tests were conducted to test the differences between the two groups. A multiple stepwise regression model was used to predict the overall performance items of golfers with different handicaps. Results: The overall performance scores, backswing angle, and wrist speed of the low handicap group were significantly better than those of the high handicap group. In the regression prediction model, the two representative variables of backswing angle and wrist speed were selected for both the high and low handicap groups, and both had significant explanatory abilities. Conclusion: This study used a wrist-worn golf smart analyzer to effectively validate the difference in swing mechanics of golfers, with different handicaps, when they hit the ball. The performance of the swing measurement, by the induction sensing of the wearable smart analyzer, can be enhanced and indirectly transformed to serve as an instant feedback reference for golfers and enthusiasts during their golf swings.

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