摘 要 本研究目的是建立不同等級划船選手的動作軌跡資料庫,依據此資料庫建立判別不同划船技術等級之方法。對象為我國大專代表隊、曾入選國家代表隊與榮獲國際獎牌之大專選手共48名(身高體174.81±7.48公分、體重69.44±10.29公斤、年齡22.39±1.72歲)。利用影像分析系統與ConceptⅡ划船器模擬系統分析選手划船動作,設定攝影機快門為1/500、攝影機擷取頻率為30Hz、拍攝距離為15公尺,ConceptⅡ槳頻為30-31(次/min)、阻力為第五等級、划船距離為500公尺。以Motus7.0動作分析軟體數位化與擷取身體各個關節點(包含頭部、肩關節、肘關節、腕關節、握柄、髖關節、膝關節、踝關節、腳尖與座椅等十一個標誌點)運動學參數座標資料,並透過王金成(民88年)建立之人體肢段慣性資料計算身體重心位置與肢段角度(相對與絕對髖關節角度、膝關節角度、踝關節角度與身體重心角度)。再以傅立葉分析方法計算與儲存傅立葉係數資料,經過SPSS統計考驗得到能鑑別技術等級的有效傅立葉參數與建立迴歸預測模式。 結果顯示:透過握柄位移第一係數(H1)、握柄位移第二係數(H2)、腕關節位移第二係數(W2)、膝關節位移第二係數(K2)、重心位移第二係數(M2)、相對髖關節角度位移第三係數(RH3)等有效傅立葉係數參數與進行多元逐步迴歸分析所得之迴歸預測模式:D=2.210 - 1.071H1 - 2.279 H2 - 5.630 W2 +15.335 K2 +7.907 M2 +0.08025RH3,可以判定划船技術表現之等級。 關鍵詞:生物力學、划船、傅立葉級數、等級、技術
ABSTRACT The purpose of the study was to establish the data of motion in different degree college rower. According to the data to establish the regression model that will be applied to assess different degree of rowing technique. In the experiment, bjects (includes collage’s students, players of ROC, players who obtain medals of world’s games) are forty-eight rowers who are age 22.39±1.72 years old, weight 60.44±10.29 Kilos, height 178.81±7.48 cm. The study analyze the motion of rowers in the ConceptⅡ by motion analysis systems and ConceptⅡ rowing systems. We set the of the video camera Shutter speed is 1/500, the frames speed is 30Hz, and the distance from camera to rowers is 15 meters, the stroke of the ConceptⅡ is set 30-31 times for one minute, and the air resistance is set on the level of 5, the rowing distance is 500 meters. The eleven body landmarks (includes head, shoulder, elbow, wrist, oar, hip, knee, ankle, heel, toe and chair) were digitized with the software of the Peak Motus 7.0,and the and body center of mass were estimated by using the Jin-cherng Wang data (1999), and the data of Fourier number were got through the Fourier series analysis. SPSS is tryout the efficient parameters and establish forecast model, and then we could authenticate the degree of the rowers. The results of study show that we could use the efficient parameters [includes the Hand of first number (H1), Hand of second number (H2), wrist of second number (W2), knee of second number (K2), gravity of second number (M2), relative angle 0f hip joint third number (RH3)] and stepwise regression model (D=2.210 - 1.071H1 - 2.279 H2 - 5.630 W2 + 15.335 K2 + 7.907 M2 + 0.08025RH3) to predicate the degree of rowing technique for the collage’s students in Taiwan. Key words:Biomechanics, Rowing, Fourier series, Degree, Technique.