• 제목/요약/키워드: Golf Swing

검색결과 152건 처리시간 0.025초

엘리트 골프 선수의 드라이버 스윙 시 스윙 평면 분석 (The Analysis of Swing Plane of Elite Golfers During Drive Swing)

  • 임영태
    • 한국운동역학회지
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    • 제19권1호
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    • pp.59-66
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    • 2009
  • 본 연구의 목적은 국내 엘리트 골프선수들을 대상으로 3차원 스윙 평면 분석(swing plane analysis)을 통해 스윙 평면의 편평도를 확인하여 이들 스윙이 어떤 유형의 스윙인지를 확인하는 것이 목적이었다. 또한 편평도를 이용한 스윙평면 분석 이외에 또 다른 운동학적 변인을 이용한 스윙 평면 분류가 가능한지도 확인하였다. 그 결과 편평도와 핸디캡간의 상관성은 없는 것으로 판명되었고 단일 및 다중 평면 스윙 그룹간의 편평도 비교를 실시한 결과 유의한 차이를 확인할 수가 있었다. 두 스윙 그룹을 구분하는 대표적인 특징인 백스윙 및 팔로우드로우에서의 스윙 궤도차이를 확인하기 위해 실시한 두 스윙 그룹 간 event 별 편평도 비교에서 그 유의한 차이를 확인함으로서 본 연구에서 정의한 오차범위 10cm는 두 스윙 스타일을 구분하는데 유효한 것으로 확인이 되었다. 편평도를 이용한 스윙평면 분석 이외에 운동학적 변인인 두 스윙 그룹 간 샤프트 단위벡터 비교와 샤프트 원위점 변위 비교를 event 별로 실시한 결과 통계적으로 유의한 차이는 확인이 되지 않았다. 하지만 전체적인 변인들의 이동패턴을 살펴 볼 때 각각의 스윙 그룹의 특징을 잘 보여주고 있기 때문에 스윙 스타일을 판단하는 간접적인 지표가 될 가능성을 보여주었다.

퍼지 시스템을 이용한 골프 스윙 분류 (Golf Swing Classification Using Fuzzy System)

  • 박준욱;곽수영
    • 방송공학회논문지
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    • 제18권3호
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    • pp.380-392
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    • 2013
  • 본 논문에서는 키넥트와 퍼지 시스템을 이용하여 골프 스윙 동작을 7가지 구간으로 분류하는 방법을 제안한다. 퍼지 논리의 입력으로 골프 클럽과 클럽의 헤드 위치를 사용하였으며 이 정보는 키넥트로부터 획득한 골퍼의 관절 정보와 컬러 영상 정보로부터 검출하였다. 제안하는 방법은 크게 신체 관절 추출 모듈, 골프 클럽 검출 및 헤드 추적 모듈, 골프 스윙 동작 분류 모듈로 구성되어 있다. 신체 관절 추출 모듈은 키넥트 센서로부터 검출되는 신체 관절 정보 중 골프 클럽의 검출을 위해 손의 좌표를 추출한다. 두 번째 모듈에서는 손의 좌표를 기준으로 허프 직선 변환 알고리즘을 사용하여 골프 클럽과 골프 클럽의 헤드를 검출한다. 마지막으로 인식 오류를 줄이고 동작별 인식 성능을 향상시키기 위해 퍼지 시스템을 적용하여 골프 스윙 동작을 분류하였다. 실시간 골프 스윙 영상에 대해 제안한 방법의 성능 평가를 시행하였고 제안한 방법은 평균 85.2%의 골프 스윙 동작 분류 신뢰도를 보여줌을 확인하였다.

Comparison of Three Normalization Methods for 3D Joint Moment in the Asymmetric Rotational Human Movements in Golf Swing Analysis

  • Lee, Dongjune;Oh, Seung Eel;Lee, In-Kwang;Sim, Taeyong;Joo, Su-bin;Park, Hyun-Joon;Mun, Joung Hwan
    • Journal of Biosystems Engineering
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    • 제40권3호
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    • pp.289-295
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    • 2015
  • Purpose: From the perspective of biomechanics, joint moments quantitatively show a subject's ability to perform actions. In this study, the effect of normalization in the fast and asymmetric motions of a golf swing was investigated by applying three different normalization methods to the raw joint moment. Methods: The study included 13 subjects with no previous history of musculoskeletal diseases. Golf swing analyses were performed with six infrared cameras and two force plates. The majority of the raw peak joint moments showed a significant correlation at p < 0.05. Additionally, the resulting effects after applying body weight (BW), body weight multiplied by height (BWH), and body weight multiplied by leg length (BWL) normalization methods were analyzed through correlation and regression analysis. Results: The BW, BWH, and BWL normalization methods normalized 8, 10, and 11 peak joint moments out of 18, respectively. The best method for normalizing the golf swing was found to be the BWL method, which showed significant statistical differences. Several raw peak joint moments showed no significant correlation with measured anthropometrics, which was considered to be related to the muscle coordination that occurs in the swing of skilled professional golfers. Conclusions: The results of this study show that the BWL normalization method can effectively remove differences due to physical characteristics in the golf swing analysis.

골프스윙오류의 운동역학적 분류 (Kinetic Classification of Golf Swing Error)

  • 전철우;황인승;임정
    • 한국운동역학회지
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    • 제16권4호
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    • pp.95-103
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    • 2006
  • The purpose of this study was to review the relevant literature about coaching and thereupon, survey the coaching methods used for golf lesson to reinterpret them and thereby, describe in view of kinetics the swing errors committed frequently by amateur golfers and suggest more scientific golf coaching methods. For this purpose, kinetic elements were divided into accuracy and power ones and therewith, the variables affecting such elements were identified. For this study, a total of 60 amateur golfer were sampled, and their swing forms were photographed with two high-speed digital cameras, and the resultant images were analyzed to determine the errors of each form kinetically, which would be analyzed again with the program V1-5000. The kinetic elements could be identified as accuracy, power and accuracy & power. Thus, setup and trajectory were classified into accuracy elements, while differences of inter-joint angles, cocking and delayed hitting. Lastly, timing and axial movement were classified into accuracy & power elements. Three errors were identified in association with setup. The errors related with trajectory elements accounted for most (6) of the 20 errors. Three errors were determined for inter-joint angle differences, and one error was associated with cocking and delayed hitting. Lastly, one error was classified into timing error, while five errors were associated with axial movement. Finally, as a result of arranging the errors into a cross table, it was found that the errors were associated with each other between take-back and back-swing, take-back and follow-through, back-swing and back-swing top, and between back-swing and down-swing. Namely, an error would lead to other error repeatedly. So, it is more effective to identify all the errors for every form and correct them comprehensively rather than single out the errors and correct them one by one.

골프스윙시 인공지능 을 이용한 (Neural Network) 슬라이스 예측에 관한 연구 (The Prediction of &apos;Slice&apos; Using Neural Network in Golf Swing)

  • 심태용;오승일;신성휴;이상식;문정환
    • 한국정밀공학회:학술대회논문집
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    • 한국정밀공학회 2004년도 추계학술대회 논문집
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    • pp.1221-1224
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    • 2004
  • In this study, we developed a method classifying slice shot during golf practice using backpropagation algorithm. The 144 data based on the backpropagation model(11 inputs, 2 outputs) was used as a learning set and the model was verified based on the extra 50 data in the process to predict a slice shot in golf swing. The results showed 100% separating rate of learning set and 91.5% separating rate of verified set. The developed method can be potentially beneficial for the predicting of slice shot in an indoor golf excercise setting without applying any additional equipment.

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Effects of real-time feedback training on weight shifting during golf swinging on golf performance in amateur golfers

  • Hwang, Ji-Hyun;Choi, Ho-Suk;Shin, Won-Seob
    • Physical Therapy Rehabilitation Science
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    • 제6권4호
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    • pp.189-195
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    • 2017
  • Objective: The purpose of this study was to examine the effects of real-time visual feedback weight shift training during golf swinging on golf performance. Design: Repeated-measures crossover design. Methods: Twenty-sixth amateur golfers were enrolled and randomly divided into two groups: The golf swing training with real-time feedback on weight shift (experimental group) swing training on the Wii balance board (WBB) by viewing the center of pressure (COP) trajectory on the WBB. All participants were assigned to the experimental group and the control group. The general golf swing training group (control group) performed on the ground. The golf performance was measured using a high-speed 3-dimensional camera sensor which analyses the shot distance, ball velocity, vertical launch angle, horizontal launch angle, back spin velocity and side spin velocity. The COP trajectory was assessed during 10 practice sessions and the mean was used. The golf performance measurement was repeated three times and its mean value was used. The assessment and training were performed at 24-hour intervals. Results: After training sessions, the change in shot distance, ball velocity, and horizontal launch angle pre- and post-training were significantly different when using the driver and iron clubs in the experimental group (p<0.05). The interaction time${\times}$group and time${\times}$club were not significant for all variables. Conclusions: In this study, real-time feedback training using real-time feedback on weight shifting improves golf shot distance and accuracy, which will be effective in increasing golf performance. In addition, it can be used as an index for golf player ability.

그립압력과 중심이동이 골프 스윙에 미치는 영향 (Effect of grip pressure and center of gravity on golf swing)

  • 이근춘;송대찬;박종대;조장호
    • 자연과학논문집
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    • 제13권1호
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    • pp.25-33
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    • 2003
  • 골프 스윙동안 그립의 압력과 중심이동을 관측하기 위하여 실험장치를 만들었다. 측정된 그립압력과 중심이동은 안정된 프로 골퍼의 스윙자세에서 일정한 형태를 보이나 스윙이 불안한 프로의 스윙에서는 불규칙한 결과를 얻었다.

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단일 키넥트를 이용한 골프 스윙 특징의 자동 추출 (Automatic extraction of golf swing features using a single Kinect)

  • 김병기
    • 한국컴퓨터정보학회논문지
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    • 제19권12호
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    • pp.197-207
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    • 2014
  • 본 논문에서는 실용적인 TOF 카메라인 키넥트(Kinect) 한 대를 이용하여 골프 스윙의 자동 분석에 필요한 스윙 특징들을 자동 추출하는 효율적인 방법을 제안하였다. 제안한 방법은 키넥트가 제공하는 관절정보와 깊이(Depth) 정보를 이용하여, 골프스윙에서 중요한 7개의 키프레임과 각 키프레임에서 중요한 스윙특징들을 자동 추출한다. 10명의 골퍼들로부터 구한 50회의 스윙데이터에 대하여 성능을 확인 하였다. 제안한 방법은 설치가 간단하면서도 비용이 저렴한 환경에서 의미 있는 3차원 골프스윙 특징 추출이 가능하고, 구체적인 수치 값을 자동으로 제시하므로 실제적인 자가 스윙분석 시스템 개발에 사용될 수 있다는 점에서 의의가 있다.

지면반력분석기를 이용한 골프 스윙의 분석 평가 방법 (A Method for Analyzing and Evaluating the Golf Swing Using the Force Platform Data)

  • 성낙준
    • 한국운동역학회지
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    • 제20권2호
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    • pp.213-219
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    • 2010
  • The purpose of this study is developing a method to analyze and evaluate a golf swing motion using the ground reaction force (GRF) data. Proper weight shifting is essential for a successful shot in golf swing and this could be evaluated by means of the forces between the feet and ground. GRF during the swing were measured from 15 low-handicapped male golfers including professionals. Four clubs(driver, iron 3, iron 5, and iron 7) were selected to analyze the differences due to different characteristics of club. Swings of each subject were taken using a high speed video camera and GRF data were taken simultaneously by two AMTI force platforms. To simplify the GRF data, forces of the three major component of GRF(vertical, lateral, anterior-posterior force) at 10 predefined temporal events for each trial were selected and the mean of each event were calculated and evaluated. Analyzed vertical GRF (VGRF) data could be divided into two different styles, one-legged and two legged. One-legged style shows good weight transfer to the target leg and most of the previous study shows this style as a typical pattern of good players. Therefore the data from the iron 5 swing obtained from 10 one-legged style golfers are provided as criteria for the evaluation of a swing.