• Korean Journal of Applied Biomechanics
• /
• v.19 no.1
• /
• pp.59-66
• /
• 2009

The purpose of this study was to evaluate flatness of swing plane and determine swing plane type using 3-D swing plane analysis from young elite male golf players. This study also investigate the possibility of determination of swing plane using other kinematic parameters except flatness. As results, no correlations was found between flatness and handicap. Comparison of flatness between single plane and multiple plane swing group were performed and found a significant difference. The error range of flatness, 10cm, which was used for distinguish swing plane type was effective since significant differences were found at MB, EB, and EF. These differences were typical characteristics to classify two swing styles. Other kinematic parameters such as unit vector components of shaft and displacement of shaft end point also compared per event but found no significant differences. However, the moving patterns of these parameters during a golf swing showed such characteristics of each swing plane type well that these parameters could be used to determine swing style as an indirect barometers.

• Journal of Broadcast Engineering
• /
• v.18 no.3
• /
• pp.380-392
• /
• 2013

A method to classify a golf swing motion into 7 sections using a Kinect sensor and a fuzzy system is proposed. The inputs to the fuzzy logic are the positions of golf club and its head, which are extracted from the information of golfer's joint position and color information obtained by a Kinect sensor. The proposed method consists of three modules: one for extracting the joint's information, another for detecting and tracking of a golf club, and the other for classifying golf swing motions. The first module extracts the hand's position among the joint information provided by a Kinect sensor. The second module detects the golf club as well as its head with the Hough line transform based on the hand's coordinate. Using a fuzzy logic as a classification engine reduces recognition errors and, consequently, improves the performance of robust classification. From the experiments of real-time video clips, the proposed method shows the reliability of classification by 85.2%.

• Journal of Biosystems Engineering
• /
• v.40 no.3
• /
• pp.289-295
• /
• 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.

• Korean Journal of Applied Biomechanics
• /
• v.16 no.4
• /
• pp.95-103
• /
• 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.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2004.10a
• /
• pp.1221-1224
• /
• 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.

• Physical Therapy Rehabilitation Science
• /
• v.6 no.4
• /
• pp.189-195
• /
• 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.

• The Journal of Natural Sciences
• /
• v.13 no.1
• /
• pp.25-33
• /
• 2003

Experiment setup was designed to observe the grip pressure and the center of gravity during golf swing. The experimental results of grip pressure and center of gravity during swing showed the constant type in the envelop of force intensity of a stable KPGA pro as a function of time.

• Journal of the Korea Society of Computer and Information
• /
• v.19 no.12
• /
• pp.197-207
• /
• 2014

In this paper, I propose an automatic extraction method of golf swing features using a practical TOF camera Kinect. I extracted 7 key swing frames and features using joints and depth information from a Kinect. I tested the proposed method on 50 swings from 10 players and showed the performace. It is meaningful that 3D swing features are extracted automatically using an inexpensive and simple system and specific numerical feature values can be used for the building of automatic swing analysis system.

• Korean Journal of Applied Biomechanics
• /
• v.20 no.2
• /
• pp.213-219
• /
• 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.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2006.10a
• /
• pp.451-452
• /
• 2006