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"Swing (Golf)"
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Biomechanical Analysis of Golf Swing Motion Using Hilbert–Huang Transform
In golf swing analysis, high-speed cameras and Trackman devices are traditionally used to collect data about the club, ball, and putt. However, these tools are costly and often inaccessible to golfers. This research proposes an alternative solution, employing an affordable inertial motion capture system to record golf swing movements accurately. The focus is discerning the differences between motions producing straight and slice trajectories. Commonly, the opening motion of the body’s left half and the head-up motion are associated with a slice trajectory. We employ the Hilbert–Huang transform (HHT) to examine these motions in detail to conduct a biomechanical analysis. The gathered data are then processed through HHT, calculating their instantaneous frequency and amplitude. The research found discernible differences between straight and slice trajectories in the golf swing’s moment of impact within the instantaneous frequency domain. An average golfer, a single handicapper, and three beginner golfers were selected as the subjects in this study and analyzed using the proposed method, respectively. For the average golfer, the head and the left leg amplitudes of the swing motions increase at the moment of impact of the swings, resulting in the slice trajectory. These results indicate that an opening of the legs and head-up movements have been detected and extracted as non-linear frequency components, reviewing the biomechanical meaning in slice trajectory motion. For the single handicapper, the hip and left arm joints could be the target joints to detect the biomechanical motion that triggered the slice trajectory. For the beginners, since their golf swing forms were not finalized, the biomechanical motions regarding slice trajectory were different from each swing, indicating that beginner golfers need more practice to fix their golf swing form first. These results revealed that our proposed framework applied to different golf levels and could help golfers to improve their golf swing skills to achieve straight trajectories.
Journal Article
Estimation of Center of Mass Trajectory using Wearable Sensors during Golf Swing
This study suggests a wearable sensor technology to estimate center of mass (CoM) trajectory during a golf swing. Groups of 3, 4, and 18 participants were recruited, respectively, for the purpose of three validation studies. Study 1 examined the accuracy of the system to estimate a 3D body segment angle compared to a camera-based motion analyzer (Vicon®). Study 2 assessed the accuracy of three simplified CoM trajectory models. Finally, Study 3 assessed the accuracy of the proposed CoM model during multiple golf swings. A relatively high agreement was observed between wearable sensors and the reference (Vicon®) for angle measurement (r > 0.99, random error <1.2° (1.5%) for anterior-posterior; <0.9° (2%) for medial-lateral; and <3.6° (2.5%) for internal-external direction). The two-link model yielded a better agreement with the reference system compared to one-link model (r > 0.93 v. r = 0.52, respectively). On the same note, the proposed two-link model estimated CoM trajectory during golf swing with relatively good accuracy (r > 0.9, A-P random error <1cm (7.7%) and <2cm (10.4%) for M-L). The proposed system appears to accurately quantify the kinematics of CoM trajectory as a surrogate of dynamic postural control during an athlete's movement and its portability, makes it feasible to fit the competitive environment without restricting surface type. Key pointsThis study demonstrates that wearable technology based on inertial sensors are accurate to estimate center of mass trajectory in complex athletic task (e.g., golf swing)This study suggests that two-link model of human body provides optimum tradeoff between accuracy and minimum number of sensor module for estimation of center of mass trajectory in particular during fast movements.Wearable technologies based on inertial sensors are viable option for assessing dynamic postural control in complex task outside of gait laboratory and constraints of cameras, surface, and base of support.
Journal Article
Kinematic analyses of the golf swing hub path and its role in golfer/club kinetic transfers
This study analyzed the fundamental geometric and kinematic characteristics of the swing hub path of the golf shot for four diverse subjects. In addition, the role of the hub path geometry in transferring the kinetic quantities from the golfer to the club were investigated. The hub path was found to have a complex geometry with significantly changing radii, and a constantly moving center-of-curvature during the downswing for all subjects. While the size and shape of the hub path differed considerably among the subjects, a three phase radius-based pattern was revealed that aligned with distinct stages of the downswing. Artificially controlling and optimizing the hub path of the better golfer in the group indicated that a non-circular hub path was superior to a constant radius path in minimizing the kinetic loading while generating the highest possible club head velocity. The shape and purpose of the hub path geometry appears to result from a complex combination of achieving equilibrium between the golfer and the club, and a purposeful configuring of the path to control the outward movement of the club while minimizing the kinetic loading on the golfer yet transferring the maximum kinetic quantities to the club. Describing the downswing relative to the hub path phasing is presented and was found to be informative since the phases align with significant swing, kinetic and kinematic markers. These findings challenge golf swing modeling methodologies which fix the center-of-curvature of the hub path thus constraining it to constant radius motion. Key pointsThe golf swing hub path was found to have a complex geometry with significantly changing radii, and a constantly moving center-of-curvature during the downswing.The hub path differed considerably among subjects, however a three phase radius-based pattern was revealed that aligned with distinct stages of the downswing.The shape and purpose of the hub path geometry appears to result from a complex combination of achieving equilibrium between the golfer and the club, and a purposeful configuring of the path to control the outward movement of the club while minimizing the kinetic loading on the golfer yet transferring the maximum kinetic quantities to the club.
Journal Article
The anatomy of greatness : lessons from the best golf swings in history
\"Every golf game begins with the swing, and no two are identical. Years ago, however, Brandel Chamblee, the highly regarded Golf Channel analyst and former PGA Tour professional, noticed that the best players of all time have shared similar positions in each part of the swing, from the grip and setup to the footwork, backswing, and follow-through. Since then, Chamblee, a student of gameś history, has used scientific precision and thoroughness to make a study of the common swing positions of the greats. Now, in The Anatomy of Greatness, he reveals what he has learned, offers hundreds of photographs as his proof, to show us how we can easily incorporate his findings into our own swings to hit the ball farther, straighter, and more consistently\"--Amazon.com.
Book
Biomechanical characteristics of swing techniques using different clubs in college male golfers
Golf is a sophisticated sport that integrates precision, skillfulness, and strategic thinking, with swing techniques of different clubs exhibiting distinct biomechanical characteristics. This study aims to investigate the biomechanical characteristics of golfers' full swings with different clubs from kinematic and dynamics perspectives, thereby providing insights for optimizing full swing techniques.
Ten low-handicap right-handed college male golfers were recruited, and their full swing parameters with the driver, 5-iron, and 7-iron (each club was successfully collected 10 times) were synchronously collected using a 250 Hz infrared motion capture system and a 1000 Hz three-dimensional force platform. A one-way ANOVA was conducted to compare biomechanical indicators during the swing motion across different clubs.
There were significant kinematic differences between the driver and irons, yet smaller differences between 5-iron and 7-iron. As a whole, irons showed a faster peak time and a smaller angular velocity. The GRF of different clubs exhibited different dynamic characteristics at various swing moments, yet the dynamic regularity remained consistent throughout the full swing. During the downswing, the horizontal angular impulse of the driver was greater than irons, and the frontal angular impulse of the 5-iron was greater than that of both driver and 7-iron.
The characteristics of the driver are slow - paced energy accumulation, delayed acceleration, and horizontal sweeping shots; the characteristics of the 5-iron are that the leading arm coordinates with the frontal angular impulse to optimize the shot trajectory; the characteristics of the 7-iron are compact transition and precise shots driven by the torso.
Journal Article
Fix it yourself : how to recognize the faults in your game-and correct them
\"A contemporary look at the most common faults that plague golfers today and the simple and effective solutions based on Leadbetter's popular original bestseller, Faults and Fixes. From the world's number one golf coach, the pro who teaches the pros, comes the only guide you'll need to improve your game, whatever your level of play. Leadbetter's Faults and Fixes, published in 1993, remains one of the most important golf guides to players all over the world. Thirty years later, he brings us a modern approach to this revolutionary format, based on the extraordinary innovations in performance and technology in recent years. Yet while golf superstars push the boundaries of performance, most recreational golfers lack access to the technology that would enable them to take their game to the next level. If you are serious about golf, you will forever be in search of clear-cut remedies to the various faults that plague your game. This comprehensive fault-finding guide, containing easy-to-understand solutions to the game's most common errors, is invaluable for any aspiring player. In this manual, you will find: - Solutions to 72 of the most common problem areas in golf - Drills and exercises specially designed to cure even the most persistent faults - Full color illustrations to take you step-by-step through your grip and swing - A unique instruction package that will enable you to identify the weaknesses in your game-and then systematically eliminate them. Golf's #1 instructor has reimagined his bestselling book, to the benefit of golfers everywhere!\"-- Provided by publisher.
Book
Dynamic Golf Swing Analysis Framework Based on Efficient Similarity Assessment
With advances in computing power and deep learning, image-based pose estimation has become a viable tool for quantitative motion analysis. Compared to sensor-based systems, vision-based approaches are cost-effective, portable, and easy to deploy. However, when applied to golf swings, conventional similarity measures often fail to match expert perception, as they rely on static, frame-wise posture comparisons and require strict temporal alignment. We propose a Dynamic Motion Similarity Measurement (DMSM) framework that segments a swing into seven canonical phases—address, takeaway, half, top, impact, release, and finish—and evaluates the dynamic trajectories of joint keypoints within each phase. Unlike traditional DTW- or frame-based methods, our approach integrates continuous motion trajectories and normalizes joint coordinates to account for player body scale differences. Motion data are interpolated to improve temporal resolution, and numerical integration quantifies path differences, capturing motion flow rather than isolated postures. Quantitative experiments on side-view swing datasets show that DMSM yields stronger discrimination between same- and different-player pairs (phase-averaged separation: 0.092 vs. 0.090 for the DTW + cosine baseline) and achieves a clear biomechanical distinction in spine-angle trajectories (Δ = 38.68). Statistical analysis (paired t-test) confirmed that the improvement was significant (p < 0.05), and coach evaluations supported perceptual alignment. Although DMSM introduces a minor computational overhead (≈169 ms), it delivers more reliable phase-wise feedback and biomechanically interpretable motion analysis. This framework offers a practical foundation for AI-based golf swing analysis and real-time feedback systems in sports training, demonstrating improved perceptual consistency, biomechanical interpretability, and computational feasibility.
Journal Article