PDF(2470 KB)
Construction of a Three-Dimensional Kinematic Model of the Full-Swing Body Motion in Elite Male Golfers——Based on AIGolf Video Recognition Technology
ZHOU Hongyu, LIU Baohua, LI Chao, LI Jiayun
Journal of Capital University of Physical Education and Sports ›› 2026, Vol. 38 ›› Issue (3) : 277-285.
PDF(2470 KB)
PDF(2470 KB)
Construction of a Three-Dimensional Kinematic Model of the Full-Swing Body Motion in Elite Male Golfers——Based on AIGolf Video Recognition Technology
Objective: To explore the kinematic data of full-swing body motion in top-ranked elite male golfersfrom around the world, summarize the technical characteristics and Kinematics principles of their full swing, and construct a three-dimensional kinematic model of the elite male golfer’s full swing. Methods: Based on AIGolf video recognition technology, the videos of 15elite male playersfrom around the world was analyzed. Result: 1)In terms of static standing posture, the spine leans forward by 34.07°±2.79°towards the“+” direction of the Y axis and tilts by -4.00°±1.13°towards the“-”direction of the x axis. The shoulder line and hip line are parallel to the target direction of the x axis. The upper limb system, with the left arm (F1: 176.07°±2.34°) and right arm(F2: 164.67°±4.35°) naturally hanging down, forms an angle of 39.87°±3.89° with the spine. The lower limb system, with the left knee (x1: 154.93°±4.37°, y1: 3.27°±3.77°) and right knee (x2: 153.00°±5.03°, y2: -1.27°±4.15°) moderately bent, forms an angle of 129.00°±4.81° between the spine and thigh, with the centers of gravity of the left and right feet evenly distributed; 2)In terms of dynamic stability, there were significant differences in the trunk spine tilt angle (B2) between P5 and P1 positions (p<0.001), as well as significant differences in the lower limb system’s spine-thigh angle (L), left knee flexion angle (x1), right knee offset angle (y2), and center of gravity distribution (z1/z2) (p<0.05). There were also significant differences in the upper limb system’s forearm-shaft angle (V1) and right arm flexion angle (F2) (p<0.001); 3)In terms of dynamic rotational force, the effective working angles of the shoulders and hips are 249.33°±16.32°and 114.93°±17.89°, respectively, with effective working powers of 67.30% and 63.33%, respectively. Conclusion: A three-dimensional kinematic model of the elite male golfer’s full swing was constructed. The model includes the lower-limb system (knee joints G1/G2), the trunk system (hip joints K1/K2, shoulder joints D1/D2), and the upper-limb system (elbow joints E1/E2), providing reference for AI recognition and optimization research on golf full swing movements.
Golf / full swing / body motion / three-dimensional data model
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Training devices to enhance golf swing technique are increasingly in demand. Golf swing biomechanics are typically assessed in a laboratory setting and not readily accessible. Inertial measurement units (IMUs) offer improved access as they are wearable, cost-effective, and user-friendly. This study investigates the accuracy of IMU-based golf swing kinematics of upper torso and pelvic rotation compared to lab-based 3D motion capture. Thirty-six male and female professional and amateur golfers participated in the study, nine in each sub-group. Golf swing rotational kinematics, including upper torso and pelvic rotation, pelvic rotational velocity, S-factor (shoulder obliquity), O-factor (pelvic obliquity), and X-factor were compared. Strong positive correlations between IMU and 3D motion capture were found for all parameters; Intraclass Correlations ranged from 0.91 (95% confidence interval [CI]: 0.89, 0.93) for O-factor to 1.00 (95% CI: 1.00, 1.00) for upper torso rotation; Pearson coefficients ranged from 0.92 (95% CI: 0.92, 0.93) for O-factor to 1.00 (95% CI: 1.00, 1.00) for upper torso rotation (p < 0.001 for all). Bland–Altman analysis demonstrated good agreement between the two methods; absolute mean differences ranged from 0.61 to 1.67 degrees. Results suggest that IMUs provide a practical and viable alternative for golf swing analysis, offering golfers accessible and wearable biomechanical feedback to enhance performance. Furthermore, integrating IMUs into golf coaching can advance swing analysis and personalized training protocols. In conclusion, IMUs show significant promise as cost-effective and practical devices for golf swing analysis, benefiting golfers across all skill levels and providing benchmarks for training.
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In golf, the location of the impact, where the clubhead hits the ball, is of imperative nature for a successful ballflight. Direct feedback to the athlete where he/she hits the ball could improve a practice session. Currently, this information can be measured via, e.g., dual laser technology; however, this is a stationary and external method. A mobile measurement method would give athletes the freedom to gain the information of the impact location without the limitation to be stationary. Therefore, the aim of this study was to investigate whether it is possible to detect the impact location via a motion sensor mounted on the shaft of the golf club. To answer the question, an experiment was carried out. Within the experiment data were gathered from one athlete performing 282 golf swings with an 7 iron. The impact location was recorded and labeled during each swing with a Trackman providing the classes for a neural network. Simultaneously, the motion of the golf club was gathered with an IMU from the Noraxon Ultium Motion Series. In the next step, a neural network was designed and trained to estimate the impact location class based on the motion data. Based on the motion data, a classification accuracy of 93.8% could be achieved with a ResNet architecture.
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This study introduces an innovative integration of Laban Movement Analysis (LMA) with biomechanical principles to examine the golf swing dynamics from an ecological perspective. Traditionally, LMA focuses on the qualitative aspects of movement, often isolated from external influences. This research bridges that gap by investigating how golfers manage and adapt to the inertial forces of the club throughout the swing. Using motion tracking sensors and screw theory, we analyzed the spatial movement pattern in the Kinesphere (mapped as an icosahedron) and related it to force dynamics in the Effort Cube through the inertia tensor. The results showed significant differences between skilled and novice golfers in terms of how efficiently they align their movements with the club’s inertia. Skilled golfers demonstrated smoother Instantaneous Screw Axes (ISAs) and better synchronization with inertia forces, while novice golfers exhibited more abrupt deviations. These findings suggest that integrating qualitative movement descriptors with biomechanical models provides deeper insights into swing efficiency, performance improvement, and injury prevention. This combined framework offers a novel method to enhance both qualitative and quantitative analysis of golf swings.
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In this study, we address two technical challenges to enhance golf swing trajectory accuracy using a wrist-worn inertial sensor: orientation estimation and drift error mitigation. We extrapolated consistent sensor orientation from specific address-phase signal segments and trained the estimation with a convolutional neural network. We then mitigated drift error by applying a constraint on wrist speed at the address, backswing top, and finish, and ensuring that the wrist's finish displacement aligns with a virtual circle on the 3D swing plane. To verify the proposed methods, we gathered data from twenty male right-handed golfers, including professionals and amateurs, using a driver and a 7-iron. The orientation estimation error was about 60% of the baseline, comparable to studies requiring additional sensor information or calibration poses. The drift error was halved and the single-inertial-sensor tracking performance across all swing phases was about 17 cm, on par with multimodal approaches. This study introduces a novel signal processing method for tracking rapid, wide-ranging motions, such as a golf swing, while maintaining user convenience. Our results could impact the burgeoning field of daily motion monitoring for health care, especially with the increasing prevalence of wearable devices like smartwatches.
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Golf participation has increased dramatically in the last several years. With this increase in participation, clinicians need better evidenced based strategies to advise those golfers with different pathologies when it is safe to return to the game. Golf teaching professionals also need to understand how to alter golf mechanics to protect injured and/or diseased joints in golfers to allow them to play pain free and avoid further injury. This study used a 3-dimensional link segment model to calculate the net joint moments on the large lower limb joints (knee and hip) during golf (lead and trail leg) and two commonly studied activities of daily living (gait and sit-to-stand) in 22 males, healthy, adult golfers. It also examined the correlations between these knee and hip joint loads and club head speed. The external valgus knee moment and the internal hip adduction moment were greater in the lead leg in golf than in the other activities and were also correlated with club head speed. This indicates a strategy of using the frontal plane GRF moment during the swing. The internal hip extension and knee flexion moment were also greater in the golf swing as compared with the other activities and the hip extension moment was also correlated with club head speed. This emphasizes the importance of hip extensor (i.e., gluteus maximus and hamstring) muscle function in golfers, especially in those emphasizing the use of anterior-posterior ground reaction forces (i.e., the pivoting moment). The golf swing places some loads on the knee and the hip that are much different than the loads during gait and sit-to-stand tasks. Knowledge of these golf swing loads can help both the clinician and golf professional provide better evidence-based advice to golfers in order to keep them healthy and avoid future pain/injury.© Journal of Sports Science and Medicine.
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