ANALYSIS OF LEFT ARM SEGMENTAL CONTRIBUTION IN GOLF SWING

The object of this study is to examine the segmental movement of the left arm in a golf swing and determine its contribution to the final club head speed. In order to examine this movement, a procedure for quantifying joint movement was developed. Electrogoniometers (Biometrics, UK) with frequency of 1000 Hz were attached to the subjects during the execution of the swing to obtain the joint angles throughout the motion. The velocities of the segment rotation can be computed with dual velocity analysis. A zero handicapper was tested with the method. The method uncovers the importance of longitudinal segmental rotations in his swing. These rotations are often neglected in 2-dimensional approaches

A preliminary investigation of trunk and wrist kinematics when using drivers with different shaft properties

It is unknown whether skilled golfers will modify their kinematics when using drivers of different shaft properties. This study aimed to firstly, determine if golf swing kinematics and swing parameters and related launch conditions differed when using modified drivers, then secondly, determine which kinematics were associated with clubhead speed. Twenty high level amateur male golfers (Mean ± SD: handicap = 1.9 ± 1.9 score) had their three-dimensional trunk and wrist kinematics collected for two driver trials. Swing parameters and related launch conditions were collected using a launch monitor. A one-way repeated measures ANOVA revealed significant (p ≤ 0.003) between-driver differences; specifically, faster trunk axial rotation velocity and an early wrist release for the low kick point driver. Launch angle was shown to be 2° lower for the high kick point driver. Regression models for both drivers explained a significant amount of variance (60 – 67%) in clubhead speed. Wrist kinematics were most associated with clubhead speed, indicating the importance of the wrists in producing clubhead speed regardless of driver shaft properties

Coach informed biomechanical analysis of the golf swing

Coach informed biomechanical analysis of the golf swin

Development and evaluation of new control algorithms for a mechanical golf swing device

Golf swing machines have become fundamental tools in the development of new equipment because they provide more consistent swing motions than golfers. Golf robots perform a simplification of the complex sequence of motions that compose a golf swing; however, traditional devices are typically capable of performing only a single swing profile at variable speeds. Significant differences exist between individual golfers’ swing motions, especially for golfers of different ability, experience, and physical stature, which suggests a requirement for swing profile variability in mechanical simulators. This investigation has found that the swing motion of a traditional golf robot provides a poor representation of golfers’ swings and, as a result, a bespoke control system has been developed for a commercially available golf robot to enable performance of variable swing profiles with positional feedback. Robot swing command files are generated by fitting a curve to a number of discrete data points that are equally spaced in time, and which define angles representative of individual golfers’ swings. The swing profiles of a professional golfer and a traditional golf robot were repeated accurately using this golf robot with a modified motion control system. The capability for individual golfers’ swings to be accurately replicated using a mechanical device was demonstrated using feedback data. All manufacturers recognize the importance of tailoring equipment to the unique characteristics of a particular golfer’s swing, and this increased robot functionality will provide considerable benefits in the development of customized equipment

An Investigation of Technique and Equipment Factors Associated with Clubhead Speed in Golf

If golfers achieve long hitting distances whilst maintaining their accuracy they will gain a competitive advantage. To increase hitting distance, faster clubhead speed is required and this can potentially be achieved through a number of factors. Firstly, anthropometric factors such as height and physical factors such as trunk rotational power have been previously considered to be of importance. However, biomechanical factors such as; the X-factor (separation of the trunk-pelvis alignment when viewed in the transverse plane), have been a major focus of recent research. Further, the interaction of the golfer with the implement they hit with i.e. the golf club has also been examined in biomechanical studies. The broad aim of this doctoral research was to investigate how male high-level amateur golfers generate club head speed and this was examined in a series of five studies that examined technical and equipment factors. The first study of this thesis (Study I) developed a valid three-dimensional Cardan / Euler model to examine the kinematics of the trunk and lower trunk during the golf swing. This validation study involved; developing and validating models and related algorithms as well as making comparisons to static and dynamic postures. It was concluded that a lateral bending / flexion-extension / axial rotation (ZYX) order of rotation was the most suitable to quantify the X-factor and lower trunk movement in the golf swing. Previous research has shown conflicting relationships between golf swing kinematics (such as variables related to the X-factor) and clubhead speed, as well as what physical variables assist in generating clubhead speed. The second study of this thesis (Study II) had two aims. The first aim was to determine whether significant between-club (driver and five-iron) differences existed for trunk and lower trunk kinematics as well as launch conditions. The second aim was to determine which anthropometric, physical and trunk and lower trunk kinematic variables were most strongly associated with clubhead speed. Fifteen high level amateur male golfers (2.5 ± 1.9 handicap) had their trunk and lower trunk three-dimensional kinematics data quantified using the methods developed in Study I. Nine significant (p \u3c 0.002) between-club differences in swing kinematics were found; namely trunk and lower trunk flexion and lower trunk axial rotation, as well as ball velocity. Regression analyses explained 33.7 % and 66.7 % of the variance in clubhead speed for the driver and five-iron respectively, with both trunk and lower trunk variables showing associations with clubhead speed. No anthropometric (i.e. height) or physical (i.e. maximum trunk rotational speed) were associated with clubhead speed. The low amount of variance explained by clubhead speed for the driver in Study II stimulated further investigation. Studies III and IV were designed to develop a method to locate the kick point during the golf swing and examine the effect of kick point location on swing parameters and their related launch conditions, respectively. Study III involved two phases, Firstly, the level of agreement between two methods of determining the static kick point was determined. This showed that an algorithm using three-dimensional locations of markers placed on the golf club was a valid method to determine the location of the static kick point. In the second phase of testing, this method was used to determine the location of the dynamic kick point during the golf swing. Excellent between-trial reliability was found for this method. Further, differences were found for the dynamic kick point location when compared to the static kick point location. The main objective of Study IV was to determine whether drivers fitted with shafts having high and low kick points would alter selected swing parameters, and related launch conditions. Twelve high level amateur male golfers (1.2 ± 1.8 handicap) had three shots analysed for each of two drivers fitted with “stiff” shafts but these drivers had differing kick point location. Stiffness profiles of these shafts were also measured. Five swing parameters and their related launch conditions were measured using a real-time launch monitor. The driver fitted with the shaft containing the high kick point displayed a more negative (steeper) angle of attack, a lower launch angle and an increased spin rate when compared to a driver fitted with a low kick point In Study II, a relatively small amount of variance in clubhead speed was explained by the driver and it was the overall intention of the last study of this thesis (Study V) to attempt to explain more of this variance by examining both trunk and wrist kinematics. This was undertaken using two drivers containing differing kick point locations (low and high), with two separate regression models being produced. Twenty high-level amateur male golfers (1.9 ± 1.9 handicap) had their trunk and lower trunk three-dimensional kinematics data quantified as in Study II, but with the addition of a wrist segment. Four significant (p In conclusion, the methods developed for this thesis to analyse golf swing kinematics revealed a greater insight into how highly skilled golfers produce clubhead speed. Particularly, the results from Studies II and V revealed significant associations between lower trunk related variables and clubhead speed when using different clubs (driver vs. fiveiron) and the same club fitted with two shafts of different kick point location (driver). Also, the methods developed in Studies III and IV to investigate dynamic shaft profiles (deflection) in the downswing provided possible explanations as to how shaft performance in the downswing can influence swing parameters and their related launch conditions at ball impact

Effects of a functional fatigue protocol on maximal softball hitting.

Fatigue can affect athletic performance in many ways, including a decrease in sport specific accuracy, impairments in joint angles, and a decrease in overall muscle performance. In regards to fatigue, little research has been conducted examining the effects of fatigue on baseball and softball performance. The majority of the research stems from examining the effects of fatigue on the overhead throwing motion among collegiate baseball players. Research suggested that as a result of a functional fatigue protocol, baseball pitchers experienced impairments in joint angles in the overhead throwing motion. Among this same population, throwing velocities decreased significantly from the first to last inning pitched, resulting in a great deal of in-game fatigue. Researchers attested that such changes in angles and velocities as a result of fatigue, would negatively affect performance. The purpose of this study was to examine the effects of a functional fatigue protocol on softball hitting form. Additional research, examined the effects of fatigue on performance among skilled tennis athletes. A functional fatigue protocol was implemented, which directly simulated tennis matchplay. Results revealed decreases in tennis hitting accuracy, and just as with the baseball players, fatigue resulted in a decrease in performance. A secondary objective was to identify the relationship between hitting variables, muscular power, and body composition. Participants (n = 6) were NCAA Division II softball players with a mean age of 19.5 ± 1.4 years who completed a functional fatigue protocol (FFP). The FFP was filmed using a digital video camera, and results were analyzed using Dartfish motion analysis software. To address the secondary objectives, participants completed the Wingate Anaerobic Power test to assess muscular power and a dual-energy x-ray absorptiometry (DXA) scan to discover body composition values. To detect differences in swing angles pre- and post-fatigue, an ANOVA was conducted revealing significant (p .05) between muscular power and LBEV or BBV, in addition to no significant relationships between percent fatigue as measured by WAnT or the FFP. Meaningful relationships were discovered between peak power and LBEV and BBV. A strong, negative correlation was present between peak power and BBV (r = -.73, p = .097) and a moderate, negative correlation between peak power and LBEV ( r = -.68, p = .138). Additionally, percent body fat was negatively related to percent fatigue in LBEV(r = -.76, p = .082). Results indicated that fatigue did in fact have a negative effect on softball hitting form, with significant decreases in LBEV and BBV, and that peak power and hitting velocities were inversely related. Although no differences were found in swing angles at ball contact, changes in LBEV and BBV could be detrimental to swing timing and performance. Results of this study will be utilized to further understand the effects of fatigue on softball hitting form and the role of muscular power and body composition on hitting performance

Investigating the Role of a Reduced-Instruction Approach in Implicit and Explicit Motor Learning Strategies

Traditional explanations of motor learning contend that skills are learned explicitly in a process in which learners accumulate declarative knowledge and progress through distinct stages of learning (e.g., Fitts & Posner, 1967). More recently, implicit approaches to instruction have been used in an attempt to bypass accumulation of explicit knowledge. Such approaches have been shown to facilitate motor learning compared to explicit instruction by enhancing skill retention and transfer under conditions involving distraction, increased pressure, or physical stress (Masters & Poolton, 2012). One method thought to invoke implicit learning involves instructions in the form of an analogy (Liao & Masters, 2001). Researchers have typically compared the effects of a single analogy statement to those of explicit instructions consisting of up to 12 statements (Liao & Masters, 2001). Thus, observed differences between these approaches could be attributed to different attentional loading. The purpose of this study was to compare the effects of analogy instruction on the performance and learning of a motor skill to those of explicit instruction consisting of a single statement (i.e., an equivalent amount of instruction). Participants (n = 48) practiced a 10-foot golf putt under one of four instructional conditions: Six-Rule Traditional Explicit Instruction (TEI), One-Rule Explicit Instruction (OREI), Analogy Instruction (AI), or no instruction (CTRL). Results indicated that the AI and OREI groups made more putts than expected during acquisition while the CTRL group made fewer. During Retention 1 and 2, however, the number of putts made was similar to what was expected, indicating that initial differences in performance of the primary task were eliminated with practice. During Transfer 1 (breaking putt), the TEI group made fewer putts than expected, suggesting that traditional explicit instruction can negatively affect adaptation to novel task demands. During Transfer 2 (attentional loading), the AI group made more putts than expected while the TEI and CTRL groups made fewer. These results suggest that when instruction is given, the length of such instruction may degrade performance under secondary-task attentional loading. Moreover, the use of analogy instruction may confer an additional benefit compared to an equivalent-length explicit instruction