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During putting in golf, the direction and velocity of the club head should be consistent across swings. In order to maintain consistency in swing timing, the cerebellum provides temporal information, motor timing, control of rhythm, and timing of movements. We utilized Interactive Metronome (IM), a brain training software program that combines the concepts of neurotechnology with the abilities of a computer, to improve an individual's rhythm and timing. We propose that IM would activate neural networks involved in decreasing variation in putt swing. Twenty professional female golfers (KLPGA) were randomly assigned to either an IM training group (n = 10, 35-40 min per session, twice a week for 6 weeks) or a control group (n = 10). The golf putting movements and brain activity were analyzed using Kinovea Software and resting state functional MRI, respectively. Consistency was measured as the standard deviation of mean swing speed (SSD) during three sections of the swing: backswing (AD-BS), backswing-impact (BS-IMP), and impact-finish (IMP-FIS). Our results show that the consistency of the IM group improved in the time between the back swing and impact in the 2 m putt and 5 m putt compared to the control group. Using functional MRI, after the training period, the IM group showed increased functional connectivity from the superior cerebellar vermis to the right medial frontal gyrus, left superior temporal gyrus, right middle occipital gyrus, right middle temporal gyrus, right cingulate gyrus, and right supramarginal gyrus (uncorrected p < 0.001, voxels > 40). These findings suggest that IM training in professional female golf players may improve consistency in putt timing. In addition, IM training may increase brain connectivity from the cerebellum to the frontal cortex, which plays an important role in motor control and timing. [ABSTRACT FROM AUTHOR]

Exploring relations between patterns of peak rotational speed of thorax, pelvis and arm, and patterns of EMG signals recorded from eight muscle regions of forearms and shoulders during the golf swing is the main objective of this article. The linear canonical correlation analysis, allowing studying relations between sets of variables, was the main technique applied. To get deeper insights, linear and nonlinear random forests-based prediction models relating a single output variable, e.g. a thorax peak rotational speed, with a set of input variables, e.g. an average intensity of EMG signals were used. The experimental investigations using data from 16 golfers revealed statistically significant relations between sets of input and output variables. A strong direct linear relation was observed between linear combinations of EMG averages and peak rotational speeds. The coefficient of determination values R 2 = 0.958 and R 2 = 0.943 obtained on unseen data by the random forest models designed to predict peak rotational speed of thorax and pelvis , indicate high modelling accuracy. However, predictions of peak rotational speed of arm were less accurate. This was expected, since peak rotational speed of arm played a minor role in the linear combination of peak speeds. The most important muscles to predict peak rotational speed of the body parts were identified. The investigations have shown that the canonical correlation analysis is a promising tool for studying relations between sets of biomechanical and EMG data. Better understanding of these relations will lead to guidelines concerning muscle engagement and coordination of thorax, pelvis and arms during a golf swing and will help golf coaches in providing substantiated advices. [ABSTRACT FROM AUTHOR]

Substantial experiential research into x-factor, and to a lesser extent crunch-factor has been undertaken with the aim of increasing clubhead speed. However, a direct comparison of the golf swing kinematics associated with each 'factor' has not, and possible differences when using a driver compared to an iron. Fifteen low handicap male golfers who displayed a modern swing had their golf swing kinematic data measured when hitting their own driver and five-iron, using a 10-camera motion analysis system operating at 250Hz. Clubhead speed was collected using a validated launch monitor. No between-club differences in x-factor and crunch-factor existed. Correlation analyses revealed within-club segment (trunk and lower trunk) interaction was different for the driver, compared to the five-iron, and that a greater number of kinematic variables associated with x-factor, compared to crunch-factor were shown to be correlated with faster clubhead speeds. This was further explained in the five-iron regression model, where a significant amount of variance in clubhead speed was associated with increased lower trunk x-factor stretch, and reduced trunk lateral bending. Given that greens in regulation was shown to be the strongest correlated variable with PGA Tour earnings (1990-2004), the findings suggests a link to player performance for approach shots. These findings support other empiric research into the importance of x-factor as well as anecdotal evidence on how crunch-factor can negatively affect clubhead speed. [ABSTRACT FROM AUTHOR]