Effects of physical randomness training on virtual and laboratory golf putting performance in novices.

External randomness exists in all sports but is perhaps most obvious in golf putting where robotic putters sink only 80% of 5 m putts due to unpredictable ball-green dynamics. The purpose of this study was to test whether physical randomness training can improve putting performance in novices. A virtual random-physics golf-putting game was developed based on controlled ball-roll data. Thirty-two subjects were assigned a unique randomness gain (RG) ranging from 0.1 to 2.0-times real-world randomness. Putter face kinematics were measured in 5 m laboratory putts before and after five days of virtual training. Performance was quantified using putt success rate and "miss-adjustment correlation" (MAC), the correlation between left-right miss magnitude and subsequent right-left kinematic adjustments. Results showed no RG-success correlation (r = -0.066, p = 0.719) but mildly stronger correlations with MAC for face angle (r = -0.168, p = 0.358) and clubhead path (r = -0.302, p = 0.093). The strongest RG-MAC correlation was observed during virtual training (r = -0.692, p < 0.001). These results suggest that subjects quickly adapt to physical randomness in virtual training, and also that this learning may weakly transfer to real golf putting kinematics. Adaptation to external physical randomness during virtual training may therefore help golfers adapt to external randomness in real-world environments.

Vector-field statistics for the analysis of time varying clinical gait data.

BACKGROUND: In clinical settings, the time varying analysis of gait data relies heavily on the experience of the individual(s) assessing these biological signals. Though three dimensional kinematics are recognised as time varying waveforms (1D), exploratory statistical analysis of these data are commonly carried out with multiple discrete or 0D dependent variables. In the absence of an a priori 0D hypothesis, clinicians are at risk of making type I and II errors in their analyis of time varying gait signatures in the event statistics are used in concert with prefered subjective clinical assesment methods. The aim of this communication was to determine if vector field waveform statistics were capable of providing quantitative corroboration to practically significant differences in time varying gait signatures as determined by two clinically trained gait experts. METHODS: The case study was a left hemiplegic Cerebral Palsy (GMFCS I) gait patient following a botulinum toxin (BoNT-A) injection to their left gastrocnemius muscle. FINDINGS: When comparing subjective clinical gait assessments between two testers, they were in agreement with each other for 61% of the joint degrees of freedom and phases of motion analysed. For tester 1 and tester 2, they were in agreement with the vector-field analysis for 78% and 53% of the kinematic variables analysed. When the subjective analyses of tester 1 and tester 2 were pooled together and then compared to the vector-field analysis, they were in agreement for 83% of the time varying kinematic variables analysed. INTERPRETATION: These outcomes demonstrate that in principle, vector-field statistics corroborates with what a team of clinical gait experts would classify as practically meaningful pre- versus post time varying kinematic differences. The potential for vector-field statistics to be used as a useful clinical tool for the objective analysis of time varying clinical gait data is established. Future research is recommended to assess the usefulness of vector-field analyses during the clinical decision making process.

Does footprint depth correlate with foot motion and pressure?

Footprints are the most direct source of evidence about locomotor biomechanics in extinct vertebrates. One of the principal suppositions underpinning biomechanical inferences is that footprint geometry correlates with dynamic foot pressure, which, in turn, is linked with overall limb motion of the trackmaker. In this study, we perform the first quantitative test of this long-standing assumption, using topological statistical analysis of plantar pressures and experimental and computer-simulated footprints. In computer-simulated footprints, the relative distribution of depth differed from the distribution of both peak and pressure impulse in all simulations. Analysis of footprint samples with common loading inputs and similar depths reveals that only shallow footprints lack significant topological differences between depth and pressure distributions. Topological comparison of plantar pressures and experimental beach footprints demonstrates that geometry is highly dependent on overall print depth; deeper footprints are characterized by greater relative forefoot, and particularly toe, depth than shallow footprints. The highlighted difference between 'shallow' and 'deep' footprints clearly emphasizes the need to understand variation in foot mechanics across different degrees of substrate compliance. Overall, our results indicate that extreme caution is required when applying the 'depth equals pressure' paradigm to hominin footprints, and by extension, those of other extant and extinct tetrapods.

Linear dependence of peak, mean, and pressure-time integral values in plantar pressure images.

Dynamic plantar pressure images are routinely used in clinical gait assessment, and peak pressure, mean pressure, and pressure-time integral are the most frequently used parameters to summarize these images. Many studies report only one parameter, but other studies report all three. The interdependency of these variables has not been explicitly studied previously. The purpose of this study was to describe the linear relation between these three pressure parameters. 327 subjects walked normally over a pressure plate. Peak pressure, mean pressure and pressure-time integral were calculated for 10 different anatomical areas and, after applying a previously described spatial normalization procedure, these variables were also calculated for each pixel. Mean pressure was highly correlated with peak pressure (r=0.90+/-0.09) and pressure-time integral (r=0.81+/-0.13) for pixels. Peak pressure and pressure-time integral showed a linear correlation coefficient of r=0.78+/-0.21. The pressure parameters of the forefoot pixels were more highly correlated than the heel pixels. The current results have two major implications: (1) plantar pressure parameters (peak, mean, and impulse) can be reasonably compared across studies, even across parameters, and (2) the variables most commonly used to characterize plantar pressures are highly inter-correlated, implying that a smaller set of parameters may more efficiently capture the biomechanical behavior of interest.

Nonlinear spatial warping for between-subjects pedobarographic image registration.

Foot size and shape vary between individuals and the foot adopts arbitrary stance phase postures, so traditional pedobarographic analyses regionalize foot pressure images to afford homologous data comparison. An alternative approach that does not require explicit anatomical labelling and that is used widely in other functional imaging domains is to register images such that homologous structures optimally overlap and then to compare images directly at the pixel level. Image registration represents the preprocessing cornerstone of such pixel-level techniques, so its performance warrants independent attention. The purpose of this study was to evaluate the performance of four between-subjects warping registration algorithms including: Principal Axes (PA), four-parameter Optimal Scaling (OS4), eight-parameter Optimal Projective (OP8), and locally affine Nonlinear (NL). Fifteen subjects performed 10 trials of self-paced walking, and their peak pressure images were registered within-subjects using an optimal rigid body transformation. The resulting mean images were then registered between-subjects using all four methods in all 210 (15x14) subject combinations. All registration methods improved alignment, and each method performed qualitatively well for certain image pairs. However, only the NL consistently performed satisfactorily because of disproportionate anatomical variation in toe lengths and rearfoot/forefoot width, for example. Using three independent image (dis)similarity metrics, MANOVA confirmed that the NL method yielded superior registration performance (p<0.001). These data demonstrate that nonlinear spatial warping is necessary for robust between-subject pedobarographic image registration and, by extension, robust homologous data comparison at the pixel level.

Grip width and the organization of force output.

The authors investigated the structure of force production and variability as a function of grip configuration and width during precision grasping. Variability was studied in absolute (standard deviation) and relative (coefficient of variation) terms; in addition, the authors used approximate entropy to examine regularity. In Experiment 1, the participants (N = 14) used a 2-digit grasp (thumb, index), whereas in Experiment 2, the participants (N = 11) used a 3-digit grasp (thumb, index, middle). The level and regularity of force increased with grip width. The amount of variability was least at narrow grip widths for 2-digit grasping and greatest at narrow grip widths for 3-digit grasping. That pattern of findings is not necessitated by the mechanical equilibrium of grasping; thus, it also reflected adaptive neural reorganization of force output to task demands.