Lincolnshire exercise referral evaluation

This document reports on evaluation work completed by the University of Lincoln through the School of Sport and Exercise Science. It examines data stored on the Lincolnshire Sports Partnership’s parachute system regarding patients attending Lincolnshire’s Exercise Referral (ER) Programme, a service funded by Public Health. The analysis was in response to specific questions determined by exercise practitioners, the Lincolnshire Sports Partnership and Public Health Lincolnshire. Data was analysed via a number of statistical methods including Chi-squared and Logistic Regression. The data spanned a period of 3.5 years and included all patients in the database starting a 12-week ER programme between 10th March 2009 through to 22nd August 2012. There were 6637 eligible patients, of which 62.3% completed a 12-week ER programme. Headline findings from the evaluative research identified; 1) There was a significant relationship between those patients who completed the referral programme and a reduction in body mass index (BMI); 2) Those patients completing nine or more (out of 12) weeks of the referral programme were significantly more likely to complete. The number of sessions within a week did not influence completion; 3) There was a significantly increased likelihood for those patients who pay for exercise referral to complete the programme. This was regardless of the deprivation score of their home postcode and 4) There was no significant relationship between the way a referral is initiated and a patient completing a referral programme. More than half of these data were missing; however, hence the validity of this finding is impaired. These findings were used to generate recommendations regarding the data that is currently collected via the parachute system and the processes that are employed by the ER programmes

METHODS FOR QUANTIFYING THE VARIABILITY IN DATA

Variability in movement affects statistical significance and is important for interpreting data. The aim of this study was to compare methods for quantifying variability, and to use these in assessing the effect of ‘pain’ in the right leg on the running technique of one male English First Division footballer. The player’s sagittal plane movements were filmed while running on a treadmill at 3.58 m.s-1. The variability in 3 strides was quantified using standard deviation, confidence intervals (95%CI) and root mean square difference (RMSD). The kinematics of the left and right legs of the player were different, but did not contain different amounts of variability (e.g. RMSD of both knees at heel strike = 1.2°). To estimate variability the preferred techniques are: 95%CI for n = 1 as the only available; RMSD for small n; normalised techniques only when means are similar. The variability of the player’s movements in other planes and at faster speeds should be explored in future

USING A BREAKPOINT TO DETERMINE THE OPTIMAL CUT-OFF FREQUENCY

The aims of this study were to compare methods of determining the optimal cut-off frequency (CFopt) for a Butterworth filter. CFopt were determined for leg displacement data for treadmill running through residual analysis using regression (RA0reg), integral of the power spectral density (PSD), and both these methods analysed through a new ‘breakpoint’ method. RA0reg did not correlate with other methods suggesting poor concurrent validity. The ‘breakpoint’ method correlated significantly between several methods. CFopt was least for anterio-posterior and highest for vertical directions for all methods (p\u3c0.05). Settings for RA0reg and PSD can have substantial effects on CFopt, but the ‘breakpoint’ is not affected as much by the settings. Future research should attempt to standardise settings and explore the criterion validity of the methods to determine CFopt

Error and Anomaly Detection for Intra-Participant Time-Series Data

Identification of errors or anomalous values, collectively considered outliers, assists in exploring data or through removing outliers improves the statistical analysis. In biomechanics, outlier detection methods have explored the ‘shape’ of the entire cycles, although exploring fewer points using a ‘moving-window’ may be advantageous. Hence, the aim was to develop a moving-window based method for detecting trials with outliers in intra-participant time-series data. The test data were the angles and displacements for the strides or cycles (mean 38 cycles) from treadmill running, with outliers detected through two-stages. Stage-1 was a one-dimensional (spatial) outlier detection at each time-point, where any data-value of a scaled median-absolute-deviation away from the median at that time-point led to removing that cycle. Stage-2 was a two-dimensional (spatial-temporal) outlier detection of a moving-window-standard-deviation (mwSD) across cycles and across the moving-window size (size of ± 0, 1, 2 or 3 time-points), where any data-value greater than the scaled mwSD led to removing that cycle. Scaling was performed using the t-statistic for three significance levels of 0.01, 0.001 or 0.0001. Fewer cycles were removed with smaller scaling and smaller window size. Appropriate settings were stage-1 scaling of 0.0001 (mean 3.5 cycles removed) and stage-2 scaling of 0.01 with a moving-window size of 1 (mean 2.6 cycles removed). Settings in the supplied Matlab code should be customised to each data set, and trials with outliers assessed to justify whether to retain or remove those trials. The method provides an effective method to identify trials with outliers in intra-participant time-series data

The clubhead and hand planes in golf draw and fade shots.

Swing planes in golf have become a popular area of research. Cochran and Stobbs (1968) examined the motion of the clubhead and hands qualitatively. Subsequent quantitative analyses have included investigations of the planarity of the whole club (Coleman & Anderson, 2007) and clubhead (Shin, Casebolt, Lambert, Kim, & Kwon, 2008). The aim of this study was to investigate the motion of the clubhead and hands in the downswing quantitatively, and to compare these motions for the fade and draw (as suggested by Coleman and Anderson, 2007). In conclusion, both the clubhead and hand planes in the late downswing were found to differ significantly in relation to the target line between the draw and fade shots. Greater differences were found between golfers, rather than between shots, in the relationship between the clubhead and hand motion during the downswing. Nevertheless, further detailed analysis is warranted of how the motions around impact – especially the clubface orientation – differ between the two types of shot

The clubhead swing plane in golf draw and fade shots

It has become popular to characterise a golf shot in terms of a ‘swing plane’. However Coleman and Anderson (2007) showed that the motion of the whole club in the downswing could not be represented by a single plane in all players. Shin et al. (2008) found that the clubhead motion was consistently planar between the club being horizontal in the downswing and follow-through. Coleman and Anderson (2007) also suggested that the club plane might differ between draw and fade shots. The purpose of this study was to compare draw and fade shots, with a focus on the clubhead motion in the late downswing. The late downswing clubhead plane differs between a draw and a fade shot, even when differences in address angles are accounted for

Determination of step rate thresholds corresponding to physical activity intensity classifications in adults

Current recommendations call for adults to be physically active at moderate and/or vigorous intensities. Given the popularity of walking and running, the use of step rates may provide a practical and inexpensive means to evaluate ambulatory intensity. Thus, the purpose of this study was to identify step rate thresholds that correspond to various intensity classifications. Methods: Oxygen consumption was measured at rest and during 10 minute treadmill walking and running trials at 6 standardized speeds (54, 80, 107, 134, 161, and 188 m∙min-1) in 9 men and 10 women (28.8 ± 6.8 yrs). Two observers counted the participants’ steps at each treadmill speed. Linear and nonlinear regression analyses were used to develop prediction equations to ascertain step rate thresholds at various intensities. Results: Nonlinear regression analysis of the metabolic cost versus step rates across all treadmill speeds yielded the highest R2 values for men (R2 = .91) and women (R2 = .79). For men, the nonlinear analysis yielded 94 and 125 step∙min-1 for moderate and vigorous intensities, respectively. For women, 99 and 135 step∙min-1 corresponded with moderate and vigorous intensities, respectively. Conclusions: Promoting a step rate of 100 step∙min-1 may serve as a practical public health recommendation to exercise at moderate intensity

QUANTIFYING COORDINATION IN KINEMATIC DATA: A RUNNING EXAMPLE

To compare methods of quantifying coordination, one healthy male participant was filmed in three dimensions at 120 Hz whilst running at 3.8 m/s. The knee and hip angles and angular velocities of the left stride, normalised to 100 data points, were analysed using continuous relative phase (CRP) and cross correlations (CC). The phase planes were normalised to -1 and +1, and the component phase angles (I) for each segment calculated with the range O°<

A SIMPLE OUTLIER DETECTION METHOD FOR INTRA-SUBJECT TIME-SERIES DATA

Removal of outliers assists in improving the statistical representations of the general finding. Currently no simple method is advocated for detecting outliers in time-series data obtained in biomechanics. The aim was to demonstrate a 2-stage method for detecting outliers. The test data were the ankle and knee angles for the strides (n=41±2.8) from treadmill running (n=6). Stage 1 was an outlier detection of >±3.3SD from the mean at each time-point, and removing any stride with an outlier. Stage 2, with padding of k=3 points and mean-detrending, was a moving window SD for all strides across ±k data points, and removing strides with any point >±2.58SD. After removal of 5.2±3 (stage 1) and 2.0±1.4 (stage 2) strides, the mean was unchanged and the SD reduced (

Stability of handwriting performance following injury-induced hand dominance transfer in adults: a pilot study

The aim of this study was to quantify stability of nondominant handwriting kinematics and legibility in participants with functional loss of the previously dominant hand. Twelve adult volunteers provided two handwriting samples 6 weeks apart. Handwriting tasks (Compose a Sentence, Copy Alphabet, Copy Date, Copy Sentence, and Draw Circles) were performed in cursive writing on standard white, lined paper taped to a digitizer to record kinematic and kinetic variables of velocity, displacement, force, and on-paper time. Results showed minimal performance variability within subjects and marked variability between subjects, as well as variability between tasks for all participants. Stylistic stability of the handwriting samples was assessed by two independent evaluators. These evaluators matched all handwriting samples at test to retest times with 89%–100% accuracy, suggesting value in the “whole” handwriting sample and emphasizing the idiosyncratic nature of handwriting. Results suggest that handwriting skill stability in the previously nondominant hand varies across subjects and task demands