Andrew Lyttle

Net forces during tethered simulation of underwater streamlined gliding and kicking techniques of the freestyle turn

Weassessed the net forces created when towing swimmers while gliding and kicking underwater to establish an appropriate speed for initiating underwater kicking, and the most effective gliding position and kicking technique to be applied after a turn. Sixteen experienced male swimmers of similar body shape were towed by a motorized winch and pulley system. A load cell measured net force (propulsive force - drag force) at speeds of 1.6, 1.9, 2.2, 2.5 and 3.1 m· s-1 . At each speed, the swimmers performed a prone streamline glide, a lateral streamline glide, a prone freestyle kick, a prone dolphin kick and a lateral dolphin kick. A two-way repeated-measures analysis of variance revealed significant differences between the gliding and kicking conditions at different speeds. The results demonstrated an optimal range of speeds (1.9 to 2.2 m· s-1 ) at which to begin underwater kicking to prevent energy loss from excessive active drag. No significant differences were found between the prone and lateral streamline glide positions or between the three underwater kicking techniques. Therefore, there appears to be no significant advantage in using one streamlining technique over another or in using one kicking style over another.

Rowing: The RowPerfect Ergometer: a training aid for on‐water single scull rowing

Abstract The purpose of this study was to compare rowing technique on the dynamic RowPerfect ergometer with a single scull. Eight national‐level rowers performed on both the RowPerfect ergometer and in a single scull over 500 m, at rates of 24, 26, and 28 strokes/minute. Blade force and oar angle (on‐water) and handle force and stroke length (on the ergometer) were measured. Both force and stroke angle/length were normalised from 0 to 100 (where 100 was the peak value). Body positions of the subjects at both the catch and finish of each of these rowing strokes were also compared for each stroke rate. The coefficient of multiple determination (CMD) was used to measure the consistency of force curves over a sample of five sequential strokes for each rower. Cross‐correlations were performed between the left‐ and right‐ side on‐water sculling force curves and a mean of these values with the ergometer curve for each rower. Stroke angle/length, which did not vary with rate, was similar for both forms of rowing. The CMDs showed a high consistency across the normalised strokes of each subject (≈0.98). Cross‐correlation values of 0.91, 0.92, and 0.93 were recorded between the force curves from the ergometer and on‐water trials for stroke rates of 24, 26, and 28 strokes/minute, respectively. The mean trunk, thigh and lower leg angles at the catch and finish of the stroke were also similar across the stroke rates as determined by t‐tests. Results indicate that technique used on the RowPerfect ergometer was similar to that for on‐water sculling, thus validating its use in off‐water training.The purpose of this study was to compare rowing technique on the dynamic RowPerfect ergometer with a single scull. Eight national-level rowers performed on both the RowPerfect ergometer and in a single scull over 500 m, at rates of 24, 26, and 28 strokes/minute. Blade force and oar angle (on-water) and handle force and stroke length (on the ergometer) were measured. Both force and stroke angle/length were normalised from 0 to 100 (where 100 was the peak value). Body positions of the subjects at both the catch and finish of each of these rowing strokes were also compared for each stroke rate. The coefficient of multiple determination (CMD) was used to measure the consistency of force curves over a sample of five sequential strokes for each rower. Cross-correlations were performed between the left- and right-side on-water sculling force curves and a mean of these values with the ergometer curve for each rower. Stroke angle/length, which did not vary with rate, was similar for both forms of rowing. The CMDs showed a high consistency across the normalised strokes of each subject (approximately 0.98). Cross-correlation values of 0.91, 0.92, and 0.93 were recorded between the force curves from the ergometer and on-water trials for stroke rates of 24, 26, and 28 strokes/minute, respectively. The mean trunk, thigh and lower leg angles at the catch and finish of the stroke were also similar across the stroke rates as determined by t-tests. Results indicate that technique used on the RowPerfect ergometer was similar to that for on-water sculling, thus validating its use in off-water training.

Performance Tolerance and Boat Set-up in Elite Sprint Kayaking

Abstract The aim of this study was to examine the inter‐relationship between athlete morphology, equipment set‐up and performance in elite sprint kayaking. Correlations applied to data from the 2000 Olympics were used to select the most important links between morphology and boat set‐up — paddle grip width and foot‐bar distance. Associations between body size and the above selected equipment set‐ups were calculated using a Pearson correlation matrix, to facilitate the logical selection of independent variables as input for regression analyses. Significant (p < 0.01) regression equations were developed for the prediction of foot‐bar distance (r2 = 0.589: standard error of estimate (SEE) = 4.48) and paddle grip width (r2 = 0.541: SEE = 3.08). Three national‐standard sprint kayakers used their preferred set‐up together with modifications of their predicted set‐up, derived from Olympic data, to test performance tolerance in sprint kayaking. Mean coefficients of multiple determination over three trials for the three paddlers of 0.91, 0.91 and 0.92 for left paddle force, right paddle force, and paddle angle at water entry, respectively, were recorded when using their preferred set‐up. These data showed that the paddlers produce consistent patterns of motion. The intervention of altering the boat set‐up resulted in varying changes to boat speed. The mean preferred speed for the three paddlers of 4.47 m/s was reduced by 0.07 and 0.10 m/s when the above boat set‐up was modified to a predicted and ‘predicted plus one standard deviation’ respectively. These changes in boat speed were the result of alterations in the mechanics of paddling technique.

Comparison of force-related performance indicators between heavyweight and lightweight rowers

The aim of this study was to examine biomechanical variables relating to the force production of mens Lightweight (LW) and Heavyweight (HW) rowing pairs. Seven HW and seven LW coxless pairs were studied under a range of stroke rates, from 20 spm to race rating (average of 33.7 spm for the HWs and 33.9 spm for the LWs). Each crew was equipped with biomechanical apparatus allowing the measurement of gate force, horizontal oar angle, and boat velocity. The HW crews exhibited significantly higher (p < 0.05) values for all variables examined, at all rates. Peak handle force was 26.2% to 30.2% higher in the HW group. Average handle force ranged from 18.7% to 22.1% higher than the LW group. Work per stroke was found to be 26% to 28% higher for the HW crews, and Power Per Kilogram was also greater for the HW crews, from 24.0% to 29.2%. The LWs were observed to be consistently, but not significantly, slower than the HWs (from 96.9% at the race situation, to 98.7% at 28 spm). These observations are important when considering biomechanical performance indicators in rowing, as significant changes in performance indicators may lead to only minimal alteration in boat velocity.

A low cost 3D markerless system for the reconstruction of athletic techniques

We present a low cost markerless system for the optimization of athlete performance in sports such as pole vault, jumping and javelin throw. The system uses a number of calibrated cameras to capture a video of an athlete from different viewpoints. The athletes body is then segmented from the background in each video frame. The silhouettes of the segmented body are then reprojected to reconstruct an estimate of the 3D body shape of the athlete, known as the visual hull (VH). The VH is tracked over a number of frames in real testing trials. A template combining a high resolution 3D scan and a 2D mass scan is then aligned with the VH in each frame. A set of motion analysis parameters such as the take-off data are finally estimated from the aligned template and compared with the ones obtained using a gold standard marker-based system, namely the Vicon. The proposed system was tested in real-time trials and was able to provide comparable results to the Vicon system.