ABSTRACT
Improvements in running economy (RE) are thought to lead to improvements in running performance (P). Multiple interventions have been designed with the aim of improving RE in middle and long-distance runners. The aim of this study was to assess the effect of interventions of at least 2-weeks' duration on RE and P and to determine whether there is a relationship between changes in RE (ΔRE) and changes in running performance (ΔP). A database search was carried out in Web of Science, Scopus and SPORTDiscus. In accordance with a PRISMA checklist 10 studies reporting 12 comparisons between interventions and controls were included in the review. There was no correlation between percentage ΔRE and percentage ΔP (r = 0.46, P = 0.936, 12 comparisons). There was a low risk of reporting bias but an unclear risk of bias for other items. Meta-analyses found no statistically significant differences between interventions and controls for RE (SMD (95% CI) = -0.37 (-1.43, 0.69), 204 participants, p = 0.49) or for P (SMD (95% CI) = -0.65 (-26.02, 24.72, 204 participants, p = 0.99). There is a need for studies of greater statistical power, methodological quality, duration and homogeneity of intervention and population. Standardised measures of performance and greater control over non-intervention training are also required.
Subject(s)
Athletic Performance/physiology , Energy Metabolism , Physical Conditioning, Human/methods , Running/physiology , Humans , Oxygen Consumption , Pulmonary Gas Exchange , Time FactorsABSTRACT
Abstracttrasonic transducers (CUTs) with curved backplates was used to acquire signals through regions of air containing solid objects, air flow, and temperature fields. Fan-beam datasets were collected and used in a tomographic reconstruction algorithm to produce cross-sectional images of the area under interrogation. In the case of the solid objects, occluded rays from the projections were accounted for using a compensation algorithm and a priori knowledge of the object. A rebinning routine was used to pick out parallel ray sets from the fan-beam data. The effects of further reducing the number of datasets also were investigated, and, in the case of imaging solid objects, characteristic Gibbs phenomena were seen in the reconstructions as expected. However, when imaging temperature and flow fields, the aliasing artefacts were not seen, but the reconstructed values decreased with the size of dataset used. The effect of changing the kernel filter function also was investigated, with the different filters giving the best compromise between image noise, reconstruction accuracy, and amount of data required in each scenario.