EMG evaluation of hip adduction exercises for soccer players: implications for exercise selection in prevention and treatment of groin injuries

This brief review examines some of the methods used to infer central control strategies from surface electromyogram (EMG) recordings. Among the many uses of the surface EMG in studying the neural control of movement, the review critically evaluates only some of the applications. The focus is on the relations between global features of the surface EMG and the underlying physiological processes. Because direct measurements of motor unit activation are not available and many factors can influence the signal, these relations are frequently misinterpreted. These errors are compounded by the counterintuitive effects that some system parameters can have on the EMG signal. The phenomenon of crosstalk is used as an example of these problems. The review describes the limitations of techniques used to infer the level of muscle activation, the type of motor unit recruited, the upper limit of motor unit recruitment, the average discharge rate, and the degree of synchronization between motor units. Although the global surface EMG is a useful measure of muscle activation and assessment, there are limits to the information that can be extracted from this signal.

Previous injury is often proposed to be a risk factor for football injury, but most studies rely on players reporting their own medical history and are thus potentially subject to recall bias. Little is known about the natural variation in injury pattern between seasons. To study whether prospectively recorded injuries during one season are associated with injuries sustained during the following season, and to compare injury risk and injury pattern between consecutive seasons. The medical staffs of 12 elite Swedish male football teams prospectively recorded individual exposure and time loss injuries over two full consecutive seasons (2001 and 2002). A multivariate model was used to determine the relation between previous injury, anthropometric data, and the risk of injury. The training and match injury incidences were similar between seasons (5.1 v 5.3 injuries/1000 training hours and 25.9 v 22.7/1000 match hours), but analysis of injury severity and injury patterns showed variations between seasons. Players who were injured in the 2001 season were at greater risk of any injury in the following season compared with non-injured players (hazard ratio 2.7; 95% confidence interval 1.7 to 4.3, p<0.0001). Players with a previous hamstring injury, groin injury, and knee joint trauma were two to three times more likely to suffer an identical injury in the following season, whereas no such relation was found for ankle sprain. Age was not associated with an increased injury risk. This study confirmed previous results showing that previous injury is an important risk factor for football injury. Overall injury incidences were similar between consecutive seasons, indicating that an injury surveillance study covering one full season can provide a reasonable overview of the injury problem among elite football players in a specific environment. However, a prolonged study period is recommended for analyses of specific injury patterns.

The identification of a quantifiable dose-response relationship for strength training is important to the prescription of proper training programs. Although much research has been performed examining strength increases with training, taken individually, they provide little insight into the magnitude of strength gains along the continuum of training intensities, frequencies, and volumes. A meta-analysis of 140 studies with a total of 1433 effect sizes (ES) was carried out to identify the dose-response relationship. Studies employing a strength-training intervention and containing data necessary to calculate ES were included in the analysis. ES demonstrated different responses based on the training status of the participants. Training with a mean intensity of 60% of one repetition maximum elicits maximal gains in untrained individuals, whereas 80% is most effective in those who are trained. Untrained participants experience maximal gains by training each muscle group 3 d.wk and trained individuals 2 d.wk. Four sets per muscle group elicited maximal gains in both trained and untrained individuals. The dose-response trends identified in this analysis support the theory of progression in resistance program design and can be useful in the development of training programs designed to optimize the effort to benefit ratio.