This study presents a new approach for automated identification of ice hockey skating strides and a method to detect ice contact and swing phases of individual strides by quantifying vibrations in 3D acceleration data during the blade–ice interaction. The strides of a 30-m forward sprinting task, performed by 6 ice hockey players, were evaluated using a 3D accelerometer fixed to a hockey skate. Synchronized plantar pressure data were recorded as reference data. To determine the accuracy of the new method on a range of forward stride patterns for temporal skating events, estimated contact times and stride times for a sequence of 5 consecutive strides was validated. Bland-Altman limits of agreement (95%) between accelerometer and plantar pressure derived data were less than 0.019 s. Mean differences between the 2 capture methods were shown to be less than 1 ms for contact and stride time. These results demonstrate the validity of the novel approach to determine strides, ice contact, and swing phases during ice hockey skating. This technology is accurate, simple, effective, and allows for in-field ice hockey testing.
Bernd J. Stetter, Erica Buckeridge, Vinzenz von Tscharner, Sandro R. Nigg, and Benno M. Nigg
Maurice Mohr, Matthieu B. Trudeau, Sandro R. Nigg, and Benno M. Nigg
To determine the effect of shoe mass on performance in basketball-specific movements and how this affects changes if an athlete is aware or not of the shoe’s mass relative to other shoes.
In an experimental design, 22 male participants were assigned to 2 groups. In the “aware” group, differences in the mass of the shoes were disclosed, while participants in the other group were blinded to the mass of shoes. For both groups lateral shuffle-cut and vertical-jump performances were quantified in 3 different basketball-shoe conditions (light, 352 ± 18.4 g; medium, 510 ± 17 g; heavy, 637 ± 17.7 g). A mixed ANOVA compared mean shuffle-cut and vertical-jump performances across shoes and groups. For blinded participants, perceived shoeweight ratings were collected and compared across shoe conditions using a Friedman 2-way ANOVA.
In the aware group, performance in the light shoes was significantly increased by 2% (vertical jump 2%, P < .001; shuffle cut 2.1%, P < .001) compared with the heavy shoes. In the blind group, participants were unable to perceive the shoe-weight variation between conditions, and there were no significant differences in vertical-jump and shuffle-cut performance across shoes.
Differences in performance of the aware participants were most likely due to psychological effects such as positive and negative expectancies toward the light and heavy shoes, respectively. These results underline the importance for coaches and shoe manufacturers to communicate the performance-enhancing benefits of products or other interventions to athletes to optimize their performance outcome.