Lumbopelvic-hip Complex Contribution During Lower Extremity Screening Tests In Elite Figure Skaters

Abstract

The use of wearable technology may provide useful insight to training using live feedback, and the use of multiple devices may provide a more comprehensive view of training differences. PURPOSE: The purpose of this study was to compare the efficacy of wearable technology in determining performance variables in endurance runners while running against varying levels of wind resistance. METHODS: 10 trained endurance runners (4 females, 6 males) were recruited for this study and were currently running at least 120 min/week for the past 3 months. Participants completed 2 sessions: preliminary testing included a VO2peak protocol, the test session involved a 20-min run at 70% VO2peak. The 20 minutes was divided into 10 min of no wind resistance (W0), and 10 min with a wind resistance of 10 mph (W10). Both sessions were performed at least 2 hours fasted, at the same time of day, and following the same dietary intake prior to each session. Power was calculated using a power meter, and muscle load (ML) of the quadriceps, glutes, and hamstrings were measured using EMG sensor-embedded compression shorts. HR was monitored via HR monitor. RER, VO2 were monitored using a metabolic cart. The middle 5 minutes were analyzed for session means to avoid non steady-state measures associated with beginning exercise and anticipation of completion. Paired t-tests were used to compare differences between wind resistances for all variables. Pearson correlations were conducted between power and ML for each segment. Significance was set at p<0.05. RESULTS: There were no significant differences between ML, RER, HR, or VO2 (p>0.119) between segments. There was a significant difference for power, with W10 greater than W0 (334.4±62.9 vs. 349.1±69.7 W; p=0.002). There were also strong correlations for power and ML for W0 (r =0.727; p=0.017) and a trend in W10 (r=0.630; p=0.051). CONCLUSIONS: The significant differences observed in power indicates the use for a power meter to differentiate between wind resistance. Additionally, there appears to be a significant correlation between power and ML, despite no significant changes in ML. These results suggest the combination of these two wearables may help determine changes in performance metrics in fluctuating conditions that can influence the physiological toll in a runner.