Gymnastik- och idrottshögskolan, GIH

Background

The emergence of wearable technology offers enhanced real-time health management, including sleep, recovery, and exercise optimization. Despite their potential to monitor load-recovery parameters in elite athletes, the selection, combination, and interpretation or reliance of metrics in relation to perceived impact remain unclear.

Objective

This study assessed data from three wearables measuring sleep, continuous glucose, and exercise, together with the Profile of Mood State (POMS) dimensions alongside subjective ratings via the Readiness Advisor application (RA app) (Silicon Valley Exercise Analytics, svexa, Menlo Park, California, USA) to evaluate their association and value in load-recovery monitoring.

Methods

Twenty national team endurance athletes, competing at the highest international level, were monitored during one year of training, recovery, and competitions. Data collections were made with Global Positioning System (GPS) watches and heart rate monitors, & Ōura rings (Ōura Health OY, Oulu, Finland), continuous glucose monitors, POMS questionnaires and subjective ratings in the RA app.

Results

Significant correlations were found between each RA question and its counterpart in a linear mixed model (r values = 0.39-0.81). However, time series analysis through autoregressive integrated moving average (ARIMA analysis) revealed individual variability.

Conclusions

These findings indicate an influence of external aspects and advocate for a multifaceted approach to the assessment of load-recovery balance, well-being and performance. Moreover, personalized analyses proved more accurate than group averages, emphasizing the need for individualized monitoring. Integrating subjective and objective data appears essential for nuanced understanding of the athlete status, advancing high-performance monitoring and athletic health management.