Transforming the performance of runners with AI-driven training planning and daily adaptivity
L. C. Nilsson, O. Sodergard, J. Rogestedt, C. M. Mattsson, F. J. Larsen
Abstract
Balancing intense training with adequate recovery is key for optimal athlete performance. While insufficient or excessive training can adversely impact performance, advancements in wearable technology facilitate more effective monitoring of training and readiness level. This study combined data from Garmin watches and a 9-item questionnaire (Readiness Advisor) application to evaluate the readiness during a 39-day long training period. Two groups were studied: one with daily adaptive modifications of the training according to their readiness level and another with a static regimen where no changes were made regardless of readiness level. Results indicated that the adaptive group maintained a more consistent readiness score and showed improved physiological responses and better performance metrics. In contrast, the static group displayed non-significant improvements. This suggests that adaptive training plans, driven by individualized data and AI analytics, can significantly enhance performance outcomes and physiological adaptations for runners.
02 /Specification & Classification
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