Authors
Noemí Sempere-Ruiz, Agustín Manresa-Rocamora, Ana Sanz-Rocher, Sabina Baladzhaeva, Laura Fuertes-Kenneally, Manuel Moya-Ramón, Olaf Hoos, José M Sarabia
Published in
European journal of sport science. Volume 26. Issue 11. Pages e70271.
Abstract
This study investigated the applicability of the short-term scaling exponent alpha 1 of detrended fluctuation analysis (DFA-a1) as a marker of internal load during constant-load cycling. The aim was to explore DFA-a1 dynamics across the moderate, heavy, and severe intensity domains and assess its utility for both monitoring and prescribing exercise intensity. Sixteen untrained adults (3 women) performed an incremental cycling stage test and three constant-load sessions (moderate, heavy, and severe). Gas exchange kinetics, blood lactate concentration, and heart rate (HR) were measured. Ventilatory (VTs), lactate, and HR variability (HRV) thresholds were determined and used to define training zones. A two-factor repeated-measures ANOVA and the Friedman test assessed intensity- and method-related effects. Significant intensity × time interactions were observed for all variables (p < 0.001). DFA-a1 remained stable without crossing the first HRV threshold throughout moderate exercise, while in the heavy and severe domains, it showed a drift over time, mirroring the behaviour of traditional markers. In the moderate session, DFA-a1-based prescription maintained > 94% session time and 87%-100% of participants within the desired zone, outperforming HR methods based on VTs (71% time, 50%-81% participants; p < 0.05). In the heavy and severe domains, corresponding values were > 23% and > 50%, whereas gas exchange or lactate prescriptions exceeded 44% and 65%, respectively (p < 0.01). DFA-a1 appears to be a suitable tool for monitoring internal load, especially in moderate intensity exercise. It offers a non-invasive, integrative measure sensitive to both intensity and duration, providing a valuable complementary perspective on systemic regulation.
PMID:
42886162
Bibliographic data and abstract were imported from PubMed on 16 Oct 2026.
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