RESUMEN
Aerobic and anaerobic thresholds of the three-zone exercise model are often used to evaluate the exercise intensity and optimize the training load. Conventionally, these thresholds are derived from the respiratory gas exchange or blood lactate concentration measurements. Here, we introduce and validate a computational method based on the RR interval (RRI) dynamics of the heart rate (HR) measurement, which enables a simple, yet reasonably accurate estimation of both metabolic thresholds. The method utilizes a newly developed dynamical detrended fluctuation analysis (DDFA) to assess the real-time changes in the dynamical correlations of the RR intervals during exercise. The training intensity is shown to be in direct correspondence with the time- and scale-dependent changes in the DDFA scaling exponent. These changes are further used in the definition of an individual measure to estimate the aerobic and anaerobic threshold. The results for 15 volunteers who participated in a cyclo-ergometer test are compared to the benchmark lactate thresholds, as well as to the ventilatory threshods and alternative HR-based estimates based on the maximal HR and the conventional detrended fluctuation analysis (DFA). Our method provides the best overall agreement with the lactate thresholds and provides a promising, cost-effective alternative to conventional protocols, which could be easily integrated in wearable devices. However, detailed statistical analysis reveals the particular strengths and weaknessess of each method with respect to the agreement and consistency with the thresholds-thus underlining the need for further studies with more data.
RESUMEN
This study focused on resolving the differences in economy between two common sit-skiing postures used by disabled athletes, suspected to be the most and least effective. Ten experienced non-disabled male cross-country skiers went through an incremental testing protocol with an ergometer simulating double poling in two sitting postures "kneeing" and "knee-high." The protocol consisted of 3 × 4 min steady-state stages (13, 22, and 34% of maximal sprint power output). Subjects' respiratory gases and heart rate were measured and blood lactate concentrations were determined. In addition, pulling forces and motion capture recordings were collected. Oxygen consumption was 15.5% (p < 0.01) higher with "knee-high" compared to "kneeing" at stage three. At stage three cycle rate was 13.8% higher (p < 0.01) and impulse of force 13.0% (p < 0.05) and hip range of motion 46.6% lower (p < 0.01) with "knee-high" compared to "kneeing." "Kneeing" was found to be considerably more economical than "knee-high" especially at 34% of maximum sprint power output. This might have been due to higher cycle rate, lower impulse of force and smaller hip range of motion with "knee-high" compared to "kneeing." This indicates that sit-skiers should adopt, if possible, posture more resembling the "kneeing" than the "knee-high" posture. Combining such physiological and biomechanical measurements and to further develop them to integrated miniature wearable sensors could offer new possibilities for training and testing both in the laboratory and in the field conditions.