Biomedical subjects

Laurent Bosquet

Publications and source records attributed to Laurent Bosquet.

5 recordsLinked to original sources

PubMed2006

Vmax estimate from three-parameter critical velocity models: validity and impact on 800 m running performance prediction.

The purpose of this study was to evaluate the validity of maximal velocity (Vmax) estimated from three-parameter systems models, and to compare the predictive value of two- and three-parameter models for the 800 m. Seventeen trained male subjects (VO2max=66.54+/-7.29 ml min(-1) kg(-1)) performed five randomly ordered constant velocity tests (CVT), a maximal velocity test (mean velocity over the last 10 m portion of a 40 m sprint) and a 800 m time trial (V 800 m). Five systems models (two three-parameter and three two-parameter) were used to compute V max (three-parameter models), critical velocity (CV), anaerobic running capacity (ARC) and V800m from times to exhaustion during CVT. Vmax estimates were significantly lower than (0.19<Bias<0.24 m s(-1)) and poorly associated (0.44<r<0.49) with actual Vmax (8.43+/-0.33 m s(-1)). Critical velocity (CV) alone explained 40-62% of the variance in V800m. Combining CV with other parameters of each model to produce a calculated V800m resulted in a clear improvement of this relationship (0.83<r<0.94). Three-parameter models had a better association (0.93<r<0.94) and a lower bias (0.00<Bias<0.04 m s(-1)) with actual V800 m (5.87+/-0.49 m s(-1)) than two-parameter models (0.83<r<0.91, 0.06<Bias<0.20). If three-parameter models appear to have a better predictive value for short duration events such as the 800 m, the fact the Vmax is not associated with the ability it is supposed to reflect suggests that they are more empirical than systems models.

Adult↗

PubMed2006

Validity of the polar S810 heart rate monitor to measure R-R intervals at rest.

PURPOSE: This study was conducted to compare R-R intervals and the subsequent analysis of heart rate variability (HRV) obtained from the Polar S810 heart rate monitor (HRM) (Polar Electro Oy) with an electrocardiogram (ECG) (Physiotrace, Estaris, Lille, France) during an orthostatic test. METHODS: A total of 18 healthy men (age: 27.1 +/- 1.9 yr; height: 1.82 +/- 0.06 m; mass 77.1 +/- 7.7 kg) performed an active orthostatic test during which R-R intervals were simultaneously recorded with the HRM and the ECG recorder The two signals were synchronized and corrected before a time domain analysis, the fast Fourier transform (FFT) and a Poincaré plot analysis. Bias and limits of agreement (LoA), effect size (ES), and correlation coefficients were calculated. RESULTS: R-R intervals were significantly different in the supine and standing position between the ECG and the HRM uncorrected and corrected signal (P < 0.05, ES = 0.000 and 0.006, respectively). The bias +/- LoA, however, were 0.9 +/- 12 ms. HRV parameters derived from both signals in both positions were not different (P > 0.05) and well correlated (r > 0.97, P < 0.05), except root mean square of difference (RMSSD) and SD1 in standing position (P < 0.05, ES = 0.052 and 0.057; r = 0.99 and 0.98, respectively). CONCLUSION: Narrow LoA, good correlations, and small effect sizes support the validity of the Polar S810 HRM to measure R-R intervals and make the subsequent HRV analysis in supine position. Caution must be taken in standing position for the parameters sensitive to the short-term variability (i.e., RMSSD and SD1).

Adult↗

PubMed2006

Prediction of one-hour running performance using constant duration tests.

Critical velocity (CV) represents, theoretically, the highest velocity that can be sustained without fatigue. The aim of this study was to compare CV computed from 5 mathematical models in order to determine which CV estimate is better correlated with 1-hour performance and which model provides the most accurate prediction of performance. Twelve trained middle- and long-distance male runners (29 +/- 5 years) performed 3 randomly ordered constant duration tests (6, 9, and 12 minutes), a maximal running velocity test for the estimation of CV, and a 1-hour track test (actual performance). Two linear, 2 nonlinear, and 1 exponential mathematical models were used to estimate CV and to predict the highest velocity that could be sustained during 1 hour (predicted performance). Although all CV estimates were correlated with performance (0.80 < r < 0.93, p < 0.01), it appeared that CV estimated from the exponential model was more closely associated with performance than all other models (r = 0.93; p < 0.01). Analysis of the bias +/- 95% interval of confidence between actual and predicted performance revealed that none of the models provided an accurate prediction of the 1-hour performance velocity. In conclusion, the estimation of CV allows us to rank middle- and long-distance runners with regard to their ability to perform well in long-distance running. However, no models provide an accurate prediction of performance that could be used as a reference for coaches or athletes.

Adult↗

PubMed2004

Effect of a 15% increase in preferred pedal rate on time to exhaustion during heavy exercise.

The aim of this study was to evaluate the effect of a 15% increase in preferred pedal rate (PPR) on both time to exhaustion and pulmonary O(2) uptake (VO(2)) response during heavy exercise. Seven competitive cyclists underwent two constant-power tests (CPT) at a power output that theoretically requires 50% of the difference in VO(2) between the second ventilatory threshold and VO(2)max (Pdelta50). Each cyclist cycled a CPT at PPR (CPTPPR) and a CPT at +15% of PPR (CPT+15%) in a randomized order. The average PPR value was 94 +/- 4 rpm, and time to exhaustion was significantly longer in CPTPPR compared with CPT+15% (465 +/- 139 vs. 303+/- 42 s, respectively; p = 0.01). A significant decrease in VO(2) values in the first minutes of exercise and a significant increase in VO(2) slow component was reported in CPT+15% compared with CPT(PPR). These data indicate that the increase of 15% PPR was associated with a decrease in exercise tolerance and a specific VO(2) response, presumably due to an increase of negative muscular work, internal work, and an altering of motor unit recruitment patterns.

Adult↗

PubMed2002

Methods to determine aerobic endurance.

Physiological testing of elite athletes requires the correct identification and assessment of sports-specific underlying factors. It is now recognised that performance in long-distance events is determined by maximal oxygen uptake (V(2 max)), energy cost of exercise and the maximal fractional utilisation of V(2 max) in any realised performance or as a corollary a set percentage of V(2 max) that could be endured as long as possible. This later ability is defined as endurance, and more precisely aerobic endurance, since V(2 max) sets the upper limit of aerobic pathway. It should be distinguished from endurance ability or endurance performance, which are synonymous with performance in long-distance events. The present review examines methods available in the literature to assess aerobic endurance. They are numerous and can be classified into two categories, namely direct and indirect methods. Direct methods bring together all indices that allow either a complete or a partial representation of the power-duration relationship, while indirect methods revolve around the determination of the so-called anaerobic threshold (AT). With regard to direct methods, performance in a series of tests provides a more complete and presumably more valid description of the power-duration relationship than performance in a single test, even if both approaches are well correlated with each other. However, the question remains open to determine which systems model should be employed among the several available in the literature, and how to use them in the prescription of training intensities. As for indirect methods, there is quantitative accumulation of data supporting the utilisation of the AT to assess aerobic endurance and to prescribe training intensities. However, it appears that: there is no unique intensity corresponding to the AT, since criteria available in the literature provide inconsistent results; and the non-invasive determination of the AT using ventilatory and heart rate data instead of blood lactate concentration ([La(-)](b)) is not valid. Added to the fact that the AT may not represent the optimal training intensity for elite athletes, it raises doubt on the usefulness of this theory without questioning, however, the usefulness of the whole [La(-)](b)-power curve to assess aerobic endurance and predict performance in long-distance events.

Exercise↗