Percorrer por autor "Fitas, Afonso"
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- Bench-press performed with a velocity- and tempo-based approach : are there differences in volume load, time under tension, and metabolic demands?Publication . Fitas, Afonso; Miras-Moreno, Sérgio; Oliveira, João Henriques; Cidrais, Margarida; Pezarat-Correia, Pedro; Schoenfeld, Brad J.; Mendonça, Gonçalo V.Background: Velocity-based training (VBT) is a resistance training approach that uses lifting velocity to determine training load and track strength progress. This study determined the impact of a VBT versus a tempo-based training (TBT) approach on volume load and time under tension during a single set of submaximal bench press performed to failure. Hypothesis: VBT would result in larger volume load and similar time under tension as TBT. Study Design: Randomized-crossover design. Level of Evidence: Level 3. Methods: A total of 14 healthy men (24.1 ± 5.8 years) performed free-weight bench-press exercise at low intensities (12%, 16%, 20%, and 24% of 1-repetition maximum [1RM]) with oxygen uptake (V.O2) measurements. V.O2 was then extrapolated to a set performed at 70% 1RM to failure and the accumulated O2 deficit was calculated together with the relative energy contribution of aerobic and anaerobic metabolism. Mechanical data were collected with a linear encoder. Results: Despite the lack of differences between conditions for total time under tension (P > 0.05), VBT achieved a higher volume load at set failure (P < 0.05). Moreover, the VBT condition resulted in a larger total V.O2 from set initiation to termination (P < 0.01). Conversely, the accumulated O2 deficit did not differ between conditions (P > 0.05). Compared with TBT, VBT elicited a higher relative contribution of aerobic energy (VBT, ~41%; TBT, 33%) and a lower relative contribution of anaerobic energy (VBT, ~59; TBT, 67%) during exercise (P < 0.01). Conclusion: VBT is an effective strategy to enhance volume load during bench-press performed to failure at 70% 1RM. This effect occurs without compromising time under tension. These findings are associated with a higher contribution of aerobic energy supply to exercise. Clinical Relevance: VBT may be beneficial for athletes aiming to maximize volume load in response to resistance exercise.
- Impact of the optimal minimum velocity threshold on the accuracy of one repetition maximum estimation-based on a mixed modelPublication . Fitas, Afonso; Gomes, Miguel; Santos, Paulo; Vila-Chã, Carolina; Pezarat-Correia, Pedro; Mendonça, Gonçalo V.Purpose: This study aimed at developing two mixed methods approaches for 1RM prediction (generalized equations together with the individual load–velocity relationship—LVR). The validity of such equations was explored and compared with the validity of individual LVRs. Methods: The submaximal LVRs of seventy-six males was obtained for the free-weight back squat. Theoretical load at zero velocity (LD0), the slope of the individual LVR, and the individual (ModelIND) and optimal minimum velocity thresholds (MVT) (ModelOPT) were selected to develop the equations. Prediction accuracy was determined through mean differences, absolute percent errors and Bland–Altman plots. Results: ModelIND was predictive of 1RM (p < 0.0001), explaining 89.7% of its variance. ModelOPT increased the prediction power of 1RM to 98.7% (p < 0.0001). No significant differences in the absolute percent errors were found (4.7 and 3.9%, for ModelIND and ModelOPT, respectively). The mean difference between actual and estimated 1RM was nearly zero for both models, while individual LVRs relying on the individual MVT displayed the contrary. The limits of agreement were 15.1 and 11.4 kg for ModelIND and ModelOPT, respectively. Conclusion: The individual and optimal MVTs add predictive value to LD0 and the slope of the individual LVR for 1RM estimation on a group level and avoid error trends over the entire muscular strength spectrum. However, only ModelIND increased the accuracy of estimations when compared with the more direct approach. From a practical standpoint, practitioners are encouraged to rely on the individual LVR instead of ModelOPT, when using the optimal MVT for estimation purposes.