Mechanical, Metabolic, and Perceptual Acute Responses to Different Set Configurations in Full Squat

Abstract

This study aimed to compare mechanical, metabolic, and perceptual responses between two traditional (TR) and four cluster (CL) set configurations. In a counterbalanced randomized order, 11 men were tested with the following protocols in separate sessions (sets × repetitions [inter-repetition rest]): TR1: 3×10 [0-s]; TR2: 6×5 [0-s]; CL1: 3×10 [10-s]; CL2: 3×10 [15-s]; CL3: 3×10 [30-s]); CL4: 1×30 [15-s]). The exercise (full-squat), number of repetitions (30), inter-set rest (5 min), and resistance applied (10RM) was the same for all set configurations. Mechanical fatigue was quantified by measuring the mean propulsive velocity during each repetition, and the change in countermovement jump height observed after each set and after the whole training session. Metabolic and perceptual fatigue were assessed via the blood lactate concentration and the OMNI perceived exertion scale measured after each training set, respectively. The mechanical, metabolic, and perceptual measures of fatigue were always significantly higher for the TR1 set configuration. The two set configurations that most minimized the mechanical measures of fatigue were CL2 and CL3. Perceived fatigue did not differ between the TR2, CL1, CL2 and CL3 set configurations. The lowest lactate concentration was observed in the CL3 set configuration. Therefore, both the CL2 and CL3 set configurations can be recommended because they maximize mechanical performance. However, the CL2 set configuration presents two main advantages with respect to CL3: (1) it reduces training session duration, and (2) it promotes higher metabolic stress, which to some extent may be beneficial for inducing muscle strength and hypertrophy gains.

Acute mechanical, physiological and perceptual responses in older men to traditional-set or different cluster-set configuration resistance training protocols

“…In particular, power output decrements observed across consecutive sets during the TRA protocol, may have been caused by an acute increase in metabolic stress. This hypothesis is in agreement with previous studies, in which traditional-set configurations similar to the one used in this study led to greater blood lactate concentration and the consequent inability to maintain optimal power outputs (Girman et al 2014 ; González-Hernández et al 2020 ; Gorostiaga et al 2014 , 2010 ). As a result, prescribing resistance training using cluster-set configurations with low repetition numbers may help to avoid these detrimental metabolic effects and provide a greater stimulus for power enhancement adaptations than resistance training using traditional-set configuration and clusters of many repetitions.…”

“…Interestingly, cluster-sets also allow greater power output when compared to matched protocols loaded with the same OPL but designed as traditional-set configurations (Dello Iacono et al 2019 ). The cumulative beneficial effects of OPL and cluster-set configurations on power output likely stem from psychophysiological (González-Hernández et al 2020 ) and metabolic (Gorostiaga et al 2014 , 2010 ) mechanisms resulting in lower perceived effort and reduced acute muscular fatigue (Tufano et al 2016 , 2017 ). Furthermore, the rest interval between consecutive clusters significantly affects cardiovascular load (Fleck 1988 , 2003 ; Kraemer et al 1987 ), with very short rest periods (i.e.…”

Differences between adjusted vs. non-adjusted loads in velocity-based training: consequences for strength training control and programming

“…These findings may indicate that a stimulus characterized by a low degree of induced fatigue (NAL) and high velocity of the repetitions within the set may be enough to induce strength adaptations in a non-experienced population. Several studies have reported the effects of VL on strength gains (Pareja-Blanco et al, 2017b;González-Hernádez et al, 2020), highlighting the usefulness of VBT in RT. These studies have been performed considering 1RM as a reference to prescribe the RI for each training session, adjusting absolute loads to the corresponding pre-programmed RI.…”

Assessment of the load-velocity profile in the free-weight prone bench pull exercise through different velocity variables and regression models

“…Furthermore, improved affordability and availability of technology has enabled the development of new training methodologies such as "velocity-based resistance training" [3–5]. Velocity-based resistance training requires the measurement of velocity in real-time and provides at least three important practical applications: (I) load can be adjusted on a daily basis to match the desired intensity (commonly expressed as a percentage of the one-repetition maximum; 1RM) due to the strong relationship between movement velocity and the load lifted [6,7], (II) the volume of the training session (e.g., the number of exercises per session, sets per exercise or repetitions per set) can be prescribed based off the magnitude of velocity loss due to its close relationship with markers of fatigue [8,9], and (III) the administration of real-time velocity feedback improves motivation and enables the maintenance of higher movement velocities during resistance training, which in turn may stimulate long-term training adaptations [10,11]. Despite these encouraging applications, many aspects related to the velocity-based resistance training approach still need to be investigated to facilitate and optimize the application of this novel strength-training methodology.…”