Cluster Set Resistance Training Reduces Autonomic Perturbations Compared to Traditional Protocols in Trained Healthy Young Individuals: A Clinical Study

Abstract

Objectives: This study investigates the effects of cluster set resistance training (RT) on heart rate variability (HRV) parameters in young, healthy individuals. Methods: This trial was registered in the Brazilian Clinical Trials Registry (ReBEC) under the identification number RBR-9857xj3 on 7 December 2024. Sixteen participants (seven female, 25 ± 2 years old) performed both cluster set and traditional RT protocols with equal relative intensity (85% 10RM), volume load (4 × 10 repetitions), and rest intervals (120 s). Cluster set configuration involved the introduction of a shorter rest interval between a cluster of sets [4 × (2 × 5) with 90 s inter-set rest and 30 s intra-set rest]. HRV parameters (RMSSD, HFnu, SD1, LFnu, LF/HF ratio, and SD2) were assessed before and 30 min post-exercise. The rating of perceived exertion (RPE) was assessed immediately after RT protocols. Results: The traditional RT protocol led to a significant reduction in parasympathetic activity (RMSSD, HFnu, SD1) and an increase in sympathetic activity (LFnu, LF/HF ratio, and SD2) (p < 0.05), whereas the cluster set RT protocol did not alter HRV parameters. Additionally, RPE was significantly higher (p < 0.001) in the traditional RT protocol. Conclusion: This study suggests that the cluster set may have a less pronounced impact on HRV parameters 30 min post-exercise compared to traditional sets. These findings can guide exercise physiologists in designing resistance training programs for clinical populations by prescribing protocols that minimize cardiac autonomic stress.

1. Introduction

Cardiovascular disease (CVD) is the leading cause of death worldwide [1]. The autonomic nervous system, through its sympathetic and parasympathetic branches, plays a major role in modulating cardiac function [2]. Oscillations in the time interval between heartbeats (R-R intervals derived from an electrocardiogram) result from complex interactions between sympathetic and parasympathetic influences on the heart [3]. Therefore, heart rate variability (HRV) serves as a non-invasive tool to assess the autonomic regulation of the heart. HRV is considered a reliable marker of autonomic nervous system activity because it reflects the dynamic balance between sympathetic and parasympathetic modulation of the sinoatrial node, providing insights into the heart’s adaptability to various physiological demands [3,4,5]. Reduced HRV (indicative of higher sympathetic activation) is associated with inadequate cardiovascular adaptation and an increased risk of arrhythmias and sudden cardiac death [6,7]. Mechanistically, diminished HRV reflects impaired vagal tone and heightened sympathetic dominance, which may lead to electrical instability in cardiac tissue. This imbalance facilitates the emergence of ventricular arrhythmias through mechanisms such as increased myocardial excitability, shortened refractory periods, and triggered activity, especially under conditions of physiological stress or ischemia [8]. Conversely, higher HRV reflects a healthy state of autonomic control and an adaptive organism [7]. In this context, assessing HRV parameters after exercise is a valuable tool for investigating cardiac stress induced by a physical exercise session, particularly in individuals at risk for CVD [9].

Resistance training (RT), a form of exercise that involves lifting external loads to generate muscle force and hypertrophy, has been shown to improve various health outcomes, including muscle strength, power, endurance, bone mineral density, and cardiovascular adaptation [10,11]. These benefits depend on appropriate intensity (a percentage of maximal capacity) and volume (the number of repetitions performed) [12]. However, high-intensity RT may reduce parasympathetic activity and increase sympathetic activation for up to 30 min post-exercise, potentially elevating the risk of sudden cardiac death [6,13,14]. In this context, recent studies have sought to attenuate parasympathetic withdrawal by modifying RT variables such as set configuration and rest intervals. For example, [14] compared a traditional protocol (3 × 10 with 60 s rest) to a short-repetition protocol (8 × 3 with 120 s rest), aiming to reduce cardiovascular stress and perceived exertion. Their findings show that the short-repetition protocol elicited lower RPE and preserved HRV indices (RMSSD and HFnu) to a greater extent, suggesting that strategies involving longer rest periods may help to maintain parasympathetic activity post-exercise. It is likely that lower hormonal release (cortisol, catecholamines, etc.) and metabolic stress after certain RT set configurations can contribute to mitigating parasympathetic withdrawal after exercise [4,13,15].

A recent alternative gaining attention is cluster set RT, which incorporates short rest intervals between clusters of repetitions within a set, allowing for the maintenance of high volume and intensity [11,16]. This approach is commonly used in athletic settings to enhance performance and/or minimize fatigue accumulation during sessions [16]. It has been shown that performing a cluster set RT configuration induces lower metabolic stress (cortisol and lactate) compared to the traditional RT protocol [15]. Thus, a key hypothesis behind cluster set RT is that distributing rest periods may attenuate the autonomic stress induced by exercise, promoting a better balance between sympathetic and parasympathetic activity and potentially resulting in faster HRV recovery after exercise [15,17]. However, despite the growing interest in this protocol, there is a significant gap in the literature regarding the comparative impact of cluster set versus traditional RT on HRV modulation.

Therefore, this study aims to evaluate the effects of two RT protocols, traditional and cluster set, on HRV parameters in healthy individuals. We hypothesize that cluster set RT will elicit a more favorable autonomic response, with a smaller disturbance in parasympathetic activity compared to traditional RT, thereby promoting a more balanced sympathetic–parasympathetic interaction and reducing the risk of adverse cardiovascular effects.

2. Materials and Methods

2.1. Ethical Aspects

All experimental procedures were conducted after thoroughly explaining the study’s purpose and obtaining written consent from the participants. This study complies with the ethical principles outlined in the Declaration of Helsinki and was approved by the Ethics Committee of the Federal University of Rio de Janeiro, Brazil (protocol number: 55184922.5.0000.5699). It was also registered with the Brazilian Clinical Trials Registry (ReBEC) under ID RBR-9857xj3 on 7 December 2024.

2.2. Participants

A priori power analysis for an F test (repeated measures, within–between interaction across two time points) was conducted using G*Power software version 3.0.1 to estimate the required sample size. Based on a statistical power (1 − β) of 0.80, a moderate effect size (f = 0.25), and an overall level of significance of 0.05, at least 17 participants were needed to perform the study. Twenty participants were recruited using flyers, posters, emails, and social media within a university campus community in Brazil. They were invited to the laboratory for eligibility assessment and a detailed explanation of the experimental procedures. Before randomization, four participants dropped out due to personal reasons, resulting in sixteen participants who completed all experimental procedures.

Table 1. Demographic characteristics of the participants.

N (female)	16 (7)
Age (years)	25 ± 2
Height (m)	1.70 ± 0.1
Weight (kg)	77.2 ± 16.5
BMI (kg/m2)	25.9 ± 4.5

BMI = body mass index. Data are expressed as mean ± standard deviation.

presents the participants’ baseline characteristics.

This study includes young adults aged from 18 to 35 years, in good health, without morbidities such as diabetes, hypertension, obesity, or dyslipidemia. All participants had engaged in an RT program for at least 12 months. Exclusion criteria included smoking, use of psychoactive substances (e.g., caffeine or pre-workout supplements), and anabolic steroid use within six months before the experimental procedures. Additionally, individuals with cardiovascular diseases or osteoarticular injuries that could impair lower-limb RT were excluded.

2.3. Experimental Design

This study was conducted using a randomized, controlled, crossover design from December 2024 to April 2025. After an initial visit for exercise familiarization, participants attended three additional laboratory sessions to complete all experimental procedures. During the first session, anthropometric measurements were obtained, and participants’ 10-repetition maximum (10RM) was determined for the leg press (Movement^®, São Paulo, Brazil) and leg extension chair (Movement^®, São Paulo, Brazil). The 10RM was established within a maximum of four attempts, with a 5 min rest interval between each attempt to minimize fatigue and ensure accurate load assessment. During the second and third visits, participants performed two different RT protocols (cluster set or traditional), which were expected to induce distinct physiological and psychological stress responses [15]. Blood pressure was assessed before, during, immediately after, and 30 min post-exercise. HRV was continuously monitored before and for 30 min after the resistance training protocols to calculate HRV parameters [18]. Rating of perceived exertion (RPE) was assessed immediately after the RT protocol (Figure 1).

RT protocols were randomized using a balanced 1:1 model. Randomization was performed by a laboratory staff member, blinded to the participants’ codes, using a random number generator. At least 72 h passed between the second and third visits to ensure adequate muscle recovery, except for female participants, whose assessments were scheduled within the same menstrual cycle phase to maintain consistency. Specifically, female participants were evaluated during the follicular phase to account for potential hormonal influences on exercise performance. All experimental procedures took place in the morning between 9:00 and 11:00 a.m. Participants were instructed to maintain the same diet throughout all visits.

2.4. RT Protocol

During the first laboratory visit, all participants underwent a 10RM test for the leg press and leg extension exercises. Forty-eight hours later, they returned to the laboratory to perform the resistance training protocol (cluster or traditional set) in a randomized order. Each participant served as their control, completing both experimental conditions (crossover design). Participants performed four sets of ten repetitions of the leg press and leg extension chair exercises at 85% of 10RM, using either the traditional (4 × 10 with 120 s inter-set rest) or cluster set (4 × [2 × 5] with 90 s inter-set rest and 30 s intra-set rest) configuration. The total rest time was equalized between conditions [15]. Before the training protocols, participants warmed up on the leg press (the first exercise) using 50% of the workload. Volume load was kept similar between RT protocols, with only the rest interval manipulated between the cluster and traditional protocols. Both RT protocols were performed on the leg press and leg extension machines. The repetition cadence was standardized at 2 s for the eccentric phase and 1 s for the concentric phase. The total duration of each session, including rest intervals and exercise execution, was approximately 20–25 min. No other physical activities were performed during the experimental sessions, and participants remained seated on the equipment and rested during the intervals between sets.

2.5. Heart Rate Variability Measurement

For the evaluation of HRV parameters, participants were placed in a temperature-controlled quiet environment, lying in a supine position on an examination bed while wearing a heart rate monitor strap affixed to the distal third of the sternum. HRV data were recorded over a 15 min resting period using the Polar RS800CX^® heart rate monitor, Kempele, na Finlândia a device validated for HRV assessment. The collected data were then transferred to a computer via the Elite HRV^® application for further processing. A 5 min segment of HRV recording was selected for analysis using the Kubios^® HRV software (version 2.0, University of Kuopio, Kuopio, Finland). This software processed the R-R intervals of the heart rate, extracting key HRV parameters within time-domain, frequency-domain, and non-linear metrics. The percentage of corrected RR intervals was below 2% for all participants, ensuring data quality. The data were detrended with the smooth prior method. The Lambda value was fixed at 500. For time-domain analysis, the root mean square of successive differences between adjacent normal R-R intervals (RMSSD) was considered. In the frequency-domain analysis, low-frequency (LF) indices and high-frequency (HF) indices, expressed in normalized units (nu), along with the low-frequency/high-frequency (LF/HF) ratio, were examined. In addition, the standard deviation of the Poincaré plot width (SD1) and standard deviation of the length of the Poincaré plot (SD2) were adopted as non-linear acquisitions. RMSSD is widely recognized as a sensitive indicator of parasympathetic nervous system activity and has been employed in previous studies [7]. The LF/HF ratio serves as an indicator of sympathovagal balance, where an increase in LFnu and LF/HF ratio suggests a shift towards sympathetic predominance [7]. The selection of HRV parameters in this study (RMSSD, LFnu, HFnu, LF/HF ratio, SD1, and SD2) was based on those most frequently investigated in prior research [4,7,9].

2.6. Blood Pressure Measurement

Systolic and diastolic blood pressure, along with heart rate, were measured at baseline, during, and 30 min after the resistance training (RT) protocols using a validated device (Bp791it, Omron Co., Tokyo, Japan) and an appropriately sized cuff for the upper left arm. All measurements were performed with participants seated [14]. The RT session began with the leg press followed by the leg extension exercise. For both protocols, blood pressure and heart rate were recorded prior to exercise (baseline), during the second (DEx1) and fourth (DEx2) sets of the leg press, during the second (DEx3) and fourth (IPEx) sets of the leg extension, and again 30 min post-exercise.

2.7. Rating of Perceived Exertion

Perceived exertion during resistance training was assessed using a scale where RPE is linked to the number of repetitions in reserve (RIR), as described by [19]. Participants were familiarized with the scale prior to each session, and data were collected exclusively immediately following the RT protocol.

2.8. Statistical Analysis

The normality and homogeneity of variances were assessed using the Shapiro–Wilk and Levene tests, respectively. A two-way repeated measures ANOVA (2 × 2) was used to detect significant differences in HRV parameters, systolic and diastolic blood pressure, and heart rate before and after the resistance training protocols (cluster and traditional sets). The sphericity test was not considered in the ANOVA analysis since the study design involved repeated measures variables with only two levels. When a significant F-value was found, additional post hoc tests with Bonferroni adjustment were performed. To detect significant differences in the RPE after the RT protocols, a dependent-sample t-test was conducted. In addition, an analysis of covariance (ANCOVA) was performed to examine the effect of the RT protocol (cluster vs. traditional) on the outcome measures, with sex included as a covariate. This approach allowed for the adjustment of potential confounding effects of sex on the physiological responses to resistance training. If the ANCOVA revealed a significant sex effect (p < 0.05), it was further explored using the ANOVA. Cohen’s d was used to calculate the effect size of the RT protocol, with thresholds defined as follows: <0.2 being trivial, from 0.2 to <0.5 being small, from 0.5 to <0.8 being moderate, and ≥0.8 being large [20]. All analyses were performed using a commercially available statistical package (IBM SPSS Statistics version 20 for Mac, Chicago, IL, USA), and results are expressed as means ± standard deviation (SD).

3. Results

3.1. HRV Parameters

Table 2. Data from heart rate variability (HRV) parameters before (pre) and post-resistance training.

HRV Metrics		Traditional	Cluster Set
RMSSD (ms)	Pre	60.6 ± 33.3	59.7 ± 35.1
	Post	28.8 ± 20.9 a	48.6 ± 50.4
HF (nu)	Pre	48.8 ± 17.9	48.1 ± 18.4
	Post	30.8 ± 16.3 a	36.8 ± 21.9
SD1 (ms)	Pre	43.6 ± 23.4	43.2 ± 24.3
	Post	20.4 ± 14.8 a	35.3 ± 34.6
LF (nu)	Pre	49.2 ± 15.8	52.3 ± 18.9
	Post	69.1 ±16.3 a	63.1 ± 21.9 a
LF/HF ratio	Pre	1.4 ± 1.2	1.4 ± 1.1
	Post	3.6 ± 3.3 a	2.9 ± 2.5 a
SD2 (ms)	Pre	69.5 ± 33.3	66.5 ± 29.7
	Post	43.1 ± 21.9 a	56.8 ± 39.2

Subscript letter “a” indicates statistical difference from pre (p < 0.05). Values are presented as mean ± standard deviation. RMSSD = root mean square of successive differences between adjacent normal R-R intervals; HF = high frequency; LF = low frequency; LF/HF ratio = high-frequency/low-frequency ratio; SD1 = standard deviation of the Poincaré plot width; and SD2 = standard deviation of the length of the Poincaré plot.

and Figure 2A–F present the HRV parameters of the participants. A significant main effect for time was observed in RMSSD (F_(1,30) = 18.86, p < 0.001, partial η² = 0.401). The post hoc test revealed a significant reduction (p < 0.001, Cohen’s d = 1.14) in RMSSD following the traditional RT protocol compared to baseline values. No significant difference was observed after the cluster RT protocol compared to baseline (p = 0.111, Cohen’s d = 0.25). Although a significant interaction effect (type of exercise protocol during pre- and post-exercise) was found for RMSSD (F_(1,30) = 6.65, p = 0.039, partial η² = 0.135), the post hoc test did not detect a significant change in RMSSD between the traditional and cluster protocols at baseline (p = 0.947) or post-RT (p = 0.157). However, a moderate effect size (Cohen’s d = 0.51) was observed when comparing post-traditional and post-cluster protocols.

Regarding HFnu, a significant main effect for time was found (F_(1,30) = 25.81, p < 0.001, partial η² = 0.463). The post hoc analysis revealed a significant reduction in HFnu following the traditional RT protocol compared to baseline (p < 0.001, Cohen’s d = 1.05). Although no significant difference was observed in HFnu at baseline and post-cluster set RT protocol (p = 0.09), a moderate effect size (Cohen’s d = 0.55) was noted. No significant interaction effect was found for HFnu (F_(1,30) = 1.33, p = 0.257, partial η² = 0.043).

A significant main effect for time was observed in the SD1 index (F_(1,30) = 17.47, p < 0.001, partial η² = 0.368). The post hoc test revealed a significant reduction (p < 0.001, Cohen’s d = 1.32) in the SD1 index following the traditional RT protocol compared to baseline. However, no significant effect was found when comparing the post-cluster set RT protocol with baseline values (p = 0.268, Cohen’s d = 0.26). A significant interaction effect was observed (F_(1,30) = 6.67, p = 0.015, partial η² = 0.182); however, the post hoc test did not show a significant difference in the SD1 index between the traditional and cluster set RT protocols at baseline (p = 0.834) or post-exercise (p = 0.145). Nevertheless, a moderate effect size (Cohen’s d = 0.55) was noted when comparing post-traditional and post-cluster set protocols.

A significant main effect for time was observed in LFnu (F_(1,30) = 27.06, p < 0.001, partial η² = 0.474). The post hoc analysis revealed a significant increase in LFnu following both the traditional (p < 0.001, Cohen’s d = 1.23) and cluster set RT (p = 0.016, Cohen’s d = 0.52) protocols compared to baseline. No significant interaction effect was found for LFnu (F_(1,30) = 2.51, p = 0.124, partial η² = 0.077). A significant main effect for time was observed in the LF/HF ratio (F_(1,30) = 17.01, p < 0.001, partial η² = 0.362). The post hoc analysis revealed a significant increase in the LF/HF ratio following both the traditional (p < 0.01, Cohen’s d = 0.88) and cluster set (p = 0.028, Cohen’s d = 0.77) RT protocols compared to baseline. No significant interaction effect was observed for the LF/HF ratio (F_(1,30) = 0.74, p = 0.394, partial η² = 0.024).

A significant main effect of time was observed for the SD2 index (F_(1,30) = 16.77, p < 0.001, partial η² = 0.359). The post hoc analysis indicated a significant decrease in SD2 after the traditional RT protocol compared to baseline (p < 0.001, Cohen’s d = 0.93). There was no significant difference between post-cluster set RT protocol values and baseline (p = 0.130, Cohen’s d = 0.27). Additionally, no significant interaction effect was observed for SD2 (F_(1,30) = 3.59, p = 0.068, partial η² = 0.107).

3.2. Blood Pressure and Heart Rate Data

A significant main effect of time was found for systolic blood pressure (F_(5,150) = 49.30, p < 0.001, partial η² = 0.622). Post hoc analysis showed a significant rise in systolic blood pressure at DEx1, DEx2, DEx3, and IPEx (all p < 0.001) following both traditional and cluster set RT protocols. No significant interaction effect was found for systolic blood pressure (F_(5,150) = 0.21, p = 0.959, partial η² = 0.007) (Figure 3A). No significant main effect for time was observed (F_(5,150) = 3.54, p = 0.07, partial η² = 0.106), nor was there a significant interaction effect (F_(5,150) = 0.43, p = 0.70, partial η² = 0.14) in diastolic blood pressure (Figure 3B).

A significant main effect for time was found in heart rate (F_(5,150) = 77.9, p < 0.001, partial η² = 0.772). The post hoc test revealed a significant increase in heart rate in DEx1 (p < 0.001), DEx2 (p < 0.001), DEx3 (p < 0.001), IPEx (p < 0.001), and 30 min post-traditional RT protocol. A significant increase in heart rate was also observed in DEx1 (p < 0.001), DEx2 (p < 0.001), DEx3 (p < 0.001), and IPEx (p < 0.001) following the cluster set RT protocol; however, no significant difference in heart rate was found 30 min post-cluster set RT protocol (p = 0.99). No significant interaction effect was observed (F_(5,150) = 1.95, p = 0.08, partial η² = 0.06) (Figure 3C).

3.3. RPE Data

A significantly lower RPE (t₍₁₅₎ = 5.3, p < 0.001) was observed following the cluster set RT protocol (7.4 ± 1.2) compared to the traditional set (9.1 ± 0.6).

3.4. Gender Effects

No significant main effects of time between sexes or interaction effects among sex, time, and group were observed for RMSSD (F_(1,28) = 2.07, p = 0.161, partial η² = 0.069; F_(1,28) = 0.115, p = 0.291, partial η² = 0.040), HFnu (main effect: F_(1,28) = 0.08, p = 0.774, partial η² = 0.003; interaction effect: F_(1,28) = 1.15, p = 0.291, partial η² = 0.040), LFnu (main effect: F_(1,28) = 0.47, p = 0.49, partial η² = 0.003; interaction effect: F_(1,28) = 0.16, p = 0.49, partial η² = 0.028), or LF/HF ratio (main effect: F_(1,28) = 0.46, p = 0.49, partial η² = 0.017; interaction effect: F_(1,28) = 0.16, p = 0.68, partial η² = 0.006).

Similarly, no significant main or interaction effects were found for SD1 (main effect: F_(1,28) = 2.58, p = 0.11, partial η² = 0.08; interaction effect: F_(1,28) = 1.09, p = 0.31, partial η² = 0.037) or SD2 (main effect: F_(1,28) = 4.83, p = 0.056, partial η² = 0.14; interaction effect: F_(1,28) = 0.32, p = 0.57, partial η² = 0.012).

Regarding cardiovascular parameters, no significant main or interaction effects were observed for systolic blood pressure (main effect: F_(5,140) = 0.92, p = 0.467, partial η² = 0.032; interaction effect: F_(5,140) = 0.291, p = 0.917, partial η² = 0.01), diastolic blood pressure (main effect: F_(5,140) = 0.83, p = 0.529, partial η² = 0.029; interaction effect: F_(5,140) = 2.56, p = 0.06, partial η² = 0.08), or heart rate (main effect: F_(5,140) = 0.966, p = 0.441, partial η² = 0.03; interaction effect: F_(5,140) = 0.104, p = 0.991, partial η² = 0.004).

4. Discussion

The present study investigates the effects of cluster set RT configurations on HRV parameters in young, healthy individuals. Our findings support the hypothesis that a single session of the cluster set RT protocol did not alter HRV parameters (parasympathetic and sympathetic activity) assessed 30 min after exercise, whereas the traditional RT protocol reduced parasympathetic activity (RMSSD, HFnu, and SD1) and increased sympathetic activity (LFnu, LF/HF ratio, and SD2). Moreover, although volume load and relative intensity (85% of 10RM) were equal, a higher subjective exertion (RPE) was observed after the traditional RT protocol compared to the cluster set. These results suggest that traditional RT substantially impacts cardiac autonomic modulation more than the cluster set RT protocol, providing relevant insights for exercise prescription, including for cardiopathic patients. Although exploring the mechanisms by which cluster sets mitigate reduced parasympathetic withdrawal after exercise goes beyond the aim of this study, it is possible that lower metabolic stress (e.g., reduced lactate and cortisol concentrations) associated with the cluster set protocol may explain differences in autonomic cardiac modulation [15]. However, future studies are needed to further investigate the underlying mechanisms behind the effects of cluster set configurations on physiological outcomes.

Aligned with our findings, a previous study evaluated the effects of two RT protocols (3 × 10 with a 60 s rest vs. 8 × 3 with a 120 s rest) designed to elicit different levels of RPE on HRV parameters (RMSSD, HFnu, and SD1) in trained individuals [14]. The authors reported a significant reduction in RMSSD and HFnu following the 3 × 10–60 s protocol compared to the 8 × 3–120 s RT protocol. Additionally, they observed significantly higher RPE in the 3 × 10–60 s condition, suggesting that higher-intensity exercise can decrease parasympathetic activity 30 min post-exercise [14]. Another study examined the effects of a high-intensity CrossFit workout (Cindy) and treadmill running, both performed for 20 min, on cardiac autonomic modulation [18]. The researchers observed a significant reduction in RMSSD and HF parameters over 30 min following both exercise modalities. However, the CrossFit workout induced a greater reduction in RMSSD and HF parameters compared to treadmill running, which may be associated with higher RPE, also observed in the study [18].

Additionally, Figueiredo et al. (2015) [21] evaluated the influence of different load intensities (60%, 70%, and 80% of 1RM) on HRV throughout 60 min post-RT in trained individuals. Although the authors did not observe a significant difference between intensities in HRV parameters, the effect size data indicated a large decrease in parasympathetic activity (RMSSD) after the 80% of 1RM session compared to the 60% and 70% of 1RM sessions [20]. Moreover, Nunes et al. (2021) [13] compared HRV parameters after a low-intensity RT with short (3 × 10 repetitions, 50% of 1RM) and long (3 × 20 repetitions, 50% of 1RM) set configurations performed for five upper limb exercises (bench press, bent-over barbell row, barbell front raise, barbell biceps curl, and lying barbell triceps extension). A significant reduction in RMSSD was observed after the long-set configuration compared to baseline, whereas no change was observed after the short-set configuration [13].

Taken together, this body of evidence suggests that RT intensity and volume load play a crucial role in autonomic response [13,20]. A recent systematic review and meta-analysis investigated the effects of a single session of RT on HRV parameters [4]. The authors concluded that RT leads to a withdrawal of cardiac parasympathetic modulation and an increase in cardiac sympathetic modulation, with these changes being more pronounced at higher training volumes. Furthermore, the number of sets, intensity, and rest intervals between sets were identified as key factors influencing HRV parameters [4].

Interestingly, both the cluster set and traditional resistance training (RT) protocols used in this study were matched for relative intensity (85% of 10RM), volume load (four sets of ten repetitions), and inter-set rest intervals (120 s). However, the inclusion of a brief intra-set rest in the cluster set configuration (five repetitions followed by a 30 s rest, then five additional repetitions) did not affect parasympathetic or sympathetic activity 30 min post-exercise. In contrast, the traditional RT protocol led to a reduction in parasympathetic activity. This phenomenon may be explained by the lower RPE and heart rate (30 min post-exercise) induced by the cluster set RT, which could indicate lower metabolic stress during exercise. [15]. Reinforcing this hypothesis, a previous study showed significantly lower cortisol and lactate levels 30 min after a cluster set compared to a traditional set RT protocol, which closely resembled the RT protocol adopted in the present study [15]. Furthermore, [17] also investigated the acute effects of RT set configuration on cardiac autonomic modulation. Despite identical intensity (15RM), total volume (200 repetitions), and resting time between sets, the short set configuration (8 × 5 repetitions with 51 s of rest) attenuated the reduction in parasympathetic activity compared to the long set configuration (4 × 10 repetitions with 2 min rest intervals). Additionally, the short set configuration resulted in lower lactate accumulation and velocity loss during exercise, without significant changes in blood pressure or baroreflex sensitivity, suggesting a more favorable autonomic and metabolic response [17]. Nevertheless, variations in rest-distribution strategies during a five-week resistance training program—comprising either four sets of eight repetitions with 5 min inter-set rest intervals or six sets of two repetitions with 1 min rest between sets and 5 min rest between exercises, both performed at a 10RM load—did not result in significant changes in heart rate parameters [22].

Experimental Considerations

Prolonged sympathetic activation and delayed parasympathetic recovery after RT are phenomena typically observed following high-intensity exercise [4]. Consequently, post-exercise HRV modulation has been associated with an increased risk of acute cardiac events [23,24]. Furthermore, HRV measurements are widely used to monitor exercise recovery, enabling adjustments in acute RT protocols based on cardiac autonomic modulation. This approach may optimize microcycle periodization, enhance training adaptations and performance, and help prevent injuries and overtraining. The cluster set RT protocol is an interesting RT configuration to generate muscle adaptation. For example, a recent study demonstrated that performing leg press and leg extension exercises using either cluster or traditional sets elicited similar increases in muscle thickness and lean tissue mass in resistance-trained individuals, suggesting that cluster sets are an efficient RT methodology for promoting muscle adaptations [11].

It is important to note that, although the present study demonstrates a decline in parasympathetic activity following a single session of traditional set RT, this does not mean that this RT configuration should not be recommended for improving cardiac autonomic modulation. A previous study reported that eight weeks of resistance training enhanced HRV parameters in young female college students [25], showing a significant increase in SDNN and a decrease in the LF/HF ratio. These findings suggest that RT reduces sympathetic activity (as indicated by SDNN) and improves sympathovagal balance (LF/HF ratio).

Additionally, the present study does not reveal a significant effect of gender on HRV parameters following cluster set and traditional RT protocols. A limitation of this study is the small sample size (16 participants); however, the large effect sizes observed reinforce our findings, as effect size calculations (Cohen’s d) are not influenced by sample size. Additionally, although the small sample also limited gender comparisons (seven females and nine males), our findings align with previous evidence from a narrative review [9] and a systematic review and meta-analysis [4], which reported that acute resistance-training-induced changes in HRV parameters are not significantly influenced by gender.

Furthermore, these findings should be interpreted with caution, as they are limited to young, healthy, resistance-trained individuals and may not generalize to older or clinical populations.

5. Conclusions

This study suggests that cluster sets may lead to smaller autonomic perturbations, as reflected by the trends and moderate effect sizes in HRV parameters 30 min post-exercise compared to traditional sets. These findings could help exercise physiologists to assist RT programs for clinical populations, such as individuals with hypertension or who are at risk for cardiovascular disease, by favoring protocols that potentially reduce cardiac autonomic stress. Future research should investigate whether these effects are consistent in clinical or older populations.