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Are rating of perceived exertion and heart rate methods useful to monitor the internal training load in functional training?

Abstract

Aim:

The study aimed to quantify and characterize the Training Load (TL) in a Functional Training (FT) model using Heart Rate (HR) and Session Rating of Perceived Exertion (sRPE) methods, and to verify whether these methods could be valid to monitor the TL during a FT program.

Methods:

The study design consisted of two phases: phase 1 - composed of a single training session of FT (FTSESSION), in which HR, sRPE, and pre- and post-exercise lactate [La] levels were assessed; phase 2 - composed of a FT program (FTPROGRAM) with eight weeks of duration and two sessions per week. The HR and SRPE were utilized to monitor all training sessions, and the results between sessions 1 vs. 8, 8 vs. 9, and 9 vs. 16 were compared.

Results:

On phase 1, HR distribution demonstrated that the participants spent about 75% of the total training time above 80% HRmax. Post-exercise [La] values were significantly higher (p < 0.05) than pre-exercise. The mean sRPE score was 8.5 ± 1.2. In phase 2, HR distribution was different between sessions 1-8 and 8-9 (p < 0.05). A strong correlation (r = 0.790) between the internal training load (ITL) and Training impulse (TRIMP) was observed.

Conclusion:

Our data demonstrated that the FTSESSION can be characterized as a high-intensity exercise, based on the pattern of HR responses and sRPE, and was reinforced by the [Lapeak]. Also, the TL monitoring methods (sRPE and TRIMP) proved to be valid for monitoring FT programs.

Keywords
workload; training load; circuit training; body weight-based exercise; heart rate

Introduction

Functional training (FT) is described as a set of exercises that aim to improve strength, balance, flexibility, and coordination through integrated and multiplanar movements1,1. Teixeira CVLS, Evangelista AL, Pereira PE de A, Da Silva-Grigoletto ME, Bocalini DS, Behm DG. Complexity: a novel load progression strategy in strength training. Front Physiol. 2019;10:1-5. doi
doi...
22. Thompson WR. Worldwide survey of fitness trends for 2021. ACSM's Heal Fit J. 2021;25(1):10-9. doi
doi...
. FT is also known as multicomponent training, task-specific training, circuit training, and body weight-based exercise, among other nominations. FT incorporates different types of exercise (i.e., resistance, aerobic, balance, cognitive) in a synergistic, integrated, and balanced manner 11. Teixeira CVLS, Evangelista AL, Pereira PE de A, Da Silva-Grigoletto ME, Bocalini DS, Behm DG. Complexity: a novel load progression strategy in strength training. Front Physiol. 2019;10:1-5. doi
doi...
. These dynamic characteristics, inexpensiveness, and flexibility-can be performed indoors or out-contribute to its popularity3-3. Monteiro AG, Evangelista AL. Treinamento Funcional: uma abordagem prática. São Paulo, Phorte; 2010.4. Boyle M. Avanços no treinamento funcional. Porto Alegre, Artmed; 2015.5. Teixeira CVLS, Evangelista AL, Pereira CA, Grigoletto ME da S. Short roundtable rbcm : functional training. Rev Bras Ci Mov. 2016;24:200-6. doi
doi...
66. Machado AF, Baker JS, Figueira Junior AJ, Bocalini DS. High-intensity interval training using whole-body exercises: training recommendations and methodological overview. Clin Physiol Funct Imaging. 2017;39(6):378-83. doi
doi...
. This makes FT one of the top twenty global fitness trends since 200722. Thompson WR. Worldwide survey of fitness trends for 2021. ACSM's Heal Fit J. 2021;25(1):10-9. doi
doi...
. However, this multicomponent particularity factor can make it difficult to characterize and monitor the training load (TL) during FT programs.

TL can be assessed using external training load (ETL) and internal training load (ITL) markers. The ETL is an objective measure of the workload performed during a given training session related to volume and intensity variables; ITL is the acute physiological response induced by exercise77. Impellizzeri FM, Rampinini E, Marcora SM. Physiological assessment of aerobic training in soccer. J Sports Sci. 2005;23(6):583-92. doi
doi...
. TL monitoring methods vary considerably depending on the sport or activity. Nevertheless, TL monitoring is often assessed using heart rate (HR) based methods such as training impulse (TRIMP)-a product of intensity and volume factors-or evaluated based on the HR distribution in intensity effort zones88. Edwards S. High performance training and racing. In: The Heart Rate Monitor Book. Sacramento, CA, Press, Feet Fleet; 1993. p.113-123.. Ratings of perceived exertion (sRPE)99. Foster C, Florhaug JA, Franklin J, Gottschall L, Hrovatin LA, Parker S, Doleshal P, Dosdge C, et al. A new approach to monitoring exercise training. J strength Cond Res. 2001;15(1):109-15. doi
doi...
are used as the primary measure of ITL1010. Drew MK, Finch CF. The relationship between training load and injury, illness and soreness: a systematic and literature review. Sport Med. 2016;46(6):861-83. doi
doi...
. Moreover, subjective measures such as sRPE can be more sensitive than objective measures1111. Coyne JOC, Gregory HG, Coutts AJ, Newton RU, Nimphius S. The current state of subjective training load monitoring - a practical perspective and call to action. Sport Med - Open. 2018;4(1). doi
doi...
, and sRPE is the most assessed TL variable over a variety of sports1212. Burgess DJ. The research doesn't always apply: practical solutions to evidence-based training-load monitoring in elite team sports. Int J Sports Physiol Perform. 2017;12:136-41. doi
doi...
.

Traditionally, exercise intensity is determined by HR, sRPE, oxygen uptake, ventilatory threshold, or blood lactate concentration ranges. Exercise is classified into low, moderate, or high-intensity zones using these ranges13,13. American College of Sports Medicine. Quantity and quality of exercise for developing and maintaining cardiorespiratory, musculoskeletal, and neuromotor fitness in apparently healthy adults: guidance for prescribing exercise. Med Sci Sports Exerc. 2011;43(7):1334-59. doi
doi...
1414. Campbell BI, Bove D, Ward P, Vargas A, Dolan J. Quantification of training load and training response for improving athletic performance. Strength Cond J. 2017;39(5):3-13. doi
doi...
. However, these parameters are habitually established by performing a maximal effort test, considering the specificity of the type of exercise13,13. American College of Sports Medicine. Quantity and quality of exercise for developing and maintaining cardiorespiratory, musculoskeletal, and neuromotor fitness in apparently healthy adults: guidance for prescribing exercise. Med Sci Sports Exerc. 2011;43(7):1334-59. doi
doi...
1414. Campbell BI, Bove D, Ward P, Vargas A, Dolan J. Quantification of training load and training response for improving athletic performance. Strength Cond J. 2017;39(5):3-13. doi
doi...
. Due to the multicomponent characteristic of FT, there are no specific methods or maximal effort tests for FT programs when combining various exercises. This makes TL characterization and monitoring challenging. It has been proposed that the TL could be divided into low, moderate, and high-intensity zones using certain TL methods and intensity parameters. This approach has been validated and is useful for various sports15,15. Lovell TWJ, Sirotic AC, Impellizzeri FM, Coutts AJ. Factors affecting perception of effort (session rating of perceived exertion) during rugby league training. Int J Sports Physiol Perform. 2013;8(1):62-9. doi
doi...
1616. Moreira A, Kempton T, Aoki MS, Sirotic AC, Coutts AJ. The impact of 3 different-length between-matches microcycles on training loads in professional rugby league playersq. Int J Sports Physiol Perform. 2015;10(6):767-73. doi
doi...
17. Manzi V, Bovenzi A, Castagna C, Salimei PS, Volterrani M, Iellamo F. Training-load distribution in endurance runners: objective versus subjective assessment. Int J Sports Physiol Perform. 2015;10(8):1023-28. doi
doi...
–1818. Seiler KS, Kjerland Gø. Quantifying training intensity distribution in elite endurance athletes: is there evidence for an “optimal” distribution? Scand J Med Sci Sport. 2006;16(1):49-56. doi
doi...
. Based on psychophysical constructs, the sRPE method provides a global indicator of exercise intensity, enabling an accurate measure of an individual's response to a training dose1515. Lovell TWJ, Sirotic AC, Impellizzeri FM, Coutts AJ. Factors affecting perception of effort (session rating of perceived exertion) during rugby league training. Int J Sports Physiol Perform. 2013;8(1):62-9. doi
doi...
. Organizing the training intensity continuum into specific zones is common in exercise models and sports studies1818. Seiler KS, Kjerland Gø. Quantifying training intensity distribution in elite endurance athletes: is there evidence for an “optimal” distribution? Scand J Med Sci Sport. 2006;16(1):49-56. doi
doi...
. For instance, Lovell et al.1515. Lovell TWJ, Sirotic AC, Impellizzeri FM, Coutts AJ. Factors affecting perception of effort (session rating of perceived exertion) during rugby league training. Int J Sports Physiol Perform. 2013;8(1):62-9. doi
doi...
and Moreira et al.1616. Moreira A, Kempton T, Aoki MS, Sirotic AC, Coutts AJ. The impact of 3 different-length between-matches microcycles on training loads in professional rugby league playersq. Int J Sports Physiol Perform. 2015;10(6):767-73. doi
doi...
demonstrated the validity and the usefulness of the sRPE in their respective studies with rugby players. They examined training intensity zones without performing maximal effort tests.

Using non-experimental data, Teixeira et al.55. Teixeira CVLS, Evangelista AL, Pereira CA, Grigoletto ME da S. Short roundtable rbcm : functional training. Rev Bras Ci Mov. 2016;24:200-6. doi
doi...
and Machado et al.66. Machado AF, Baker JS, Figueira Junior AJ, Bocalini DS. High-intensity interval training using whole-body exercises: training recommendations and methodological overview. Clin Physiol Funct Imaging. 2017;39(6):378-83. doi
doi...
indicated that TL monitoring in FT could be done using traditional methods, such as HR and sRPE, as previously described. Machado et al.66. Machado AF, Baker JS, Figueira Junior AJ, Bocalini DS. High-intensity interval training using whole-body exercises: training recommendations and methodological overview. Clin Physiol Funct Imaging. 2017;39(6):378-83. doi
doi...
also suggest that the lactate concentrations ([La]) could be used to analyze exercise intensity. Studies that utilized the FT as an intervention program have adopted both HR and effort perception methods1919. Gist NH, Freese EC, Ryan TE, Cureton KJ. Effects of low-volume, high-intensity whole-body calisthenics on Army ROTC cadets. Mil Med. 2015;180(5):492-8. doi
doi...
20. Schleppenbach LN, Ezer AB, Gronemus SA, Widenski KR, Braun SI, Janot JM. Speed-and circuit-based high-intensity interval training on recovery oxygen consumption. Int J Exerc Sci. 2017;10(7):942-53. https://digitalcommons.wku.edu/cgi/viewcontent.cgi?article=1918&context=ijes
https://digitalcommons.wku.edu/cgi/viewc...
-2121. Kliszczewicz B, Williamson C, Bechke E, McKenzie M, Hoffstetter W. Autonomic response to a short and long bout of high-intensity functional training. J Sports Sci. 2018;36(16):1872-9. doi
doi...
. None of the studies tested or reported on the validity of these methods for TL characterization or monitoring.

Considering the lack of information on TL variables in the FT model, the present study aimed to quantify and characterize the TL in an FT model using HR88. Edwards S. High performance training and racing. In: The Heart Rate Monitor Book. Sacramento, CA, Press, Feet Fleet; 1993. p.113-123. and sRPE based methods99. Foster C, Florhaug JA, Franklin J, Gottschall L, Hrovatin LA, Parker S, Doleshal P, Dosdge C, et al. A new approach to monitoring exercise training. J strength Cond Res. 2001;15(1):109-15. doi
doi...
. We aimed to verify the validity of these methods for monitoring TL during an FT program. It is hypothesized that FT could be characterized as a high-intensity exercise and that HR and sRPE based methods are valid for monitoring TL during the FT program.

Materials and methods

Participants

The sample was composed of fifteen cisgender participants (ten women and five men) with mean age of 26.2 ± 4.0 years. A total of thirteen (eight women and five men), with mean body mass (kg) 68.3 ± 13.4, height (m) 1.6 ± 0.1, and Fat% 26.9 ± 7.7, participated in the FTSESSION, and ten (eight women and two men) with mean body mass (kg) 62.0 ± 11.0, height (m) 1.64 ± 0.1 and Fat% 25.3 ± 6.4 participated of the FTPROGRAM. Seven participants performed the two phases of this study.

The physical activity level of the participants was determined by International Physical Activity Questionnaire (IPAQ). Only one participant was characterized as “Active”. The other participants were characterized as “Irregularly Active A” or “B”. Thus, the participant group was considered irregularly active.

The inclusion criteria adopted were to be able to perform the exercise routine; do not use any medications that influence the HR responses (stimulants or blockers); do not present any cardiac disease (according to anamnesis and cardiological test before experimental procedures); age between 18 and 35 years. Participants who did not complete the FTSESSION in two trials after reporting dizziness and nausea (1 participant) and who started another training program during the FTPROGRAM (1 participant) were excluded. Thus, 12 individuals in FTSESSION and 9 in FTPROGRAM completed the study.

All participants were informed about the research procedures and signed the consent form. The procedures carried out following the regulations required in the Resolution 466/2012 of the National Health Council on research involving human beings and this project was approved by the local University Ethics Committee, under the protocol number 2.395.616/2017.

Study design

The current study consisted of two phases: phase 1 - composed by a single training session of FT (FTSESSION), in which HR, sRPE, and pre-and post-exercise [La] were assessed; phase 2 - composed of a FT program (FTPROGRAM) with eight weeks of duration and two sessions per week. For training monitoring, HR and SRPE were analyzed in all 16 sessions.

All participants performed a familiarization session one week before the experimental protocol. The familiarization was performed with reduced volume (10 min of duration) and intensity (20 s of exercise for 40 s of passive recovery) compared to the original protocol. The focus of the familiarization was the execution of the exercises.

For phase 1, data were collected on four consecutive days in the same week, from 8:00 a.m. to 10:00 a.m. All participants performed the FTSESSION only once and started the circuit performing the same exercise routine. In addition to HR and sRPE monitoring, blood samples were collected pre- and post-the exercise sessions for [La] analysis.

In Phase 2, the training sessions were carried out in the morning (8:00-8:30 a. m) and in the afternoon (5:30-6:00 p.m.), two times a week. Participants chose the training schedule according to their time and performed all sessions at the same daytime of their choice. The HR and sRPE responses were monitored in all 16 sessions.

FT protocols

Exercises were chosen based on the FT description, which suggest the integration of physical capacities (i.e., muscular endurance, cardiorespiratory resistance, balance, agility)1,1. Teixeira CVLS, Evangelista AL, Pereira PE de A, Da Silva-Grigoletto ME, Bocalini DS, Behm DG. Complexity: a novel load progression strategy in strength training. Front Physiol. 2019;10:1-5. doi
doi...
22,22. Silva-Grigoletto ME, Brito CJ, Heredia JR. Treinamento funcional: funcional para que e para quem? Rev Bras Cineantropometria e Desempenho Hum. 2014;16(6):714-19. doi
doi...
2323. Teixeira CVLS, Evangelista AL, Novaes JS, Da Silva Grigoletto ME, Behm DG. “You're only as strong as your weakest link”: a current opinion about the concepts and characteristics of functional training. Front Physiol. 2017;8:1-6. doi
doi...
. Different exercise protocols were used, composed of 10 exercises of calisthenics, multiarticular and monoarticular characteristics, arranged in circuit.

The FTSESSION and sessions 1-8 of the FTPROGRAM were performed following the same exercise protocol (protocol 1: squat; lunge; hip thrusts; burpee for beginners variation - bench squat thrust; jumping jack; jump overstep; push-up; TRX row; sit-up and oblique sit-up). From sessions 9-16 of the FTPROGRAM, the exercises complexity that comprised the initial training protocol was increased for TL progression, as proposed by Teixeira et al11. Teixeira CVLS, Evangelista AL, Pereira PE de A, Da Silva-Grigoletto ME, Bocalini DS, Behm DG. Complexity: a novel load progression strategy in strength training. Front Physiol. 2019;10:1-5. doi
doi...
(protocol 2: squat + lunge; walking lunge; hip thrusts on Swiss ball; sumo squat on agility ladder; burpee; high knees on jump trampoline; push-up; TRX row at a 90-degree angle; sit-up and plank).

The training sessions were characterized by two rounds, alternating 1 min of exercise for 30 s of passive recovery (2: 1), totaling 30 min.

Training load

The HR was monitored beat-to-beat using a Polar Team 2 Pro (Polar®, Kempele, Finland) in the FTSESSION and a Polar Watch RS800CX (Polar®, Kempele, Finland) in the FTPROGRAM. The HR data obtained in the two phases were exported and analyzed using Polar Pro Trainer 5 software (Polar®, Kempele, Finland). HR responses were distributed in intensity zones (zone 1: 50-60%; zone 2: > 60-70%; zone 3: > 70-80%; zone 4: > 80-90%; zone 5: > 90%), represented by a percentage range of maximal HR (HRmax)88. Edwards S. High performance training and racing. In: The Heart Rate Monitor Book. Sacramento, CA, Press, Feet Fleet; 1993. p.113-123.. Training impulse (TRIMP) was calculated by the time (minutes) accumulated in each intensity zone and multiplied by the respective arbitrary value of the same zone88. Edwards S. High performance training and racing. In: The Heart Rate Monitor Book. Sacramento, CA, Press, Feet Fleet; 1993. p.113-123..

The HRmax was considered the maximum value of HR reached during the FTSESSION (sHRmax). For the FTPROGRAM, the sHRmax achieved in the 1st session of each protocol was considered. sHRmax verified in session 1 was used from session 1 to 8 and sHRmax verified in session 9, from session 9-16. For comparison, the HRmax estimated from the equation proposed by Tanaka2424. Tanaka H, Monahan KD, Seals DR. Age-predicted maximal heart rate revisited. J Am Coll Cardiol. 2001;37(1):153-6. doi
doi...
(eHRmax) was also calculated.

The SRPE was monitored using an adapted scale of 10 points (CR-10) proposed by Foster99. Foster C, Florhaug JA, Franklin J, Gottschall L, Hrovatin LA, Parker S, Doleshal P, Dosdge C, et al. A new approach to monitoring exercise training. J strength Cond Res. 2001;15(1):109-15. doi
doi...
, 15 minutes after the end of the session2525. Pedro RE, Oliveira RS, Vasconcelos PS de S, Pires Junior R, Milanez VF. Efeito temporal sobre a resposta da percepção subjetiva do esforço. Rev Bras Med Esporte. 2014;20(5):1-4. doi
doi...
. For the estimated internal training load (ITL), the SRPE score was multiplied by the duration (in minutes) of the training session. TRIMP and SRPE results were presented in arbitrary unity (AU).

Blood samples (25 μL) were collected from the earlobe to determine the lactate concentration ([La]) at the pre-moment ([Lapre]), immediately after the session ([Lapost]), at the 3rd ([Lamin3]) and and 5th ([Lamin5]) minutes after the end of the session, by a heparinized capillary tube and immediately transferred to Eppendorf® tubes containing 50 μL of 1% sodium fluoride (NaF) and frozen at −20 °C for further analysis. Lactate concentration was determined electrochemically on a YSI 2300 STAT® (Yellow Springs Ind, Ohio, USA). Lactate peak ([Lapeak]) was defined for each participant as the highest post-exercise [La] value.

Statistics analysis

All analyses were performed on Graph Pad Prism (version 9), considering a significance level of 5% (p < 0.05). The normality of the data was verified by the Shapiro-Wilk test and the descriptive data were presented as mean ± standard deviation (SD). After, the t-test for independent samples was performed for the comparison between the HRmax values reached in the FTSESSION and the HR estimation by the Tanaka equation.

One-way ANOVAs with Bonferroni post-hoc test was performed to verify the variances between time-points for the HR distribution in intensity zones related to HRmax in FTSESSION, the [La] at pre-and post-FTSESSION. Also, the same test was performed to compare sRPE, ITL, and TRIMP 1-8, 8-9, and 9-16 sessions during the FTPROFGRAM.

The HR distribution in intensity effort zones on sessions 1-8, 8-9, and 9-16 were evaluated by two-way ANOVA test (zones and sessions) considering the assumptions of homogeneity of the variances (Levene's test) and equality of matrices of covariance (Box M test) followed by Bonferroni's post hoc, considering the significance of the test (p < 0.05).

The correlation between Time Z5 and [Lapeak] in the FTSESSION was performed using Pearson test. The Pearson test was also used to correlate sRPE, ITL, Time Z5 and [Lapeak] on the FTPROGRAM. For TRIMP correlate with variables presented in Table 2, was used the Spearman test. The adopted qualitative description was proposed by Hopkins2626. Hopkins WG, Marshall SW, Batterham AM, Hanin J. Progressive statistics for studies in sports medicine and exercise science. Med Sci Sports Exerc. 2009;41(1):3-12. doi
doi...
.

Results

FTSESSION

The mean HR values for immediately before FTSESSION (HRpre), as well as the HRmax during the FTSESSION and the HRmax estimated by Tanaka's equation2424. Tanaka H, Monahan KD, Seals DR. Age-predicted maximal heart rate revisited. J Am Coll Cardiol. 2001;37(1):153-6. doi
doi...
were 80 ± 12 bpm, 185 ± 13 bpm, and 189 ± 3 bpm, respectively. There was no difference between the HRmax verified in the and FTSESSION and the HRmax estimated by Tanaka et al. (2001) (p = 0.365; t = 0.924; df = 22). The average HR found during FTSESSION was 158 ± 15 bpm, which corresponds to 84.9% of the HRmax.

Figure 1 shows the pattern of HR distribution in zones related to HRmax and includes both exercise time and passive rest time. The participants spent about 95% of the total training time in zones 3, 4, and 5, with the highest percentages found for zones 4 (42.8 ± 7.7%) and 5 (32.5 ± 14.3%). The activity in zones 3, 4, and 5 was different from zones 1 and 2 p < 0.001, for the three intensity zones). Zones 4 and 5 also presented differences compared to zone 3 (p < 0.001, p = 0.005, respectively). There was no difference between zones 4 and 5 (p = 0.112).

Figure 1
Time percentage spent in intensities effort zones relative to HRmax, during the TF session (n = 12). F = 48.6. ∗p < 0.05 in relation to zone 1; #p < 0.05 in relation to zone 2; †p < 0.05 in relation to zone 3.

The mean values for the sRPE, ITL, and TRIMP related to the FTSESSION were 8.5 ± 1.2 (AU), 250.0 ± 46.9 (AU), and 121.3 ± 13.0 (AU), respectively. Individual values were presented in Figure 2.

Figure 2
Individual sRPE, ITL and TRIMP quantification in the FTSESSION.

Table 1 shows the pre-and post-[La] concentrations for FTSESSION. The largest difference found at the end of FTSESSION, is described as [Lapeak]. Among the twelve participants, eight individuals presented the highest blood lactate concentrations at [Lapost], three at [Lamin3] and only one individual at [Lamin5]. All post-exercise [La] values were higher than the pre-exercise values (p < 0.001; F = 167). There was no difference between [Lapost], [Lamin3], [Lamin5], and [Lapeak]. A very strong correlation2626. Hopkins WG, Marshall SW, Batterham AM, Hanin J. Progressive statistics for studies in sports medicine and exercise science. Med Sci Sports Exerc. 2009;41(1):3-12. doi
doi...
was observed between [Lapeak] and the time spent in zone 5 (Time Z5) (r = 0.765; p < 0.001).

Table 2 presents the correlation between TL monitoring methods and total time spent (in minutes) in zone 5 (Time Z5) and [Lapeak].

Table 1
Blood lactate concentrations pre- and post-FTSESSION (n = 12).
Table 2
Correlations between training load monitoring methods based on the HR and RPE with the analyzed variables in the FTSESSION.

FTPROGRAM

Figure 3 presents the time percentage spent in intensity effort zones related to HRmax during all 16 sessions. A significant interaction effect between zones and sessions (p < 0.001; F = 8.488) was observed. The post hoc test shows a significant decrease in the percentage of time spent in zone 5, between the 1st (session 1) and the last session (session 8) of protocol 1 (p = 0.008). There was a significant increase in the time spent in the same zone (p = 0.002) when the last session of protocol 1 (session 8) was compared with the 1st session of protocol 2 (session 9). Consequently, the time spent between the lower intensity zones, such as zone 2, showed a significant increase when compared to sessions 1 and 8 (p = 0.014), and a significant decrease for sessions 8 and 9 (p = 0.004). There was no statistical difference for zone 3, when comparing sessions 1 and 8 (p = 0.191) and sessions 8 and 9 (p = 0.096). The distribution of HR between zones 1 and 4 did not present a statistical difference for the analyzed sessions.

Figure 3
HR distribution in intensity effort zones (zone 1: 50-60% HRmax; zone 2: > 60-70% HRmax, zone 3: > 70-80% HRmax; zone 4: > 80-90% HRmax; zone 5: > 90% HRmax) during all sessions of the FTPROGRAM (n = 9). (F = 8.488).

The mean values of ITL, TRIMP, and sRPE verified in all FTPROGRAM sessions are presented in Figure 4. All monitoring methods presented significant difference between sessions 1 vs. 8 (p = 0.022 for ITL; p = 0.033 for TRIMP and p = 0.020 for sRPE) and between sessions 8 vs. 9 (p = 0.022 for ITL; p = 0.001 for TRIMP and p = 0.025 for sRPE). There was no significant difference between sessions 9 vs. 16 for all monitoring methods. Moreover, a very strong correlation (r = 0.790; p < 0.002) was found between the ITL and TRIMP methods.

Figure 4
Mean values of ITL, TRIMP and sRPE verified in FTPROGRAM sessions. ITL (F = 8.906), TRIMP (F = 12.08) and sRPE (F = 8.874) FTPROGRAM sessions. ∗p < 0.05 session 1. #p < 0.05 session 8.

Discussion

This study was composed of two phases. Phase 1 aimed to quantify and characterize the TL in an FT model using HR88. Edwards S. High performance training and racing. In: The Heart Rate Monitor Book. Sacramento, CA, Press, Feet Fleet; 1993. p.113-123. and sRPE methods99. Foster C, Florhaug JA, Franklin J, Gottschall L, Hrovatin LA, Parker S, Doleshal P, Dosdge C, et al. A new approach to monitoring exercise training. J strength Cond Res. 2001;15(1):109-15. doi
doi...
. Phase 2 aimed to verify the validity of these methods for TL monitoring during an FT program. The main findings demonstrated that the FTSESSION could be characterized as a high-intensity exercise, according to HR distribution and sRPE scores. The observed post-exercise [La] results validate this characterization. Also, the TL quantification methods were validated for TL monitoring during the FT program, confirming the present study's hypothesis. To our knowledge, this is the first study to quantify and describe TL using HR and sRPE methods, both in a single FT session and across an FT program.

The HR distribution in the intensities effort zones showed that participants spent most of the total training time (≅ 75%) between the most intense zones (4 and 5, i. e. above 80% HRmax). This indicates that the FTSESSION was performed at high intensity, per the classification proposed by the ACSM1313. American College of Sports Medicine. Quantity and quality of exercise for developing and maintaining cardiorespiratory, musculoskeletal, and neuromotor fitness in apparently healthy adults: guidance for prescribing exercise. Med Sci Sports Exerc. 2011;43(7):1334-59. doi
doi...
and other authors in different sports1515. Lovell TWJ, Sirotic AC, Impellizzeri FM, Coutts AJ. Factors affecting perception of effort (session rating of perceived exertion) during rugby league training. Int J Sports Physiol Perform. 2013;8(1):62-9. doi
doi...
16. Moreira A, Kempton T, Aoki MS, Sirotic AC, Coutts AJ. The impact of 3 different-length between-matches microcycles on training loads in professional rugby league playersq. Int J Sports Physiol Perform. 2015;10(6):767-73. doi
doi...
17. Manzi V, Bovenzi A, Castagna C, Salimei PS, Volterrani M, Iellamo F. Training-load distribution in endurance runners: objective versus subjective assessment. Int J Sports Physiol Perform. 2015;10(8):1023-28. doi
doi...
-1818. Seiler KS, Kjerland Gø. Quantifying training intensity distribution in elite endurance athletes: is there evidence for an “optimal” distribution? Scand J Med Sci Sport. 2006;16(1):49-56. doi
doi...
. In addition, it is important to note that the%HRmax average between participants was 84.9 ± 3. Furthermore, the HR responses include both exercise time and passive rest.

Despite the reports from studies that have used HR responses to describe TL in FT sessions1919. Gist NH, Freese EC, Ryan TE, Cureton KJ. Effects of low-volume, high-intensity whole-body calisthenics on Army ROTC cadets. Mil Med. 2015;180(5):492-8. doi
doi...
20. Schleppenbach LN, Ezer AB, Gronemus SA, Widenski KR, Braun SI, Janot JM. Speed-and circuit-based high-intensity interval training on recovery oxygen consumption. Int J Exerc Sci. 2017;10(7):942-53. https://digitalcommons.wku.edu/cgi/viewcontent.cgi?article=1918&context=ijes
https://digitalcommons.wku.edu/cgi/viewc...
-21,21. Kliszczewicz B, Williamson C, Bechke E, McKenzie M, Hoffstetter W. Autonomic response to a short and long bout of high-intensity functional training. J Sports Sci. 2018;36(16):1872-9. doi
doi...
2727. Kliszczewicz B, Buresh R, Bechke E, Williamson C. Metabolic biomarkers following a short and long bout of high-intensity functional training in recreationally trained men. J Hum Sport Exerc. 2017;12(3)710-718. doi
doi...
, none have demonstrated HR responses distributed over intensity effort zones88. Edwards S. High performance training and racing. In: The Heart Rate Monitor Book. Sacramento, CA, Press, Feet Fleet; 1993. p.113-123., limiting the comparison. However, when comparing the mean%HRmax in the FT session, the values were very similar (84.9 ± 3% vs. 84.6 ± 5.3%) to the calisthenic exercise protocol with a similar volume (23 min-36.5 min)1919. Gist NH, Freese EC, Ryan TE, Cureton KJ. Effects of low-volume, high-intensity whole-body calisthenics on Army ROTC cadets. Mil Med. 2015;180(5):492-8. doi
doi...
.

Compared to CrossFit® protocols-High-Intensity Functional Training (HIFT)-the FTSESSION%HRmax average was lower than the values reported for both short HIFT (84.9 ± 3% vs. 92.7 ± 4%) and long HIFT (84.9 ± 3% vs. 91.3 ± 3%)21,21. Kliszczewicz B, Williamson C, Bechke E, McKenzie M, Hoffstetter W. Autonomic response to a short and long bout of high-intensity functional training. J Sports Sci. 2018;36(16):1872-9. doi
doi...
2727. Kliszczewicz B, Buresh R, Bechke E, Williamson C. Metabolic biomarkers following a short and long bout of high-intensity functional training in recreationally trained men. J Hum Sport Exerc. 2017;12(3)710-718. doi
doi...
. The characteristics of the HIFT protocols may explain these lower HR responses observed in the present study. First, CrossFit® protocols are considered the most intense FT models2828. Claudino JG, Gabbett TJ, Bourgeois F, Sá Souza H, Miranda RC, Mezencio B, et al. Crossfit overview: systematic review and meta-analysis. Sport Med - Open. 2018;4(1):11. doi
doi...
. Both HIFT protocols were performed utilizing weights and other equipment (e.g., dumbbells, kettlebells, rowing ergometer, Olympic barbell), and the total volume of the HIFT was at least two times lower than the FTSESSION (30 min vs. > 2 min for short HIFT; 15 min for long HIFT). Yet, the HIFT exercises were performed “all-out”66. Machado AF, Baker JS, Figueira Junior AJ, Bocalini DS. High-intensity interval training using whole-body exercises: training recommendations and methodological overview. Clin Physiol Funct Imaging. 2017;39(6):378-83. doi
doi...
with rest ad libitum. In contrast, all FTSESSION exercises had calisthenic characteristics and were performed in a fixed time with passive rest (2:1 proportion). According to Abderrahman et al. (2013)2929. Abderrahman AB, Zouhal H, Chamari K, Thevenet D, De Mullenheim PY, Gastinger S, et al. Effects of recovery mode (active vs. passive) on performance during a short high-intensity interval training program: a longitudinal study. Eur J Appl Physiol. 2013;113(6):1373-83. doi
doi...
, passive rest or recovery could make HR maintenance during intermittent exercise difficult.

The mean sRPE score (8.5 ± 1.2) was between “extremely hard” (score 8) and “almost maximum” (score 9) intensity classification, as proposed by Seiler and Kjerland1818. Seiler KS, Kjerland Gø. Quantifying training intensity distribution in elite endurance athletes: is there evidence for an “optimal” distribution? Scand J Med Sci Sport. 2006;16(1):49-56. doi
doi...
. This indicates that the FTSESSION was performed in the high-intensity zone. Compared to other calisthenics protocols performed at high intensity, the FTSESSION sRPE score was higher (8.5 ± 1.2 vs. 7.3 ± 1.3 and 8.5 ± 1.2 vs. 7.5 ± 1.0)19,19. Gist NH, Freese EC, Ryan TE, Cureton KJ. Effects of low-volume, high-intensity whole-body calisthenics on Army ROTC cadets. Mil Med. 2015;180(5):492-8. doi
doi...
2020. Schleppenbach LN, Ezer AB, Gronemus SA, Widenski KR, Braun SI, Janot JM. Speed-and circuit-based high-intensity interval training on recovery oxygen consumption. Int J Exerc Sci. 2017;10(7):942-53. https://digitalcommons.wku.edu/cgi/viewcontent.cgi?article=1918&context=ijes
https://digitalcommons.wku.edu/cgi/viewc...
. In addition to HR responses and sRPE, the [La] found after the FTSESSION supports the intensity characterization; the mean observed value of [Lapeak] indicates the significant contribution of the anaerobic glycolytic metabolism3030. Buchheit M, Laursen PB. High-intensity interval training, solutions to the programming puzzle. Sport Med. 2013;43(10):927-54. doi
doi...
. All [La] values verified post-exercise were higher than the secondary criterion concentration used to indicate effort made until maximal voluntary exhaustion (i.e., ≥ 8 mmol·L−1)3131. Howley ET, Bassett DR, Welch HG. Criteria for maximal oxygen uptake: review and commentary. Med Sci Sports Exerc. 1995;27(9):1292-1301. PMID.
PMID...
. Similar concentrations are generally found in high-intensity protocols, such as maximum tests performed on a treadmill (10.3 ± 2.0 mmol·L−1)3232. Machado FA, Kravchychyn ACP, Peserico CS, da Silva DF, Mezzaroba PV. A new age-based equation for predicting maximum heart rate in endurance-trained runners. Rev Bras Ciências do Esporte. 2018;40(1):100-5. doi
doi...
and during HIFT (long: 13.7 ± 1.5 mmol·L−1; short: 14.2 ± 2.0 mmol·L−1)21,21. Kliszczewicz B, Williamson C, Bechke E, McKenzie M, Hoffstetter W. Autonomic response to a short and long bout of high-intensity functional training. J Sports Sci. 2018;36(16):1872-9. doi
doi...
2727. Kliszczewicz B, Buresh R, Bechke E, Williamson C. Metabolic biomarkers following a short and long bout of high-intensity functional training in recreationally trained men. J Hum Sport Exerc. 2017;12(3)710-718. doi
doi...
.

For comparison, the post-exercise [La] values of the calisthenic protocol proposed by Gist et al.1919. Gist NH, Freese EC, Ryan TE, Cureton KJ. Effects of low-volume, high-intensity whole-body calisthenics on Army ROTC cadets. Mil Med. 2015;180(5):492-8. doi
doi...
were lower than the FTSESSION (11.1 ± 2.9 mmol·L−1 vs. 13.3 ± 2.9 mmol·L−1). According to Buchheit and Laursen3030. Buchheit M, Laursen PB. High-intensity interval training, solutions to the programming puzzle. Sport Med. 2013;43(10):927-54. doi
doi...
, the proportion of 2:1 for effort:pause-ratio increases anaerobic glycolytic energy demand, which can increase blood lactate levels at the end of the exercise.

The correlations between sRPE [Lapeak], ITL, and TRIMP suggest that the sRPE method can be used as a practical and effective method for quantifying TL in the FT model3333. Moreira A, Freitas CG, Nakamura FY, Aoki MS. Percepção de esforço da sessão e a tolerância ao estresse em jovens atletas de voleibol e basquetebol. Rev Bras Cineantropometria e Desempenho Hum. 2010;12(5):345-51. doi
doi...
. These findings highlight the broad scope of the RPE scale and endorse it as a method of TL quantification in a variety of exercise models and sports15,15. Lovell TWJ, Sirotic AC, Impellizzeri FM, Coutts AJ. Factors affecting perception of effort (session rating of perceived exertion) during rugby league training. Int J Sports Physiol Perform. 2013;8(1):62-9. doi
doi...
16,16. Moreira A, Kempton T, Aoki MS, Sirotic AC, Coutts AJ. The impact of 3 different-length between-matches microcycles on training loads in professional rugby league playersq. Int J Sports Physiol Perform. 2015;10(6):767-73. doi
doi...
18,18. Seiler KS, Kjerland Gø. Quantifying training intensity distribution in elite endurance athletes: is there evidence for an “optimal” distribution? Scand J Med Sci Sport. 2006;16(1):49-56. doi
doi...
33,33. Moreira A, Freitas CG, Nakamura FY, Aoki MS. Percepção de esforço da sessão e a tolerância ao estresse em jovens atletas de voleibol e basquetebol. Rev Bras Cineantropometria e Desempenho Hum. 2010;12(5):345-51. doi
doi...
3434. Lupo C, Tessiore A, Gasperi L, Gomez M. Session-RPE quantifying the load of different youth basketball training sessions. Biol Sport. 2017;34(1):11-17. doi
doi...
. In addition, the sRPE and TRIMP also positively correlated with the [Lapeak] and each other. This indicates that they may represent the magnitude of the stress suffered due to physical effort. These results were expected because these methods are used in intermittent exercise models and sports modalities following these characteristics15,15. Lovell TWJ, Sirotic AC, Impellizzeri FM, Coutts AJ. Factors affecting perception of effort (session rating of perceived exertion) during rugby league training. Int J Sports Physiol Perform. 2013;8(1):62-9. doi
doi...
16,16. Moreira A, Kempton T, Aoki MS, Sirotic AC, Coutts AJ. The impact of 3 different-length between-matches microcycles on training loads in professional rugby league playersq. Int J Sports Physiol Perform. 2015;10(6):767-73. doi
doi...
35,35. Manzi V, D'Ottavio S, Impellizeri FM, Chamari CK, Castagna C. Profile od weekly training load in elite male professional basketball players. J strength Cond Res. 2010;24(5):1399-1406. doi
doi...
3636. Gaudino P, Iaia FM, Strudwick AJ, Hawkins RD, Alberti G, Atkinson G, Gregson W, et al. Factors influencing perception of effort (Session-RPE) during elite soccer training. Int J Sports Physiol Perform. 2015;10(7):860-4. doi
doi...
. Moreover, the positive correlation found between Time Z5 and [Lapeak] demonstrates the influence of exercise intensity on lactate responses. This implies it is a good marker for metabolic stress analysis in this FT model.

The second phase of this study was characterized by TL monitoring during the eight weeks of the FTPROGRAM. The HR distribution, sRPE, ITL, and TRIMP were verified in all 16 sessions. The results of sessions 1 vs. 8, 8 vs. 9, and 9 vs. 16 were compared to analyze the sensitivity of the training adaptation monitoring methods1313. American College of Sports Medicine. Quantity and quality of exercise for developing and maintaining cardiorespiratory, musculoskeletal, and neuromotor fitness in apparently healthy adults: guidance for prescribing exercise. Med Sci Sports Exerc. 2011;43(7):1334-59. doi
doi...
and load progression11. Teixeira CVLS, Evangelista AL, Pereira PE de A, Da Silva-Grigoletto ME, Bocalini DS, Behm DG. Complexity: a novel load progression strategy in strength training. Front Physiol. 2019;10:1-5. doi
doi...
. The HR responses, sRPE, ITL, and TRIMP variations verified between sessions with the same protocols (sessions 1 vs. 8) and in the transition from protocol 1 to 2 (sessions 8 vs. 9, respectively), provided evidence for the validity of the monitoring methods for TL changes during the FTPROGRAM.

These results indicate the validity of these monitoring methods for assessing training load during an FT program37,37. Costa EC, Vieira CMA, Moreira A, Ugrinowitsch C, Castagna C, Aoki MS. Monitoring external and internal loads of Brazilian soccer referees during official matches. J Sport Sci Med. 2013;12(3):559-64.3838. Impellizzeri FM, Rampinini E, Coutts AJ, Sassi A, Marcora SM. Use of RPE based training load in soccer. Med Sci Sports Exerc. 2004;36(6):1042-7. doi
doi...
. The results are considered in conjunction with the cardiovascular and psychophysiological responses from the FT. The ITL and TRIMP results showed a similar pattern at a different magnitude. This suggests the importance of using both methods to monitor FT to obtain more comprehensive information on the participants’ psychophysiological responses. This provides a more robust monitoring training system that may aid in the optimization of the individual prescription. This could ensure better training program results. Notably, the correlation observed in the present study supports results observed in other studies3434. Lupo C, Tessiore A, Gasperi L, Gomez M. Session-RPE quantifying the load of different youth basketball training sessions. Biol Sport. 2017;34(1):11-17. doi
doi...
35. Manzi V, D'Ottavio S, Impellizeri FM, Chamari CK, Castagna C. Profile od weekly training load in elite male professional basketball players. J strength Cond Res. 2010;24(5):1399-1406. doi
doi...
-36,36. Gaudino P, Iaia FM, Strudwick AJ, Hawkins RD, Alberti G, Atkinson G, Gregson W, et al. Factors influencing perception of effort (Session-RPE) during elite soccer training. Int J Sports Physiol Perform. 2015;10(7):860-4. doi
doi...
38,38. Impellizzeri FM, Rampinini E, Coutts AJ, Sassi A, Marcora SM. Use of RPE based training load in soccer. Med Sci Sports Exerc. 2004;36(6):1042-7. doi
doi...
3939. Milanez VF, Dantas JL, Christofaro DGD, Fernandes RA. Resposta da frequência cardíaca durante sessão de treinamento de karatê. Rev Bras Med do Esporte. 2012;18(1):42-5. doi
doi...
. Our study, therefore, adds important information to existing literature, specifically regarding FT monitoring.

Conclusion

The present study demonstrated that the assessed FTSESSION can be characterized as a high-intensity exercise, based on the pattern of HR and sRPE responses, and reinforced by the [Lapeak]. Finally, the TL monitoring methods (sRPE and TRIMP) proved to be valid to be used during FT programs. Such information may serve as a basis for prescription and TL monitoring in similar FT programs while assisting professionals, students, and researchers concerning with this activity to better monitor the FT intervention programs. However, the study present limitations, such as the small number of participants in the FTPROGRAM, not controlling the sleep time and the environment temperature of the training local and lacking to monitor other training responses associated with the imposed TL, such as the stress tolerance, mood states, muscle soreness, and perceived recovery. Future studies should investigate these responses to FT training in order to improve the quality of the training monitoring.

Acknowledgments

The authors would like to thank all volunteers for their participation, Ph.D. Enio Ricardo Vaz Ronque, Ph.D. Solange de Paula Ramos, GETA and GEFEAH for technical and material support.

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Associate Editor: Iane de Paiva Novaes0000-0001-5956-4036, Universidade Estadual do Sudoeste da Bahia, Jequié, BA, Brazil. E-mail: ianepaiva@yahoo.com.br.

Publication Dates

  • Publication in this collection
    12 Sept 2022
  • Date of issue
    2022

History

  • Received
    04 Nov 2021
  • Accepted
    14 July 2022
Universidade Estadual Paulista Universidade Estadual Paulista, Av. 24-A, 1515, 13506-900 Rio Claro, SP/Brasil, Tel.: (55 19) 3526-4330 - Rio Claro - SP - Brazil
E-mail: motriz.rc@unesp.br