Skip to main content
NCBI home page
European Journal of Sport Science logoLink to European Journal of Sport Science
. 2024 May 17;24(7):878–888. doi: 10.1002/ejsc.12118

Adjunctive hiking bouts during 8 weeks regular sailing training improves cardiorespiratory and muscular responses during hiking emulation in highly trained sailors

Dandan Pan 1, Kaiyang Sun 2,✉, Xiuxia Liu 3
PMCID: PMC11235692  PMID: 38956795

Abstract

To investigate the effects of 8‐week hiking bench training on cardiorespiratory and muscular responses of highly trained sailors during hiking emulation. Twenty‐four sailors were assigned into two groups: the hiking bench training group (HTG, n = 12) and the control group (CG, n = 12). Both groups maintained their regular training with the HTG performed two additional hiking bench training sessions per week for 8 weeks, while the CG performed an equivalent duration of on‐water sailing training. Physiological responses were assessed by performing four successive 3‐min hiking bouts on a sailing emulation ergometer before and after the 8‐week training period. Comparing the pretest, both groups exhibited a significant decrease (p < 0.05) in the percentage of maximal oxygen uptake (%VO2max) and maximal heart rate (%HRmax); the HTG experienced a greater decrease in %VO2max in bouts 2 and 3. The root mean square (RMS) of rectus femoris (RF), vastus lateralis (VL), rectus abdominis (RA), and external oblique decreased significantly (p < 0.05), whereas the mean power frequency (MPF) of RF, VL, and RA exhibited an increasing trend. The RMS of RF and RA in HTG were lower than those in CG in the initial three bouts; VL and EA in HTG were lower than those in CG in bouts 1 and 2 (p < 0.05). The MPF of RA in HTG was significantly increased in bouts 2, 3, and 4 (p < 0.05). Eight‐week hiking bench training could improve hiking economy and the activation of lower limb and trunk muscles delaying the onset of fatigue in sailors.

Keywords: cardiorespiratory and muscular responses, hiking, hiking bench training, sailors

Highlights

  • Hiking is the most physically demanding task in dinghy sailing, eliciting highly specific cardiorespiratory, and muscular responses. Highly trained sailors attempt to improve the physiological response and performance of hiking through hiking bench training.

  • Hiking bench training involves a series of movement exercises performed by sailors on sailing emulation ergometer that are tailored specific profiles with the objective of optimizing sailing performance.

  • Hiking bench training can effectively enhance the economy of hiking among highly trained sailors, improve the activation of lower limb and trunk muscles, and delay the onset of fatigue in hiking. Hiking bench training can be used as an effective means of enhancing hiking performance for highly trained sailors.

1. INTRODUCTION

Hiking is a fundamental technique utilized by dinghy sailors during upwind and reaching maneuvers in sailing. It involves the sailor assuming a seated position on the side of the boat, hooking the feet under the foot strap near the centerline of the boat, and leveraging their body as a lever arm. By leaning back and hanging over the water, the sailor counteracts the tilting moment generated by the wind on the sails, thereby maintaining hull stability and enhancing sailing speed (Caraballo et al., 2019; Sun & Pan, 2023). A recent study has highlighted that in regatta, the upwind sailing duration constitutes over half of the race time and increases with the increase of wind speeds. Moreover, the ranking achieved in the first upwind leg strongly correlates with the performance of each race, thus serving as a valuable indicator for predicting sailors' performance (Pan & Sun, 2022). Maintaining a high‐quality hiking technique throughout a race is essential in competitive sailing, as poor hiking postures can diminish boat speed and compromise sailing direction (Marshall, 2009).

There are three types of hiking postures based on the hip angles corresponding to different wind conditions (Sekulic et al., 2006): (1) siting hiking (90–120° hip angle), (2) upright hiking (120–150° hip angle), and (3) extended hiking (EH; 150–180° hip angle). The physical fitness demands increase as the hip angles become larger (Pan et al., 2022). The predominant physiological load during hiking is formally defined as a “quasi‐isometric” concept, which elicits cardiorespiratory and muscular responses largely comparable to the classical observations during isometric exercise (Spurway, 2007). The anterior muscles of the body are subjected to considerable quasi‐isometric stress during hiking, with the quadriceps being the primary muscle recruited and reaching a higher percentage of maximum voluntary contraction (% MVC), followed by the abdominal muscles (Bourgois et al., 2017; Spurway, 2007). Bourgois et al. reported that isometric quadriceps strength determines neuromuscular fatigue and influences sailing performance (Bourgois et al., 2016). However, in the real sailing environment, sailors adapt their body positions and maneuvers according to the changes in wind speed, direction, and waves at any given time, involving rapid flexion and extension of the knees, hips, and trunk. Consequently, hiking is inherently a dynamic activity (Sun & Pan, 2023).

Training specificity is considered as fundamental in shaping training responses; its essence is that the training response elicited by a given exercise pattern is directly related to the physiological factors responding to the specific exercise stress (Gamble, 2013). Athletes aiming to enhance performance in a particular sport or skill must undergo specific training to induce the neuromuscular or metabolic adaptations requisite for that sport. The hiking bench serves as a land‐based sailing emulation ergometer specializing in the development of the hiking maneuvers. It allows researchers to impose a certain quasi‐isometric upwind sailing protocol (whereby, the researcher defines the exact sailing conditions) to several subjects or a single subject on different occasions (Callewaert, Geerts, et al., 2013). However, previous studies on hiking bench have primarily focused on exploring the biomechanical and physiological parameters of hiking process and have rarely investigated its potential as muscle‐strengthening machines for the development of specialized skills (Binns et al., 2009). Therefore, the purposes of this study were to examine the effects of 8 weeks of hiking bench training on the cardiorespiratory and muscular responses of highly trained sailors during hiking emulation, validate the effectiveness of the hiking bench training protocol in promoting specific adaptations, and to provide a basis for land‐based specific training of sailors. We hypothesized that the 8‐week hiking bench training would produce beneficial effects on the cardiorespiratory and muscular systems of sailors during hiking emulation with sailors in the hiking bench training group (HTG) showing greater improvements compared to the control group (CG).

2. METHODS

2.1. Participants

Twenty‐four single‐handed dinghy sailors (12 males and 12 females) with an average age of 22.3 ± 4.2 years, height of 176.4 ± 6.5 cm, weight of 72.0 ± 7.6 kg, and sailing experience of 10.3 ± 5.6 years participated in this study. All sailors possessed proficient sailing skills and were capable of completing structured and periodized training. Additionally, each sailor had achieved medals at national events and/or championships, indicating a high level of competitive experience. Participants were defined as highly trained sailors based on the classification framework established by McKay et al. (2021). Participants were first stratified by gender and then ranked by regatta's performance (National Sailing Championships ranking last year) into pairs (i.e., female sailors ranked 1 and 2 were pair one, those ranked 3 and 4 were pair two, etc.). Subsequently, the sailors in each pair were randomly assigned to either the HTG (six males and six females) or the CG (six males and six females). The details were shown in Table 1. The criteria for inclusion were that participants had at least 5 years of systematic sailing and resistance training experience, engage in sailing training sessions at least 4 times per week, and be able to complete all intervention programs. All participants were informed of the experimental steps and did not engage in strenuous physical activity for 48 h prior to the experimental test. The study protocols were approved by the Capital University of Physical Education and Sports Ethics Committee and according to the ethical principles of the World Medical Association Declaration of Helsinki.

TABLE 1.

Anthropometric information and training background of sailors.

Group HTG CG
Male (n = 6) Female (n = 6) Male (n = 6) Female (n = 6)
Age (years) 21.8 ± 3.1 22.0 ± 4.3 22.5 ± 4.6 22.7 ± 4.5
Height (cm) 183.1 ± 3.9 172.1 ± 4.6 181.6.1 ± 1.9 170.1 ± 1.6
Weight (kg) 79.2 ± 3.9 65.8 ± 2.4 78.7 ± 2.6 64.3 ± 2.8
Sailing experience (years) 9.3 ± 5.2 10.5 ± 5.9 10.2 ± 4.3 11.3 ± 6.6
Sailing hours per week (hours) 13.6 ± 1.1 13.8 ± 1.3 13.8 ± 1.3 13.3 ± 1.2
Fitness hours per week (hours) 7.7 ± 0.9 7.5 ± 1.5 8.0 ± 1.0 7.8 ± 0.9
Open in a new tab

2.2. Experimental design

Sailors in both groups maintained the same regular training regimen, consisting of at least four sailing sessions and three land‐based physical fitness sessions per week. The HTG performed two additional hiking bench training sessions of 30–45 min per week for 8 weeks, while the CG performed two extra on‐water upwind sailing sessions of the same duration in wind speeds higher than eight knots. To assess the effects of the interventions, all participants preformed an incremental load rowing test and a hiking emulation test (HET) before (pretest) and after (posttest) the experiment, respectively.

Two types of sailing emulation ergometer were utilized during the actual training sessions (Figure S1). One is the Laser Pro HikingbenchTM (https://hikingbench.com/), which is modeled based on the size and angle values of the cockpit section of the boat used as a standard in ILCA class, allowing sailors to engage in stable surface training on land. The other is adjustable hiking bench (AHB), which shares the same size as the Laser Pro HikingbenchTM but maintains an inclined position, requiring sailors to exert hiking force to maintain balance. The initial load for the bench to reach a balanced position is set at 53 kg, with four adjustable resistance springs located at the bottom of the hiking bench, each providing a load of 7.5 kg, allowing the sailor to adjust the hiking load by increasing the number of springs. The fundamental distinction between these two types of sailing emulation ergometer is that the AHB allows the hiking load to be adjusted without altering the sailor's hiking posture. The hiking bench training program was implemented progressively over an 8‐week period and consisted of different phases. The first phase (weeks 1–2) focused on stable surface static isometric training. The second phase (weeks 3–4) involved stable surface dynamic strength and endurance training. The third phase (weeks 5–6) incorporated unstable surface static isometric training, while the fourth phase (weeks 7–8) included unstable surface dynamic strength and power training. The implementation of an unstable surface was achieved by placing the hiking bench on the REAX BOARD smart floor with dynamic impulses technology (REAX BOARD 250, REAXING), which can perform sudden inclinations in every direction with a frontal incline of ±11% and a lateral incline of ±14%. The specific hiking bench training program is detailed in Table 2. Some of the hiking bench exercises are shown in Figure S2.

TABLE 2.

Hiking bench training program.

Exercise Time Set Assisted equipment
W1 EH, EH trunk rotation‐left/right, EH hands up, and trunk extensor endurance exercise (static) 30–45 s 3 HB
W2 Resistance band exercises: EH, EH trunk rotation‐left/right, EH hands up, and trunk extensor endurance exercise (static) 30–45 s 4 HB
W3 EH crunch, EH lateral flexion, EH trunk dynamic rotation, and trunk extensor endurance exercise (dynamic) 30–45 s 4 HB
W4 Resistance band exercises: EH trunk crunch, EH lateral flexion, EH trunk dynamic rotation, and trunk extensor endurance exercise (dynamic) 45–60 s 4 HB resistance band
W5 UH, UH trunk rotation‐left/right, single leg UH‐left/right, UH, and hands up with weight (2.5 kg) 30–45 s 3 AHB weight
W6 EH, EH trunk rotation‐left/right, single leg EH‐left/right, EH, and hands up with weight (5 kg) 30–45 s 4 AHB weight
W7 Medicine ball exercises: Alternating UH and EH, UH chest pass, UH trunk rotational throw, and UH backward throw 45–60 s 4 AHB MB
W8 Medicine ball exercises: Alternating UH and EH, EH chest pass, EH trunk rotational throw, and EH backward throw 45–60 s 4 AHB MB
Open in a new tab

Abbreviations: AHB, adjustable hiking bench; EH; extended hiking; HB, Laser Pro HikingbenchTM; MB, medicine ball; UH, upright hiking; W, week.

2.3. Incremental rowing test

Each participant performed a continuous incremental rowing test (IRT) on the ergometer (Concept2 RowErg, Concept2 Inc), starting work load at 120 W for male and 90 W for female, with load increments every 2 min, increasing by 30 W for male and 20 W for female at each stage. The drag factor was set at 130, typically corresponding to a damper setting of four for males, and 115 for females, equivalent to a damper setting of three. During IRT, participants' maximum oxygen uptake (VO2max) and maximal heart rate (HRmax) were determined using Cardiorespiratory Exercise Testing System (COSMED, K5) and the POLAR HR belt (POLAR, Polar Electroy). The VO2max value can be determined by the presence of three out of the following four criteria (Bringard et al., 2006; Hung et al., 2019): (1) respiratory exchange ratio >1.1; (2) HR in excess of 90% of age predicted HRmax (220–age); (3) an identification of a plateau (<150 mL/min increase) in oxygen uptake (VO2) despite a further increase load; and (4) failure of participant to continue.

2.4. Hiking emulation test

The HET protocol utilized in the present study has been described in detail elsewhere (Vogiatzis et al., 1996, 2011). Sailors performed four successive 3‐min hiking bouts, interspersed with 15‐s rest intervals to emulate tacking maneuvers on a Laser dinghy emulation ergometer. During the test, participants were instructed to extend their hip and knee joints as far as possible and maintain a self‐perceived maximally EH posture with the hip and knee angles reaching at least 120° and 140°, respectively (Boyas et al., 2009; García & Martínez, 2015).

Prior to the HET, participants performed a 5‐min cycling warm‐up, followed by a series of dynamic and static hiking exercises on the Laser Pro HikingbenchTM. Subsequently, participants were equipped with the MYON wireless surface electromyograph device (Myon) and performed three MVC tests lasting 5 s each for the main muscles involved in maintaining the hiking posture, with a sampling frequency of 2000 Hz. The rectus femoris (RF), vastus lateralis (VL), rectus abdominis (RA), and external oblique (EO) were selected as the main muscle groups for assessing the hiking activity (García & Martínez, 2015). After the MVC test, the participant completed HET wearing the Cardiorespiratory Exercise Testing System and the POLAR HR belt.

The VO2 and HR data collected in the middle 1 min of each bout of HET were averaged, resulting in representative mean values for VO2 and HR for each bout. The VO2max and HRmax obtained during IRT were set to 100%, and the values during HET expressed relative to those achieved during the IRT. Surface electromyography (sEMG) signals underwent signal processing, including low‐pass filtering at 400 Hz and high‐pass filtering at 20 Hz. Subsequently, sEMG signals obtained from the middle minute of each bout during IRT and the MVC test signals were normalized to a 1000 ms window (Silva et al., 2020). The muscle root mean square (RMS) during the test was normalized according to its own MVC to obtain RMS (%MVC) as an expression of motor unit recruitment and mean power frequency (MPF) as an expression of muscle activation frequency and fatigue development (Coburn et al., 2005). Bilateral RMS and MPF values for the same muscle were averaged to assess muscle recruitment and fatigue.

3. STATISTICAL ANALYSIS

Statistical analysis was performed with the SPSS Statistics V26.0 software (IBM Corporation). The data are presented as means (Ms) and standard deviations. Normal distribution of data was checked using the Kolmogorov–Smirnov test, and homogeneity was performed with Levene's test. Based on anthropometric information and training experience, an independent t‐test is needed. To assess differences in physiological indicators of hiking, we used a two‐way (groups × time) within‐between analysis of variance (ANOVA) with repeated measures. A least significant difference post hoc test was applied to determine the difference between groups or within‐group changes from pretest to posttest. The intraclass correlation coefficient (ICC) was used to determine the test–retest reliability of the measures. The level of significance was set at p < 0.05.

4. RESULT

No significant baseline differences were found between groups (HTG vs. CG) in age (21.9 ± 3.9 vs. 22.6 ± 4.8 years, p = −0.375), height (177.1 ± 7.3 vs. 175.8 ± 6.2 cm, p = 0.459), weight (72.5 ± 7.8 vs. 71.5 ± 8.0 kg, p = 0.854), training experience (9.9 ± 5.9 vs. 10.8 ± 5.9 years, p = 0.991), sailing hour per week (13.7 ± 1.2 vs. 13.5 ± 1.3 h, p = 0.811), and fitness hours per week (7.8 ± 1.0 vs. 7.7 ± 1.3 h, p = 0.731) before the intervention.

The results of the IRT are as follow: as these indicators are relevant to the cardiorespiratory parameters during the HET. No group × time interactions were observed for the VO2max and HRmax. Following training, both groups of sailors exhibited a significant increase in VO2max values (HTG: pretest, 53.53 ± 4.51 mL/kg/min; posttest, 55.72 ± 5.84 mL/kg/min; CG: pretest, 54.00 ± 5.45 mL/kg/min; posttest, 55.31 ± 5.64 mL/kg/min; and p < 0.001), while HRmax remained unchanged (HTG: pretest, 190.92 ± 7.22 beats/min; posttest, 192.30 ± 7.20 beats/min; CG: pretest, 188.50 ± 8.22 beats/min; posttest, 193.50 ± 7.03 beats/min; and p > 0.05). There were no significant differences between the HTG and CG in VO2max and HRmax.

All the variables showed highly reliable data with ICC ranging from 0.875 to 0.942 for the HET. Significant interaction effects (time and group) were observed during the test in both VO2 or HR values (p < 0.05) (Table 3). Post hoc test showed that compared to pretest data, sailors in both HTG and CG showed significant decrease in %VO2max and %HRmax values in each bout (p < 0.05). Notably, there was a significant difference between %VO2max of the HTG and CG in bouts 2 and 3 in the pretest (p = 0.021 and p = 0.036), but no significant difference in the posttest (Bout 2: The posttest %VO2max value decreased by 5.51% and 1.49% in HTG and CG, respectively; Bout 3: The posttest %VO2max value decreased by 5.52% and 1.91% in HTG and CG, respectively). Meanwhile, a significant difference in %HRmax values between HTG and CG in bout 3 in the posttest (HTG: 62.2 ± 6.60%, CG: 67.89 ± 6.39%, and p = 0.043).

TABLE 3.

The results of the VO2 and HR in hiking emulation test.

Bout HTG CG p
Pretest Posttest Pretest Posttest T × G T G
VO2max ml/kg/min 53.53 ± 4.51 55.72 ± 5.84 54.00 ± 5.45 55.31 ± 5.64 0.304 <0.001 0.989
%VO2max 1 a , b 23.15 ± 4.37 19.34 ± 2.57 21.17 ± 2.62 19.19 ± 2.03 0.038 <0.001 0.372
2 a , b , c 31.16 ± 4.56 25.65 ± 2.78 27.19 ± 3.12 25.70 ± 2.43 <0.001 <0.001 0.138
3 a , b , c 32.94 ± 4.99 27.42 ± 3.26 29.18 ± 3.05 27.27 ± 2.55 0.002 <0.001 0.168
4 a , b 34.62 ± 5.26 28.92 ± 3.37 31.18 ± 3.77 28.71 ± 2.92 0.013 <0.001 0.233
HRmax beats/min 190.92 ± 7.22 192.30 ± 7.20 188.50 ± 8.22 193.50 ± 7.03 0.636 0.387 0.986
%HRmax 1 a , b 63.92 ± 6.62 58.06 ± 5.93 64.85 ± 6.55 62.08 ± 5.73 0.003 <0.001 0.333
2 a , b 67.67 ± 6.51 60.7 ± 6.66 67.96 ± 6.28 65.57 ± 6.01 <0.001 <0.001 0.324
3 a , b , d 69.83 ± 5.88 62.2 ± 6.60 69.99 ± 6.50 67.89 ± 6.39 <0.001 <0.001 0.258
4 a , b 71.25 ± 6.51 64.87 ± 7.31 71.90 ± 6.83 69.66 ± 6.77 0.004 <0.001 0.329
Open in a new tab

Abbreviations: CG, control group; G, group factor; HTG, hiking bench training group; T, time factor; T × G, interaction of time and group factors.

a

Significant difference between pre and posttest in the HTG.

b

Significant difference between pre and posttest in the control group.

c

Significant difference between the HTG and the control group in pretest.

d

Significant difference between the HTG and the control group in posttest.

A two‐way ANOVA revealed a significant interaction effect for RMS values of RF, VL, RA, and EA in all bouts of the HET (p < 0.05) (Figure 1A). Subsequent post hoc tests revealed a decrease in RMS values of RF, VL, RA, and EO between HTG and CG after training (p < 0.05). There was no significant difference in RMS values among the four muscles between HTG and CG in the pretest (p > 0.05), but the RMS of RF and RA in the HTG were significantly lower than those in the CG in the initial three bouts (p < 0.05), and the RMS of VL and EA in the HTG was significantly lower than those in the CG in bouts 1 and 2 of the posttest (p < 0.05).

FIGURE 1.

(A) The change of RMS (%MVC) in two groups (B) The change of MPF in two groups. #, significant difference in the main factor (p < 0.05); *, significant difference between levels (p < 0.05); CG POST, posttest for control group; CG PRE, pretest for control group; CG PRE‐POST, control group between pre and posttest; EO, external oblique; HTG POST, posttest for hiking bench training group; HTG PRE, pretest for hiking bench training group; HTG PRE‐POST, hiking bench training group between pre and posttest; RA, rectus abdominis; RF, rectus femoris; VL, vastus lateralis.

graphic file with name EJSC-24-878-g002.jpg

graphic file with name EJSC-24-878-g001.jpg

Open in a new tab

The MPF values of the RF and RA exhibited significant interaction effects (p < 0.05) in bouts 2, 3, and 4 of the HET, and the MPF values of the VL and EO demonstrated significant interaction effects (p < 0.05) in bout 1 (Figure 1B). Compared to before training, sailors showed a tendency toward increased MPF values of RF, VL, and RA after training. The MPF values of RF significantly increased in bouts 2, 3, and 4 for the HTG (p < 0.001) and in bouts 3 and 4 for the CG after training (p = 0.031, p = 0.039). Meanwhile, the MPF of RF in the HTG were significantly higher than those the CG in bout 2 of the posttest (p = 0.031). The MPF of VL in the HTG were significantly lower than those in the CG in the first bout of the pretest (p = 0.021), but exhibited significant increase after training, with no significant difference between the two groups. The MPF of RA in the HTG were significantly increased in bouts 2, 3, and 4 of the posttest (p < 0.001), whereas no such increase was observed in the CG. There was a significant increase in MPF of EO in bout 1 of the posttest for the HTG (p = 0.002).

5. DISCUSSION

The purpose of this study was to investigate the effects of 8‐week hiking bench training on the cardiorespiratory and muscular responses of highly trained single‐handed dinghy sailors during hiking emulation, and to validate the effectiveness of the hiking bench training protocol in promoting specific adaptations. Our results indicated that the 8‐week hiking bench training not only elicited favorable effects on the cardiorespiratory system and metabolic responses but also improved muscle activation and fatigue responses in sailors during HET.

The VO2max is the gold standard for assessing aerobic capacity and is used as an indicator of superior performance in endurance athletes of mixed ability levels (Millet et al., 2003). A lower VO2 or energy consumption during a given task implies heightened efficiency, making athletes more likely to achieve outstanding performance (Keytel et al., 2005). HR is an important parameter for evaluating an individual's response to training loads and is also one of the most cost‐effective methods for assessing energy expenditure and physiological changes (Roos et al., 2013). Sailing predominantly relies on aerobic energy supply, the economy of movement and low energy consumption are directly correlated with sailing technique and performance (Onur et al., 2021).

In the present study, both groups of sailors showed a significant decrease in %VO2max and %HRmax in the posttest, which could be attributable to the increase in VO2max reducing the load intensity endured by the body to a certain extent, to the improvement in hiking technique increasing the efficiency of the movement, or both. It is noteworthy that although there was no significant difference in %VO2max between the HTG and CG; the %VO2max reduction in the HTG was higher than that of the CG notably in bouts 2 and 3 of the posttest. Additionally, the HTG exhibited a significantly lower %HRmax compared to the CG in bout 3. This could be influenced by the following factors: (1) Practice‐reduced efficiency. Lay et al. (2002) noted that well‐practiced individuals, while maintaining mechanical power output constant, achieve energy savings by reducing the internal mechanical work required to coordinate and control the limbs, thereby reducing HR and metabolic energy expenditure. Andrianopoulos et al. (2014) reported that highly‐ranked sailors exhibit superior cardiovascular and/or local muscle adaptations, facilitating more efficient oxygen transport and utilization during hiking. (2) Task‐specific effects. Specific static and dynamic exercises on the hiking bench induce particular cardiorespiratory changes and enhance the skeletal muscle's capacity to utilize oxygen. Studies have shown that both metabolic and mechanical stresses on the exercising skeletal muscle induce cardiovascular change, and specific local muscle training blunts the pressor response to isometric exercise (Fisher & White, 2004). Thus, it appears that prolonged static hiking training may diminish the metabolic stimulation of muscle afferent, thereby blunt the sensitivity of muscle metabolic reflexes. Conversely, when sailors perform dynamic hiking exercises, the lower limbs and trunk engage in alternating contraction and relaxation, leading to restricted blood flow during contraction and increased blood flow during relaxation, and resulting in enhanced oxygen delivery and oxidative metabolism (Kounoupis et al., 2020; Sun & Pan, 2023). (3) Core training benefits: Hiking movement itself is a form of core training, improving core stability and providing a stable pivot for force transfer between lower and upper limbs, thereby enhancing muscle work efficiency as well as economy of movement (Teixeira et al., 2019), and reducing overall energy consumption.

During hiking emulation, a significant increase in RMS and decrease in MPF have been demonstrated, reflecting an increase in additional motor unit recruitment and muscle fatigue, respectively (Callewaert et al., 2014). The present study showed a significant decrease in RMS values of RF, VL, RA, and EO in both groups of sailors after 8‐week training, which could be attributed to the reduced muscle activity under specific loads due to training. This may be associated with the enhanced oxidative capacity of slow muscle fibers in sailors resulting long‐term specific hiking training (Häkkinen et al., 2003). In addition, Callewaert, Boone, et al. (2013) reported that trained sailors performed numerous hours of quasi‐isometric knee‐extension exercises during sailing training, potentially altering their muscle activation patterns by predominantly recruiting slow‐twitch fibers, whereas untrained individuals may rely more on fast‐twitch fibers that fatigue more quickly over the same duration. Moreover, hiking posture is a position task involving numerous muscles, requires specific muscle synergies to stabilize the body. Boyas et al. (2009) observed that the individuals regularly engaged in specific hiking activities altered the distribution of the electrical activity among synergist muscles involved in the maintenance of hiking task, thereby developing higher intermuscular coordination ability. This enhanced coordination postponed the decline in force production of active muscle fibers and enabled sailors to delay the recruitment of fresh motor units.

Moreover, our results indicated a larger reduction in RMS values in HTG compared to CG, which was primarily attributed to practice or motor learning (Lay et al., 2002; Oliveira & Gonçalves, 2009). For sailors in the HTG, as a result of additional practice of land‐based hiking maneuvers, the synchronization of motor unit and firing rate of already active motor units increased, resulting in improved efficiency and requiring fewer motor units to be recruited to accomplish the same task (Creer et al., 2004; Oliveira & Gonçalves, 2009). On the other hand, there may be an increase in coordination of neural control patterns and a decrease in muscle co‐activation. Land‐based hiking exercises enable sailors to achieve tighter coordination in their muscle activation patterns during hiking and improve muscle coordination and control (Arabadzhiev et al., 2010). High skilled sailors can extend endurance time in the hiking posture by coordinating neural distribution of active muscles, such as reducing the utilization of trunk flexors and preferentially recruiting the quadriceps muscles (Maisetti et al., 2006). Schubert et al. (2008) observed that intensive training of motor skills may reduce the neural effort required to perform a task, leading to the automation of motor responses and shifting neural activation from higher to lower brain centers.

Fatigue is considered as a reduction of force or power output of the working muscle over time. In dinghy racing, achieving a higher sailing level is partially determined by a lower rate of neuromuscular fatigue during hiking (Bourgois et al., 2017). Literature findings suggest that the sEMG signal, MPF, shows a significant decreasing trend both in static and in dynamic fatiguing contraction conditions (Wang et al., 2018). In this study, the MPF values of RF, VL, and RA in sailors exhibited an increasing trend after 8‐week training. This could be attributed to an increase in muscle fiber conduction velocity and synchronization of motor units, resulting in improved motor efficiency and coordination, consequently delaying the onset of fatigue (Creer et al., 2004). Such improvements could assist sailors in extending hiking endurance, subsequently improving upwind sailing performance.

Notably, the MPF of RA significantly increased in the HTG but not in CG after 8‐week training, indicating the hiking bench training resulted in a slower development of fatigue for RA during hiking in sailors, and delayed the decline in force production of active muscle fibers. The abdominal muscles fulfill two crucial functions in hiking activity, one is spinal stabilization and the other is optimization of trunk flexion and extension (Caraballo et al., 2019). Abdominal muscles are considered to be the most easily fatigued muscles during EH (Boyas et al., 2009). Fatigued or too weak abdominal muscles may lead to increased activity and recruitment of the hip flexor muscles during hiking, which tends to promote lordosis, resulting in high compression and shearing forces acting the posterior surface of the vertebrae and intervertebral discs, thereby increasing the potential risk of chronic injury (Araújo et al., 2020). In contrast, maintaining a high level of abdominal muscle strength can sustain trunk extension outside the boat's side for a longer duration, thus exerting continuous leverage on the boat to maintain hull stability, particularly in moderate to high wind conditions. Compared to hiking bench training, traditional on‐water training environments are more dynamic and complex, the sailors need to adjust the hiking posture in continuously varying wind and wave conditions, and the trunk constantly moving in and out of the boat, resulting in increased dynamic body activity and less sustained EH time (Bourgois et al., 2017; Sekulic et al., 2006). Therefore, hiking bench training produces greater stimulation of the abdominal muscles, enhancing their resistance to fatigue, which could contribute to improved performance the sailors in EH posture during upwind sailing (Allen & De Jong, 2006).

The MPF values of RF, VL, and EO in the HTG differed from those the CG only in individual bouts of the test after 8‐week training. We believe this may be attributed to differences in the strategies employed by sailors to manage fatigue and muscle stimulation during hiking activities. The quadriceps is the most activated muscle during dinghy sailing; however, hiking is not always performed with both legs, as sailors alternate between legs to prevent fatigue, a phenomenon observed in both on‐water and on‐land tests (Bourgois et al., 2017). Additionally, the posture adopted during hiking primarily varies in the sagittal plane between an upright trunk and leaning backward. As the angle of trunk lean increases, the RA bears a greater load (Bourgois et al., 2017), whereas the EO primarily contributes to trunk stability and assists in spinal movement.

5.1. Limitations

There are some limitations to this study. Firstly, the sample size is relatively small, which may restrict the generalizability of the findings to a larger population. Secondly, the land‐based testing environment is more static compared to on‐water conditions, resulting in reduced trunk flexion, extension, and dynamic body adjustments among sailors, which may underestimate the energy expenditure during hiking. Furthermore, although we specified the joint angles of the sailors in the HET, the self‐perceived maximally EH posture is subjective and influenced by individual effort perception, which could impact our analysis of the training effects.

5.2. Conclusion

The 8‐week hiking bench training could improve hiking economy among highly trained sailors, elevate the activation level of lower limb and trunk muscles, and delay the onset of fatigue during hiking. Hiking bench training can be considered an effective means for optimizing hiking performance in highly trained sailors.

5.3. Perspectives

Based on the findings of this study, integrating two additional hiking bench training sessions per week over an 8‐week period emerges as a feasible training approach to enhance cardiorespiratory and muscular adaptations during hiking emulation among highly skilled sailors. Consequently, the introduction of a hiking bench can be an important tool when there is not enough time for on‐water training as an alternative. Future studies endeavors should focus on refining a more dynamic emulation protocol, incorporating precise adjustments for joint angles during hiking emulation tests.

AUTHOR CONTRIBUTIONS

Dandan Pan: Writing; conceptualization; methodology; formal analysis; writing‐original draft preparation. Kaiyang Sun: Data curation; writing review; software; and supervision. Xiuxia Liu: Writing review and supervision.

CONFLICT OF INTEREST STATEMENT

The authors declare that they have no conflicts of interest.

Supporting information

Supporting Information S1

EJSC-24-878-s001.docx (2.3MB, docx)

ACKNOWLEDGMENTS

This study was supported by the Shanghai Administration of Sports (No. 24T001).

REFERENCES

  1. Allen, J. B. , and De Jong M. R.. 2006. “Sailing and Sports Medicine: A Literature Review.” British Journal of Sports Medicine 40(7): 587–593. 10.1136/bjsm.2002.001669. [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Andrianopoulos, Vasileios , Louvaris Z., Orfanos I., Kouliaridou E., and Vogiatzis I.. 2014. “Quadriceps Muscle Oxygen Availability between Highly‐Ranked and Club Sailors during Successive Simulated Hiking Bouts.” Journal of Athletic Enhancement 3(2): 1000146. 10.4172/2324-9080.1000146. [DOI] [Google Scholar]
  3. Arabadzhiev, Todor I. , Dimitrov Vladimir G., Dimitrova Nonna A., and Dimitrov George V.. 2010. “Influence of Motor Unit Synchronization on Amplitude Characteristics of Surface and Intramuscularly Recorded EMG Signals.” European Journal of Applied Physiology 108(2): 227–237. 10.1007/s00421-009-1206-3. [DOI] [PubMed] [Google Scholar]
  4. Araújo, Laís Marinho de , Dell’Antonio Elisa, Hubert Marcel, Ruschel Caroline, Roesler Helio, and Pereira Suzana Matheus. 2020. “Trunk Muscular Endurance, Lumbar Spine Mobility and Hip Flexibility in Sailors with and without Low Back Pain.” Fisioterapia em Movimento 33: e003334. 10.1590/1980-5918.033.ao34. [DOI] [Google Scholar]
  5. Binns, Jonathan R. , Mooney John, Saunders Norman R., and Habgood Mark. 2009. “The Application of Sailing Simulation to Learning Environments.” In Paper Presented at the Conference Proceedings SIMTECT 2009. [Google Scholar]
  6. Bourgois, Jan G. , Callewaert Margot, Celie Bert, De Clercq Dirk, and Boone Jan. 2016. “Isometric Quadriceps Strength Determines Sailing Performance and Neuromuscular Fatigue during an Upwind Sailing Emulation.” Journal of Sports Sciences 34(10): 973–979. 10.1080/02640414.2015.1082613. [DOI] [PubMed] [Google Scholar]
  7. Bourgois, Jan G. , Dumortier Jasmien, Callewaert Margot, Celie Bert, Capelli Carlo, Sjøgaard Gisela, De Clercq Dirk, Boone Jan, and Boone J.. 2017. “Tribute to Dr Jacques Rogge: Muscle Activity and Fatigue during Hiking in Olympic Dinghy Sailing.” European Journal of Sport Science 17(5): 611–620. 10.1080/17461391.2017.1300328. [DOI] [PubMed] [Google Scholar]
  8. Boyas, S. , Maïsetti O., and Guével A.. 2009. “Changes in sEMG Parameters Among Trunk and Thigh Muscles during a Fatiguing Bilateral Isometric Multi‐Joint Task in Trained and Untrained Subjects.” Journal of Electromyography and Kinesiology 19(2): 259–268. 10.1016/j.jelekin.2007.09.002. [DOI] [PubMed] [Google Scholar]
  9. Bringard, A. , Perrey S., and Belluye N.. 2006. “Aerobic Energy Cost and Sensation Responses during Submaximal Running Exercise‐Positive Effects of Wearing Compression Tights.” International Journal of Sports Medicine 27(05): 373–378. 10.1055/s-2005-865718. [DOI] [PubMed] [Google Scholar]
  10. Callewaert, M. , Boone J., Celie B., De Clercq D., and Bourgois J.. 2013. “Quadriceps Muscle Fatigue in Trained and Untrained Boys.” International Journal of Sports Medicine 34(1): 14–20. 10.1055/s-0032-1316359. [DOI] [PubMed] [Google Scholar]
  11. Callewaert, Margot , Boone Jan, Celie Bert, De Clercq Dirk, and Bourgois Jan G.. 2014. “Cardiorespiratory and Muscular Responses to Simulated Upwind Sailing Exercise in Optimist Sailors.” Pediatric Exercise Science 26(1): 56–63. 10.1123/pes.2012-0203. [DOI] [PubMed] [Google Scholar]
  12. Callewaert, Margot , Geerts Stefan, Lataire Evert, Boone Jan, Vantorre Marc, and Bourgois Jan. 2013. “Development of an Upwind Sailing Ergometer.” International Journal of Sports Physiology and Performance 8(6): 663–670. 10.1123/ijspp.8.6.663. [DOI] [PubMed] [Google Scholar]
  13. Caraballo, Israel , González‐Montesinos José Luis, and Alías Antonio. 2019. “Performance Factors in Dinghy Sailing: Laser Class.” International Journal of Environmental Research and Public Health 16(24): 1–10. 10.3390/ijerph16244920. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Coburn, Jared W. , Housh Terry J., Cramer Joel T., Weir Joseph P., Miller Joshua M., Beck Travis W., Malek Moh H., Johnson Glen O., and Johnson Glen O.. 2005. “Mechanomyographic and Electromyographic Responses of the Vastus Medialis Muscle during Isometric and Concentric Muscle Actions.” The Journal of Strength & Conditioning Research 19(2): 412–420. 10.1519/00124278-200505000-00029. [DOI] [PubMed] [Google Scholar]
  15. Creer, A. Ricard , Ricard M. D., Conlee R. K., Hoyt G. L., and Parcell A. C.. 2004. “Neural, Metabolic, and Performance Adaptations to Four Weeks of High Intensity Sprint‐Interval Training in Trained Cyclists.” International Journal of Sports Medicine 25(02): 92–98. [DOI] [PubMed] [Google Scholar]
  16. Erkan, Günay , Onur Karasu, Caner Çetinkaya, and Tolga Şahin. 2021. “Blood Pressure Is the Key Physiological Indicator of Hiking Performance in Laser Sailors.” The Online Journal of Recreation and Sport 10(1): 1–10. 10.22282/ojrs.2021.76. [DOI] [Google Scholar]
  17. Fisher, James P. , and White Michael J.. 2004. “Muscle Afferent Contributions to the Cardiovascular Response to Isometric Exercise.” Experimental Physiology 89(6): 639–646. 10.1113/expphysiol.2004.028639. [DOI] [PubMed] [Google Scholar]
  18. Gamble, Paul . 2013. Strength and Conditioning for Team Sports: Sport‐specific Physical Preparation for High Performance. 2nd ed. Routledge. [Google Scholar]
  19. García, I. C. , and Martínez A. E.. 2015. “Determining Factors in the Performance of Hiking in Dinghy Sailing: A Literature Review.” European Journal of Human Movement 34: 15–33. [Google Scholar]
  20. Häkkinen, K. , Alen M., Kraemer W. J., Gorostiaga E., Izquierdo M., Rusko H., Mikkola J., et al. 2003. “Neuromuscular Adaptations during Concurrent Strength and Endurance Training versus Strength Training.” European Journal of Applied Physiology 89(1): 42–52. 10.1007/s00421-002-0751-9. [DOI] [PubMed] [Google Scholar]
  21. Hung, Kwong‐Chung , Chung Ho‐Wa, Yu Clare Chung‐Wah, Lai Hong‐Chung, and Sun Feng‐Hua. 2019. “Effects of 8‐week Core Training on Core Endurance and Running Economy.” PLoS One 14(3): e0213158. 10.1371/journal.pone.0213158. [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Keytel, L. R. , Goedecke J. H., Noakes Timothy D., Hiiloskorpi H., Laukkanen Raija, van der Merwe Lize, and Lambert E. V.. 2005. “Prediction of Energy Expenditure from Heart Rate Monitoring during Submaximal Exercise.” Journal of Sports Sciences 23(3): 289–297. 10.1080/02640410470001730089. [DOI] [PubMed] [Google Scholar]
  23. Kounoupis, Anastasios , Papadopoulos Stavros, Galanis Nikiforos, Dipla Konstantina, and Zafeiridis Andreas. 2020. “Are Blood Pressure and Cardiovascular Stress Greater in Isometric or in Dynamic Resistance Exercise?” Sports 8(4): 41. 10.3390/sports8040041. [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Lay, B. S. , Sparrow W. A., Hughes K. M., and O’Dwyer N. J.. 2002. “Practice Effects on Coordination and Control, Metabolic Energy Expenditure, and Muscle Activation.” Human Movement Science 21(5–6): 807–830. 10.1016/s0167-9457(02)00166-5. [DOI] [PubMed] [Google Scholar]
  25. Maisetti, O. , Boyas S., and Guevel A.. 2006. “Specific Neuromuscular Responses of High Skilled Laser Sailors during a Multi‐Joint Posture Sustained until Exhaustion.” International Journal of Sports Medicine 27(12): 968–975. 10.1055/s-2006-923893. [DOI] [PubMed] [Google Scholar]
  26. Marshall, R. 2009. “Quality of Dinghy Hiking: Effects on Speed and Heading.” In Paper Presented at the 27 International Conference on Biomechanics in Sports. [Google Scholar]
  27. McKay, Alannah K. A. , Stellingwerff Trent, Smith Ella S., Martin David T., Mujika Iñigo, Goosey‐Tolfrey Vicky L., Sheppard Jeremy, Burke Louise M., and Burke Louise M.. 2021. “Defining Training and Performance Caliber: A Participant Classification Framework.” International Journal of Sports Physiology and Performance 17(2): 317–331. 10.1123/ijspp.2021-0451. [DOI] [PubMed] [Google Scholar]
  28. Millet, Gregoire P. , Dreano Patrick, and Bentley David J.. 2003. “Physiological Characteristics of Elite Short‐ and Long‐Distance Triathletes.” European Journal of Applied Physiology 88(4): 427–430. 10.1007/s00421-002-0731-0. [DOI] [PubMed] [Google Scholar]
  29. Oliveira, Anderson de Souza Castelo , and Gonçalves Mauro. 2009. “EMG Amplitude and Frequency Parameters of Muscular Activity: Effect of Resistance Training Based on Electromyographic Fatigue Threshold.” Journal of Electromyography and Kinesiology 19(2): 295–303. 10.1016/j.jelekin.2007.07.008. [DOI] [PubMed] [Google Scholar]
  30. Pan, Dandan , and Sun Kaiyang. 2022. “Analysis of Sailing Variables and Performance of Laser Sailors with Different Rankings under the Condition of Certain Wind Speed.” Heliyon 8(12): e11682. 10.1016/j.heliyon.2022.e11682. [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Pan, Dandan , Zhong Bingshu, Guo Wei, and Xu Yixiao. 2022. “Physical Fitness Characteristics and Performance in Single‐Handed Dinghy and 470 Classes Sailors.” Journal of Exercise Science & Fitness 20(1): 9–15. 10.1016/j.jesf.2021.11.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Roos, Lilian , Taube Wolfgang, Brandt Monika, Heyer Louis, and Wyss Thomas. 2013. “Monitoring of Daily Training Load and Training Load Responses in Endurance Sports: What Do Coaches Want?” Schweizerische Zeitschrift für Sportmedizin und Sporttraumatologie 61(4): 30–36. [Google Scholar]
  33. Schubert, Martin , Beck Sandra, Taube Wolfgang, Amtage Florian, Faist Michael, and Gruber Markus. 2008. “Balance Training and Ballistic Strength Training Are Associated with Task‐specific Corticospinal Adaptations.” European Journal of Neuroscience 27(8): 2007–2018. 10.1111/j.1460-9568.2008.06186.x. [DOI] [PubMed] [Google Scholar]
  34. Sekulic, D. , Medved V., Rausavljevi N., and Medved V.. 2006. “EMG Analysis of Muscle Load during Simulation of Characteristic Postures in Dinghy Sailing.” The Journal of Sports Medicine and Physical Fitness 46(1): 20–27. [PubMed] [Google Scholar]
  35. Silva, Joao Renato , Sideris Vasileios, Chrismas Bryna C. R., and Read Paul J.. 2020. “Optimizing Athlete Assessment of Maximal Force and Rate of Development: A Comparison of the Isometric Squat and Mid‐thigh Pull.” bioRxiv, 2020.2004. 2017.046359. [Google Scholar]
  36. Spurway, Neil C. 2007. “Hiking Physiology and the “Quasi‐Isometric” Concept.” Journal of Sports Sciences 25(10): 1081–1093. 10.1080/02640410601165270. [DOI] [PubMed] [Google Scholar]
  37. Sun, Kaiyang , and Pan Dandan. 2023. “Analysis on the Characteristics and Relationships of Lower Limbs Strength and Power of Sailors in Different Positions and Levels.” PLoS One 18(8): e0289273. 10.1371/journal.pone.0289273. [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. Teixeira, Cauê V. La Scala , Evangelista Alexandre L., Silva Marta Santos, Bocalini Danilo Sales, Da Silva‐Grigoletto Marzo E., and Behm David G.. 2019. “Ten Important Facts about Core Training.” ACSM's Health & Fitness Journal 23(1): 16–21. 10.1249/fit.0000000000000449. [DOI] [Google Scholar]
  39. Vogiatzis, Ioannis , Andrianopoulos Vasileios, Louvaris Zafeiris, Cherouveim Evgenia, Spetsioti Stavroula, Vasilopoulou Maroula, and Athanasopoulos Dimitrios. 2011. “Quadriceps Muscle Blood Flow and Oxygen Availability during Repetitive Bouts of Isometric Exercise in Simulated Sailing.” Journal of Sports Sciences 29(10): 1041–1049. 10.1080/02640414.2011.574720. [DOI] [PubMed] [Google Scholar]
  40. Vogiatzis, I. , Spurway N. C., Jennett S., Wilson J., and Sinclair J.. 1996. “Changes in Ventilation Related to Changes in Electromyograph Activity during Repetitive Bouts of Isometric Exercise in Simulated Sailing.” European Journal of Applied Physiology and Occupational Physiology 72(3): 195–203. 10.1007/bf00838638. [DOI] [PubMed] [Google Scholar]
  41. Wang, Lejun , Wang Yuting, Ma Aidi, Ma Guoqiang, Ye Yu, Li Ruijie, and Lu Tianfeng. 2018. “A Comparative Study of EMG Indices in Muscle Fatigue Evaluation Based on Grey Relational Analysis during All‐Out Cycling Exercise.” BioMed Research International 2018: 1–8. 10.1155/2018/9341215. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supporting Information S1

EJSC-24-878-s001.docx (2.3MB, docx)

Articles from European Journal of Sport Science are provided here courtesy of Wiley

RESOURCES