Abstract
tudy was to assess the influence of year-long training of race walkers on physiological cost and total energy center of mass (CoM). The assessment performed was based on indicating the differences between the resulting energy cost in a group of elite race walkers walking at technical, threshold, and racing speeds calculated by physiological and biomechanical methods before beginning and after finishing a year-long training cycle. The study involved 12 competitive race walkers who had achieved champion or international champion level. Their aerobic endurance was determined by means of a direct method, applying an incremental exercise test on the treadmill. The gait of the participants was recorded using the 3D Vicon analysis system. Changes in mechanical energy amounted to the value of the total external work of the muscles needed to accelerate and lift the center of mass during a normalized gait cycle. The highest influence on the total external work increase for increasing speeds of gait in both examinations was attributed to the
participants was recorded using the 3D Vicon analysis system. Changes in mechanical energy amounted to the value of the total external work of the muscles needed to accelerate and lift the center of mass during a normalized gait cycle. The highest influence on the total external work increase for increasing speeds of gait in both examinations was attributed to the changes in the kinetic energy resulting from the center of mass movement. A statistically significant decrease of the mean value of total external work for racing speed was observed in the second examination (p< 0.001). An approx. 8% decrease (NS) of EE energy cost, standardized by body mass and distance covered, was found between the first and second examinations. The energy cost and total external work were significantly differentiated by the walkers’ gait speeds (p< 0.05–0.001). The energy cost significantly differed from the total external work atp< 0.001. Keywords:race walking; energy cost; total energy; maximal oxygen uptake; anaerobic threshold 1. Introduction The economics of movement involves the transformation of physiological energy produced by muscles into mechanical energy that powers the motor system. This concept includes two main components: efficiency, which refers to the conversion of chemical energy into mechanical energy within muscles, and effectiveness, which relates to the application of mechanical energy to achieve motion. This motion is observed as the displacement of the center of mass (CoM) within the gravitational field. To enhance clarity, it is essential to simplify and break down complex sentences, focusing on conveying each idea more concisely [1]. Efficiency is measured by physiological methods, whereas effectiveness is measured using biomechanical methods for individual movement techniques. As stressed by Yamada et al. [2], during a race walking competition, the final effect, i.e., race result, depends not only on maintaining a high level of gait speed but also on following the individual technique strategy despite growing fatigue. It is a very difficult task. As indicated by Brisswalter and Fougeron [3], race walkers are able to follow their individual Appl. Sci.2024,14, 8805.
only on maintaining a high level of gait speed but also on following the individual technique strategy despite growing fatigue. It is a very difficult task. As indicated by Brisswalter and Fougeron [3], race walkers are able to follow their individual Appl. Sci.2024,14, 8805.
Appl. Sci.2024,14, 8805 2 of 13 walking scheme only if energy cost is kept at a similar level. That is why the necessity of developing a high level of efficiency and effective individual movement technique, as well as resistance to organism fatigue, as sports success factors is frequently highlighted in works concerning the analysis of race walking [4–7]. The forerunners in measuring the energetics of race walking from a biomechanical perspective were Cavagna and Franzetti [8] as well as Marchetti et al. [9]. On an experimental basis, the authors calculated changes in the mechanical energy of the CoM in a gait cycle for different movement speeds. However, as indicated by Pavei et al. [10] in their survey work, there exist few reliable studies concerning the issue of gait energetics. Although many authors [4–6] stress that analysis of gait energetics, on an equal level with assessment of the mechanical power of the lower limbs and their efficiency, is the key element of gait technique analysis which can influence coaching in race walking, the level of studies differs, and they include many drawbacks affecting their value. Pavei et al. [10] point to some key deficiencies in current studies. They comprise testing athletes at training speeds, much lower than racing ones, and an insufficient number of cases and steps (often only 1 step was analyzed). Preatoni et al. [11] suggest that only an analysis of at least 15 steps allows a reliable description of the biomechanical variables of race walking. However, there are no works that truly illustrate the influence of long-term race walking training directed at the optimization of individual technique and maintenance of a high level of organism efficiency on energy expenditure during walking. A reaction to the lack of knowledge in this research field was an experiment whose initial results were presented by Chwała et al. [7]. The current study extends the presentation of the findings from the referenced work and includes a comparison of the outcomes from the first and second phases of research following a year of training designed to enhance individual techniques of race walking. The authors
in this research field was an experiment whose initial results were presented by Chwała et al. [7]. The current study extends the presentation of the findings from the referenced work and includes a comparison of the outcomes from the first and second phases of research following a year of training designed to enhance individual techniques of race walking. The authors of the work assessed the level of energy expenditure in elite race walkers moving at technical, threshold, and racing speeds. Next, after identifying individual technical errors, the principles of walker movement technique correction were elaborated. After the year-long implementation of individual guidelines of technique optimization, energy expenditure was assessed again using physiological and biomechanical methods. The outcome of the research was to obtain the comparative material demonstrated in the present work. The aim of this work was to determine the influence of a year’s training directed at optimization of individual technique and maintenance of high efficiency of movement on the level of energy expenditure assessed by physiological and biomechanical methods in elite race walkers. Assessment of the influence of gait biomechanical correction on the amount of physiological cost and total energy was analyzed based on race technique gait at threshold, racing, and technical speeds. A reduction in the amount of energy expended on work directly decreases the muscles’ demand for oxygen, which results in a decreased proportion of anaerobic metabolism without affecting the intensity of the exercise. Thus, the athlete can move faster consuming the same volume of oxygen [7]. It was assumed that correction of movement technique aiming at elimination of identified errors and its optimization regarding somatic build would have a positive effect on lowering the exercise’s physiological cost. 2. Materials and Methods 2.1. Characteristics of the Participants The study involved 12 elite race walkers who had achieved either championship or international level. The average age of the participants was 24.9 years in the first study and 25.9 years in the second study. The participants had an average height of 1.80 m and a body weight of 69 kg in the first study, and 1.81 m and 68.9
The study involved 12 elite race walkers who had achieved either championship or international level. The average age of the participants was 24.9 years in the first study and 25.9 years in the second study. The participants had an average height of 1.80 m and a body weight of 69 kg in the first study, and 1.81 m and 68.9 kg in the second study, respectively. Detailed characteristics, including BMI, can be found in Table. The training experience of the participants ranged from 6 to 20 years. Some of the participants were finalists in the Olympic Games and World Championships, and one was a European Championship medalist. Inclusion criteria included being an elite-level race walker with a minimum of 6 years of training experience and having competed at the national or
Appl. Sci.2024,14, 8805 3 of 13 international level. Exclusion criteria were any current injuries or medical conditions that could affect performance or participation in the study and failure to complete the full year of prescribed training. Table 1.Characteristics of the subjects. N = 12 Age [Years] Body Height [m] Body Mass [kg] BMI [kgm −2 ] I study 24.9 ±4.10 1.80 ±0.68 69 ±7.06 21.29 ±1.81 II study 25.9 ±4.10 1.81 ±0.76 68.9 ±0.8 21.03 ±1.26 2.2. Experimental Procedure The research was conducted twice: once in the initial period and again after a year of training aimed at optimizing individual race walking technique. Before the first main stage of the research, the aerobic capacity of each participant was determined, specifically maxi- mum oxygen uptake (VO2max) and anaerobic threshold, using a direct method involving an incremental exercise test on a treadmill. The same procedure was repeated after a year of targeted training to assess the impact of the training on the physiological cost and total external work. The research method for both stages of the experiment and the results of the first stage were precisely described in the work of Chwała et al. [7]. The results of the second stage of the experiment are presented in this paper. 2.3. Measurement Methods The energy cost for the race walkers was determined at three different speeds: technical speed (vt), threshold speed (vp), and racing speed (vs). Before the 8-min test, participants performed a warm-up session including gradual speed progression to adapt to the test conditions. Data were collected during the entire 8-min walking period at each speed. The energy cost was determined using an indirect method based on the net oxygen uptake for each of the analyzed walking speeds and immediately after their completion until the total oxygen debt was repaid. The caloric equivalent used was selected based on the current ratio of the volume of exhaled carbon dioxide to the volume of oxygen uptake (RER). Gait analysis was recorded using the Vicon Oxford Metrics system (Vicon, Oxford Metrics Ltd., Oxford, UK) with Nexus software, version 2.10.3. The system operated at a frequency
completion until the total oxygen debt was repaid. The caloric equivalent used was selected based on the current ratio of the volume of exhaled carbon dioxide to the volume of oxygen uptake (RER). Gait analysis was recorded using the Vicon Oxford Metrics system (Vicon, Oxford Metrics Ltd., Oxford, UK) with Nexus software, version 2.10.3. The system operated at a frequency of 120 frames per second, utilizing passive reflective markers placed on the participants’ skin according to the Golem model, allowing for precise 3D motion capture and biomechanical analysis. Changes in mechanical energy corresponding to the total external energy were calculated using the methods described by Cavagna et al. [12], Minetti et al. [13], and Schepens et al. [14]. Average energy changes were standardized per kilogram of body weight and per meter of distance traveled. In the next step, the average changes energy were standardized by kilogram of body mass and one meter of distance covered. Body mass was determined with the electronic scale “Tanita” Body Composition Analyzer (Tanita Corporation, Tokyo, Japan), and body height was measured using an anthropometer with an accuracy of 0.01 m. All exercise tests were performed on the treadmill, “Cardionics” model 2113 (Cardionics Inc., Webster, TX, USA). The respiratory system parameters were recorded by a portable ergospirometer Start-2000-M made by MES (Kraków, Poland). The participants’ heart rate was recorded by a recording device connected to the ergospirometer. 2.4. Training Description The training conducted over the year was typical for the preparatory period, character- ized by a high volume of aerobic and mixed work, with participants covering 140–180 km per week. After the first stage of the study, based on analyses of exhaled gases and 3D movement technique, individual schemes of race walking were elaborated
Appl. Sci.2024,14, 8805 4 of 13 for individual competitors as well as physiological EE and biomechanical (total energy) ∆Ec costs adequate for them. During the analyzed annual cycle, the athletes completed a weekly training amount ranging from 80 to 180 km, depending on their performance level and training period. The amount of training was primarily aimed at improving walking economy, while mixed-intensity methods (aerobic–anaerobic) were used to increase the threshold speed in walking. The obtained information was then analyzed and used to detect errors in competitors’ individual technique. Next, a model of changes in technique was elaborated for each competitor that was to change the movement pattern through optimization of step length ratio (following the index suggested by Murray et al. [15]) and frequency of steps in relation to actual walking speed at accepted values of vertical and side oscillations of the center of mass and duration of the swing phase. An individual competitor model was directed at saving energy and the symmetrical work of both lower and upper limbs as well as the pelvis. Additionally, the training focused on strengthening the extensors of the hip joint, whose importance was highlighted by Hoga et al. [5], and knee joint flexors, whose activity in the initial stage of the support phase controls extension of the knee joint, as indicated by Hanley and Bissas [6]. Subsequent muscles included in the strengthening work and coordination exercises in the year-long training were plantar and dorsal flexors, which control the support phase of the limb. Their significant role in shaping a proper scheme of race walking was underlined by Hoga et al. [5]. An important aspect of the training was the wide range of exercises coordinating the work of all the joints in the lower limbs with the work of pelvis, trunk, and upper limbs in order to obtain the best effects of energy transfer between body segments and to shape the driving force properly. After the year’s training, identical control measurements were taken using the same measurement tools. 2.5. Statistical Analysis To detect statistically significant differences between the energy cost and total external work
limbs with the work of pelvis, trunk, and upper limbs in order to obtain the best effects of energy transfer between body segments and to shape the driving force properly. After the year’s training, identical control measurements were taken using the same measurement tools. 2.5. Statistical Analysis To detect statistically significant differences between the energy cost and total external work of the muscles at different walking speeds, a repeated measures ANOVA and Tukey’s post hoc test were applied. The differences between the average values of energy cost and total external work were tested for significance using one-way analysis of variance, with walking speed as the dependent variable. Tukey’s post hoc test was used to identify statistically significant variable pairs in both analyses. 3. Results The results of the study are presented in Tables, as well as in Figures–3, which detail the changes in energy cost and total external work across different walking speeds before and after the year of training. In the incremental exercise test, participants achieved an average maximum oxygen uptake (VO2max) of 67.4±7.25 mL·kg −1 · min −1 , a value typical for elite endurance athletes capable of competing at the international level. The corresponding maximal lung ventilation and heart rate were 139.7±18.8 L·min −1 and 186±10.7 beats per minute, respectively. These physiological parameters reflect the high aerobic capacity of the participants, which is crucial for sustained performance in race walking. Table 2.Average values of physiological parameters during maximal exercise. VO2max mL·kg −1 ·min −1 VO2max L·min −1 VEmax L·min −1 HRmax sk·min −1 67.4±7.25 4.7 ±0.81 139.7 ±18.8 186 ±10.7 VO2max—maximum oxygen uptake. VEmax—maximal lung ventilation. HRmax—maximal heart rate.
Appl. Sci.2024,14, 8805 5 of 13 Table 3.The average energy cost of walking at technical (vt), threshold (vp), and racing (vs) speeds. V m·s −1 Study Energy Cost of EE Effort kJ·min −1 J·m −1 J·m −1 ·kg −1 vt= 3.1±0.19 I 51.2 ±10.05 267 ±52.3 3.86 ±0.55 II 48.38 ±6.04 252 ±31.5 3.68 ±0.42 vp= 3.7±0.13 I 69.2 ±11.04 312 ±49.7 4.51 ±0.51 II 65.72 ±7.90 vt−vp *** 296±35.6 vt−vp *** 4.30±0.21 vt−vp *** vs= 4.0±0.14 I 78.3 ±13.01 326 ±54.2 4.74 ±0.62 II 74.42±6.34 vt−vs **** 310±26.4 vt−vs **** 4.37±0.27 vt−vs **** I−IIp= 0.058 ***p< 0.005. ****p< 0.001.Appl. Sci. 2024, 14, x FOR PEER REVIEW 6 of 12 * p < 0.05. ** p < 0.01. *** p < 0.005. **** p < 0.001. Table 4 details the biomechanical costs of exercise, including potential energy (ΔEp), kinetic energy (ΔEk), and total external work (ΔEc), for each walking speed. This table provides a comprehensive overview of how these variables were affected by the year of training. Figure 1. The average values of the potential energy changes (ΔEp) in the second study at technical (vt), threshold (vp), and racing (vs) speeds, * p < 0.05. Figure 2. The average values of the kinetic energy changes ΔEk, at technical (vt), threshold (vp), and racing (vs) speeds, * p < 0.05, *** p < 0.005, **** p < 0.001. 3.5 3.7 3.9 4.1 4.3 4.5 4.7 4.9 5.1 5.3 5.5 vt vp vs ΔEp [kJ•min-1] res. I ΔEp [kJ•min-1] res. II * 7.0 9.0 11.0 13.0 15.0 17.0 19.0 vt vp vs ΔEk [kJ•min-1] res. I ΔEk[kJ•min-1] res. II * *** **** * Figure 1.The average values of the potential energy changes (∆Ep) in the second study at technical (vt), threshold (vp), and racing (vs) speeds, *p< 0.05.Appl. Sci. 2024, 14, x FOR PEER REVIEW 6 of 12 * p < 0.05. ** p < 0.01. *** p < 0.005. **** p < 0.001. Table 4 details the biomechanical costs of exercise, including potential energy (ΔEp), kinetic energy (ΔEk), and total external work (ΔEc), for each walking speed. This table provides a
and racing (vs) speeds, *p< 0.05.Appl. Sci. 2024, 14, x FOR PEER REVIEW 6 of 12 * p < 0.05. ** p < 0.01. *** p < 0.005. **** p < 0.001. Table 4 details the biomechanical costs of exercise, including potential energy (ΔEp), kinetic energy (ΔEk), and total external work (ΔEc), for each walking speed. This table provides a comprehensive overview of how these variables were affected by the year of training. Figure 1. The average values of the potential energy changes (ΔEp) in the second study at technical (vt), threshold (vp), and racing (vs) speeds, * p < 0.05. Figure 2. The average values of the kinetic energy changes ΔEk, at technical (vt), threshold (vp), and racing (vs) speeds, * p < 0.05, *** p < 0.005, **** p < 0.001. 3.5 3.7 3.9 4.1 4.3 4.5 4.7 4.9 5.1 5.3 5.5 vt vp vs ΔEp [kJ•min-1] res. I ΔEp [kJ•min-1] res. II * 7.0 9.0 11.0 13.0 15.0 17.0 19.0 vt vp vs ΔEk [kJ•min-1] res. I ΔEk[kJ•min-1] res. II * *** **** * Figure 2.The average values of the kinetic energy changes∆Ek, at technical (vt), threshold (vp), and racing (vs) speeds, *p< 0.05, ***p< 0.005, ****p< 0.001.
Description
This study evaluates the impact of training on energy cost in elite race walkers.