Developing a methodology for estimating the drag in front-crawl swimming at various velocities

Understanding the Importance of Drag Coefficient Assessment for a Deeper Insight into the Hydrodynamic Profile of Swimmers

The main objective of this study was to confirm that the passive drag coefficient is less dependent on swimming speed than the passive drag, Froude, and Reynolds numbers, even as swimming speed increases. The sample consisted of 12 young proficient non-competitive swimmers (seven males and five females: 20.4 ± 1.9 years). Passive drag was measured with a low-voltage isokinetic engine at 1.2, 1.4, 1.6 and 1.8 m/s. The frontal surface area was measured using digital photogrammetry. Passive drag showed significant differences with a strong effect size over the four towing speeds measured (F = 116.84, p < 0.001, η2 = 0.91) with a quadratic relationship with speed. The Froude and Reynolds numbers had similar trends, but with linear relationships. Conversely, the passive drag coefficient showed non-significant differences across the four towing speeds (F = 3.50, p = 0.062, η2 = 0.33). This strongly suggests that the passive drag coefficient should be the variable of choice for monitoring the hydrodynamic profile of swimmers rather than the absolute value of passive drag.

Estimating Active Drag Based on Full and Semi-Tethered Swimming Tests

During full tethered swimming no hydrodynamic resistance is generated (since v = 0) and all the swimmer's propulsive force (FP) is utilized to exert force on the tether (FT = FP). During semi-tethered swimming FP can be made useful to one of two ends: exerting force on the tether (FST) or overcoming drag in the water (active drag: Da). At constant stroke rate, the mean propulsive force (FP) is constant and the quantity FP - FST (the "residual thrust") corresponds to Da. In this study we explored the possibility to estimate Da based on this method ("residual thrust method") and we compared these values with passive drag values (Dp) and with values of active drag estimated by means of the "planimetric method". Based on data obtained from resisted swimming (full and semi-tethered tests at 100% and 35, 50, 60, 75, 85% of the individual FT), active drag was calculated as: DaST = kaST.vST2 = FP - FST ("residual thrust method"). Passive drag (Dp) was calculated based on data obtained from passive towing tests and active drag ("planimetric method") was estimated as: DaPL = Dp.1.5. Speed-specific drag (k = D/v2) in passive conditions (kp) was )25 kg.m-1 and in active conditions (ka) )38 kg.m-1 (with either method); thus, DaST > Dp and DaST > DaPL. In human swimming active drag is, thus, about 1.5 times larger than passive drag. These experiments can be conducted in an ecological setting (in the swimming pool) by using basic instrumentation and a simple set of calculations.

Measurement of the active drag coefficient in front-crawl: A stroke-by-stroke analysis

The purpose of this study was to understand the change in active drag coefficient (CDA) over successive stroke cycles in front-crawl and the relationship between swimming speed and CDA. Eighteen national competitive swimmers (nine girls and nine boys with a mean age of 14.91 ± 0.59 years) were recruited. Swimming speed, propulsion (Ftotal) and frontal surface area were measured to calculate the CDA. Swimming speed (F = 1.790, p = 0.182, η2 = 0.07) and CDA (F = 0.907, p = 0.413, η2 = 0.06) did not change significantly over time, but swimming speed showed a decrease between the second and third stroke cycle. On the other hand, the Ftotal changed significantly over time (F = 4.437, p = 0.019, η2 = 0.21). Swimming speed and CDA showed a linear and strong relationship (R2 = 63.8 %). A stroke-by-stroke analysis showed that national level swimmers were able to maintain their hydrodynamic profile during a front-crawl maximal trial. Thus, it can be argued that a decrease in swimming speed can be related to a decrease in Ftotal. Swimming speed and CDA showed an inverse and significant relationship, with lower values of CDA resulting in faster swimming speeds.

Role of kicking action in front crawl: the inter-relationships between swimming velocity, hand propulsive force and trunk inclination

This study aimed to investigate the essential role of the kicking action in front crawl. To achieve this objective, we examined the relationships of the hand propulsive force and trunk inclination with swimming velocity over a wide range of velocities from 0.75 m·s-1 to maximum effort, including the experimental conditions of arm stroke without a pull buoy. Seven male swimmers performed a 25 m front crawl at various speeds under three swimming conditions: arm stroke with a pull buoy, arm stroke without a pull buoy (AWOB) and arm stroke with a six-beat kick (SWIM). Swimming velocity, hand propulsive force and trunk inclination were calculated using an underwater motion-capture system and pressure sensors. Most notably, AWOB consistently exhibited greater values than SWIM for hand propulsive force across the range of observed velocities (p < 0.05) and for trunk inclination below the severe velocity (p < 0.05), and these differences increased with decreasing velocity. These results indicate that 1) the kicking action in front crawl has a positive effect on reducing the pressure drag acting on the trunk, thereby allowing swimmers to achieve a given velocity with less hand propulsive force, and 2) this phenomenon is significant in low-velocity ranges.

Load-Velocity Profile and Active Drag in Young Female Swimmers: An Age-Group Comparison

PURPOSE

The present study aimed to establish differences in load-velocity profiling, active drag (AD), and drag coefficient (Cd) between 3 age groups of female swimmers.

METHODS

Thirty-three swimmers (11, 13, or 16 y old) were recruited. The individual load-velocity profile was determined for the 4 competitive swimming strokes. The maximal velocity (V0), maximal load (L0), L0 normalized to the body mass, AD, and Cd were compared between the groups. A 2-way analysis of variance and correlation analysis were conducted.

RESULTS

Compared with their younger counterparts, 16-year-old swimmers generally had larger V0, L0, and AD, which was particularly evident when comparing them with 11-year-old swimmers (P ≤ .052). The exception was breaststroke, where no differences were observed in L0 and AD and Cd was smaller in the 16-year-old group than the 11-year-old group (P = .03). There was a negative correlation between Cd and V0 for all groups in backstroke (P ≤ .038) and for the 11-year-old group and 13-year-old group in breaststroke (P ≤ .022) and front crawl (P ≤ .010). For the 16-year-old group, large correlations with V0 were observed for L0, L0 normalized to the body mass, and AD (P ≤ .010) in breaststroke and for L0 and AD with V0 in front crawl (P ≤ .042). In butterfly, large negative correlations with V0 were observed in the 13-year-old group for all parameters (P ≤ .027).

CONCLUSIONS

Greater propulsive force is likely the factor that differentiates the oldest age group from the younger groups, except for breaststroke, where a lower Cd (implying a better technique) is evident in the oldest group.

"Selecting the right tool for the job" a narrative overview of experimental methods used to measure or estimate active and passive drag in competitive swimming

Free-swimming performance depends strongly on the ability to develop propulsive force and minimise resistive drag. Therefore, estimating resistive drag (passive or active) may be important to understand how free-swimming performance can be improved. The purpose of this narrative overview was to describe and discuss experimental methods of measuring or estimating active and passive drag relevant to competitive swimming. Studies were identified using a mixed-model approach comprising a search of SCOPUS and Web of Science data bases, follow-up of relevant studies cited in manuscripts from the primary search, and additional studies identified by the co-authors based on their specific areas of fluid dynamics expertise. The utility and limitations of active and passive drag methods were critically discussed with reference to primary research domains in this field, 'swimmer morphology' and 'technique analysis'. This overview and the subsequent discussions provide implications for researchers when selecting an appropriate method to measure resistive forces (active or passive) relevant to improving performance in free-swimming.

How do swimmers control their front crawl swimming velocity? Current knowledge and gaps from hydrodynamic perspectives

The aim of this study was to review the literature on front crawl swimming biomechanics, focusing on propulsive and resistive forces at different swimming velocities. Recent studies show that the resistive force increases in proportion to the cube of the velocity, which implies that a proficient technique to miminise the resistive (and maximise the propulsive) force is particularly important in sprinters. To increase the velocity in races, swimmers increase their stroke frequency. However, experimental and simulation studies have revealed that there is a maximum frequency beyond which swimmers cannot further increase swimming velocity due to a change in the angle of attack of the hand that reduces its propulsive force. While the results of experimental and simulation studies are consistent regarding the effect of the arm actions on propulsion, the findings of investigations into the effect of the kicking motion are conflicting. Some studies have indicated a positive effect of kicking on propulsion at high swimming velocities while the others have yielded the opposite result. Therefore, this review contributes to knowledge of how the upper-limb propulsion can be optimised and indicates a need for further investigation to understand how the kicking action can be optimised in front crawl swimming.Abbreviations: C: Energy cost [kJ/m]; Ė: Metabolic power [W, kJ/s]; Fhand: Fluid resultant force exerted by the hand [N]; Ftotal: Total resultant force [N] (See Appendix A); Fnormal: The sum of the fluid forces acting on body segments toward directions perpendicular to the segmental long axis, which is proportional to the square of the segmental velocity. [N] (See Appendix A); Ftangent: The sum of the fluid forces acting on body segments along the direction parallel to the segmental long axis, which is proportional to the square of the segmental velocity. [N] (See Appendix A); Faddmass: The sum of the inertial force acting on the body segments due to the acceleration of a mass of water [N] (See Appendix A); Fbuoyant: The sum of the buoyant forces acting on the body segments [N] (See Appendix A); D: Fluid resistive force acting on a swimmer's body (active drag) [N]; T: Thrust (propulsive) force acting in the swimming direction in reaction to the swimmer's actions [N]; Thand: Thrust force produced in reaction to the actions of the hand [N]; Tupper_limb: Thrust force produced in reaction to the actions of the upper limbs [N]; Tlower_limb: Thrust force produced in reaction to the actions of the lower limbs [N]; Mbody: Whole-body mass of the swimmer [kg]; SF: Stroke frequency (stroke number per second) [Hz]; SL: Stroke length (distance travelled per stroke) [m]; v: Instantaneous centre of mass velocity of the swimmer [m/s]; V - : Mean of the instantaneous centre of mass velocities in the swimming direction over the period of the stroke cycle [m/s]; a: Centre of mass acceleration of the swimmer [m/s2]; V - hand: Mean of the instantaneous magnitudes of hand velocity over a period of time [m/s]; Ẇtot: Total mechanical power [W]; Ẇext: External mechanical power [W]; Ẇd: Drag power (mechanical power needed to overcome drag) [W, Nm/s]; α: Angle of attack of the palm plane with respect to the velocity vector of the hand [deg]; ηo: Overall efficiency [%]; ηp: Propelling efficiency [%]; MAD-system: Measuring Active Drag system; MRT method: Measuring Residual Thrust method.

Agreement between Different Methods to Measure the Active Drag Coefficient in Front-Crawl Swimming

The aim of this study was to analyze the agreement of the active drag coefficient measured through drag and propulsion methods. The sample was composed of 18 swimmers (nine boys: 15.9 ± 0.9 years; nine girls: 15.3 ± 1.2 years) recruited from a national swimming team. The velocity perturbation method was used as the drag measurement system and the Aquanex system as the propulsion system. For both sexes combined, the frontal surface area was 0.1128 ± 0.016 m2, swim velocity 1.54 ± 0.13 m.s-1, active drag 62.81 ± 11.37 N, propulsion 68.81 ± 12.41 N. The level of the active drag coefficient agreement was calculated based on the mean values comparison, simple linear regression, and Bland Altman plots. The mean data comparison revealed non-significant differences (p > 0.05) between methods to measure the active drag coefficient. Both the linear regression (R2 = 0.82, p < 0.001) and Bland Altman plots revealed a very high agreement. The active drag coefficient should be the main outcome used in the interpretation of the swimmers' hydrodynamic profile, because it is less sensitive to swimming velocity. Coaches and researchers should be aware that the active drag coefficient can also be calculated based on propulsion methods and not just based on drag methods. Thus, the swimming community can now use different equipment to measure the hydrodynamics of their swimmers.

Reliability and Validity of a Flume-Based Maximal Oxygen Uptake Swimming Test

A mode-specific swimming protocol to assess maximal aerobic uptake (VO₂max_sw) is vital to accurately evaluate swimming performance. A need exists for reliable and valid swimming protocols that assess VO₂max_sw in a flume environment. The purpose was to assess: (a) reliability and (b) "performance" validity of a VO₂max_sw flume protocol using the 457-m freestyle pool performance swim (PS) test as the criterion. Nineteen males (n = 9) and females (n = 10) (age, 28.5 ± 8.3 years.; height, 174.7 ± 8.2 cm; mass, 72.9 ± 12.5 kg; %body fat, 21.4 ± 5.9) performed two flume VO₂max_sw tests (VO₂max_swA and VO₂max_swB) and one PS test [457 m (469.4 ± 94.7 s)]. For test-retest reliability (Trials A vs. B), moderately strong relationships were established for VO₂max_sw (mL·kg^-1·min^-1)(r= 0.628, p = 0.002), O₂pulse (mL O₂·beat^-1)(r = 0.502, p = 0.014), VEmax (L·min^-1) (r = 0.671, p = 0.001), final test time (sec) (0.608, p = 0.004), and immediate post-test blood lactate (IPE (BLa)) (0.716, p = 0.001). For performance validity, moderately strong relationships (p < 0.05) were found between VO₂max_swA (r =-0.648, p = 0.005), O₂pulse (r= -0.623, p = 0.008), VEmax (r = -0.509 p = 0.037), and 457-m swim times. The swimming flume protocol examined is a reliable and valid assessment of VO₂max_sw., and offers an alternative for military, open water, or those seeking complementary forms of training to improve swimming performance.

A Simple Approach to Estimate the Drag Coefficients of a Submerged Floater

The calculation of the drag force is a fundamental requirement in the design of any submerged system intended for marine exploration. The calculation can be performed by analytic analysis, numerical modeling, or by a direct calculation performed in a designated testing facility. However, for complex structures and especially those with a non-rigid design, the analytic and numerical analyses are not sufficiently accurate, while the direct calculation is a costly operation. In this paper, we propose a simple approach for how to calculate the drag coefficient in-situ. Aimed specifically at the complex case of elastic objects whose modeling via Computer-Aided Design (CAD) is challenging, our approach evaluates the relation between the object's speed at steady-state and its mass to extract the drag coefficient in any desired direction, the hydro-static force, and, when relevant, also the thruster's force. We demonstrate our approach for the special case of a highly complex elastic-shaped floater that profiles the water column. The analysis of two such floaters in two different sea environments shows accurate evaluation results and supports our claim for robustness. In particular, the simplicity of the approach makes it appealing for any arbitrary shaped object.

Numerical and experimental methods used to evaluate active drag in swimming: A systematic narrative review

Introduction: In swimming, it is necessary to understand and identify the main factors that are important to reduce active drag and, consequently, improve the performance of swimmers. However, there is no up-to-date review in the literature clarifying this topic. Thus, a systematic narrative review was performed to update the body of knowledge on active drag in swimming through numerical and experimental methods.

Methods: To determine and identify the most relevant studies for this review, the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) approach was used.

Results: 75 studies related to active drag in swimming and the methodologies applied to study them were analyzed and kept for synthesis. The included studies showed a high-quality score by the Delphi scale (mean score was 5.85 ± 0.38). Active drag was included in seven studies through numerical methods and 68 through experimental methods. In both methods used by the authors to determine the drag, it can be concluded that the frontal surface area plays a fundamental role. Additionally, the technique seems to be a determining factor in reducing the drag force and increasing the propulsive force. Drag tends to increase with speed and frontal surface area, being greater in adults than in children due to body density factors and high levels of speed. However, the coefficient of drag decreases as the technical efficiency of swimming increases (i.e., the best swimmers (the fastest or most efficient) are those with the best drag and swimming hydrodynamics efficiency).

Conclusion: Active drag was studied through numerical and experimental methods. There are significantly fewer numerical studies than experimental ones. This is because active drag, as a dynamical phenomenon, is too complex to be studied numerically. Drag is greater in adults than in children and greater in men than in women across all age groups. The study of drag is increasingly essential to collaborate with coaches in the process of understanding the fundamental patterns of movement biomechanics to achieve the best performance in swimming. Although most agree with these findings, there is disagreement in some studies, especially when it is difficult to define competitive level and age. The disagreement concerns three main aspects: 1) period of the studies and improvement of methodologies; 2) discrimination of methodologies between factors observed in numerical vs. experimental methods; 3) evidence that drag tends to be non-linear and depends on personal, technical, and stylistic factors. Based on the complexity of active drag, the study of this phenomenon must continue to improve swimming performance.

The projected frontal area and its components during front crawl depend on lung volume

We examined the influence of lung volume on the vertical body position, trunk inclination, and projected frontal area (PFA) during swimming and the inter-relationships among these factors. Twelve highly trained male swimmers performed a 15 m front crawl with sustained maximal inspiration (INSP), maximal expiration (EXP), and intermediate (MID) at a target velocity of 1.20 m·s^-1 . Using our developed digital human model, which allows inverse kinematics calculations by fitting individual body shapes measured with a three-dimensional photonic image scanner to individually measured underwater motion capture data, vertical center of mass (CoM) position, trunk inclination, and PFA were calculated for each complete stroke cycle. In particular, the PFA was calculated by automatic processing of a series of parallel frontal images obtained from a reconstructed digital human model. The vertical CoM position was higher with a larger lung-volume level (P < 0.01). The trunk inclination was smaller in INSP and MID than in EXP (P < 0.01). PFA was smaller with a larger lung-volume level (P < 0.01). Additionally, there was a significant interaction of vertical CoM position and trunk inclination with PFA (P = 0.006). There was a negative association between PFA and vertical CoM position, and a positive association between PFA and trunk inclination less than the moderate vertical CoM position (each P < 0.05). These results obtained using our methodology indicate that PFA decreases with increasing lung volume due to an increase in vertical CoM position, and additionally due to a decrease in trunk inclination at low-to-moderate lung-volume levels.

Reliability of the active drag assessment using an isotonic resisted sprint protocol in human swimming

The purpose of the presents study was to investigate the reliability of the active drag (D_a) assessment using the velocity perturbation method (VPM) with different external resisted forces. Eight male and eight female swimmers performed 25 m sprints with five isotonic loads (1–2–3–4–5 kg for females; 1–3–5–7–9 kg for males), which were repeated twice on different days. The mean velocity and semi-tethered force were computed for each condition, and the free-swimming maximum velocity was estimated with load-velocity profiling. From the obtained variables, D_a at the maximum free-swimming condition was calculated using VPM. Absolute and typical errors and the intra-class correlation (ICC) were calculated to assess test–retest reliability. 95% confidence interval (95% CI) lower bound of ICC was larger than 0.75 in 3, 4 (females only) and 5 kg trials in both sexes (corresponding to 37–60 N additional resistance; all p < 0.001), which also showed small absolute and relative typical errors (≤ 2.7 N and ≤ 4.4%). In both sexes, 1 kg load trial (16–17 N additional resistance) showed the lowest reliability (95% CI of ICC; − 0.25–0.83 in males and 0.07–0.94 in females). These results suggested that a tethered force of 37–60 N should be used to assess D_a using VPM.

Vertical body position during front crawl increases linearly with swimming velocity and the rate of its increase depends on individual swimmers

Vertical body position during swimming is assumed to closely affect drag. It is consequently associated with swimming velocity; however, the association between swimming velocity and vertical body position has not yet been sufficiently established. Here, we aimed to clarify how vertical body position increases with front crawl velocity and whether there are inter-individual differences in velocity effect. Eleven college-level male swimmers performed a 15 m front crawl with sustained forced maximal inspiration at various swimming velocities. The body's centre of mass (CoM) was estimated from individual digital human models with inertial parameters using inverse kinematics. The horizontal CoM velocity and vertical CoM position from the water surface were averaged for one stroke cycle as respective indexes of swimming velocity and vertical body position. Linear mixed-effects model analysis revealed that there is a positive trend between swimming velocity and vertical CoM position during front crawl across the participants. These results indicate that swimming velocity is associated with vertical body position during front crawl. Additionally, the linear mixed-effects model with random intercepts and slopes was a better fit than that with only random intercepts, indicating that there are inter-individual differences in the rate of increase in vertical body position against swimming velocity.

Relationship Between Hand Kinematics, Hand Hydrodynamic Pressure Distribution and Hand Propulsive Force in Sprint Front Crawl Swimming

Purpose

This study investigated the relationship between hand kinematics, hand hydrodynamic pressure distribution and hand propulsive force when swimming the front crawl with maximum effort.

Methods

Twenty-four male swimmers participated in the study, and the competition levels ranged from regional to national finals. The trials consisted of three 20 m front crawl swims with apnea and maximal effort, one of which was selected for analysis. Six small pressure sensors were attached to each hand to measure the hydrodynamic pressure distribution in the hands, 15 motion capture cameras were placed in the water to obtain the actual coordinates of the hands.

Results

Mean swimming velocity was positively correlated with hand speed (r = 0.881), propulsive force (r = 0.751) and pressure force (r = 0.687). Pressure on the dorsum of the hand showed very high and high negative correlations with hand speed (r = −0.720), propulsive force (r = −0.656) and mean swimming velocity (r = −0.676). On the contrary, palm pressure did not correlate with hand speed and mean swimming velocity. Still, it showed positive correlations with propulsive force (r = 0.512), pressure force (r = 0.736) and angle of attack (r = 0.471). Comparing the absolute values of the mean pressure on the palm and the dorsum of the hand, the mean pressure on the dorsum was significantly higher and had a larger effect size (d = 3.71).

Conclusion

It is suggested that higher hand speed resulted in a more significant decrease in dorsum pressure (absolute value greater than palm pressure), increasing the hand propulsive force and improving mean swimming velocity.

Vision-Based System for Automated Estimation of the Frontal Area of Swimmers: Towards the Determination of the Instant Active Drag: A Pilot Study

Swimmers take great advantage by reducing the drag forces either in passive or active conditions. The purpose of this work is to determine the frontal area of swimmers by means of an automated vision system. The proposed algorithm is automated and also allows to determine lateral pose of the swimmer for training purposes. In this way, a step towards the determination of the instantaneous active drag is reached that could be obtained by correlating the effective frontal area of the swimmer to the velocity. This article shows a novel algorithm for estimating the frontal and lateral area in comparison with other models. The computing time allows to obtain a reasonable online representation of the results. The development of an automated method to obtain the frontal surface area during swimming increases the knowledge of the temporal fluctuation of the frontal surface area in swimming. It would allow the best monitoring of a swimmer in their swimming training sessions. Further works will present the complete device, which allows to track the swimmer while acquiring the images and a more realistic model of conventional active drag ones.

Case Study: Comparison of Swimsuits and Wetsuits Through Biomechanics and Energetics in Elite Female Open Water Swimmers

AIM

The authors investigated how the Arena Powerskin R-EVO Closed Back swimsuit and Arena Carbon Triwetsuit (full-sleeve wetsuit), both approved by the Fédération Internationale de Natation (FINA) regulations, affect biomechanics and energetics of 3 elite female open water (OW) swimmers at maximal and 4 submaximal swimming intensities.

METHODS

Three elite female OW swimmers (OW1 = 24 y, 1.64 m, 60 kg; OW2 = 23 y, 1.69 m, 65 kg; OW3 = 27 y, 1.63 m, 64.5 kg) were tested 1 week prior to a FINA/CNSG (China National Sports Group) Marathon Swim World Series event and 40 days before the 18th FINA World Championships 2019. Each OW swimmer completed 2 identical testing sessions, one with a swimsuit and other with a wetsuit, involving shoulder flexion power output assessed from medicine-ball throw, maximal performance and drag coefficient assessment, and an incremental intermittent swim test at 4 different relative intensities.

RESULTS

Estimated peak oxygen uptake was 4.4 L·min-1 for OW1, 5.6 L·min-1 for OW2, and 5.0 L·min-1 for OW3. Despite a distinct behavior observed on index of coordination for OW3, a null index of synchronization, increased stroke rate (mean difference = 2%-8%), reduced drag factor (minimum = -14%; maximum = -30%), lower energy cost (mean difference = -2% to -6%), and faster performance (mean difference = 2% to 3%) were observed with the wetsuit compared with swimsuit for all elite OW swimmers.

CONCLUSION

The wetsuit enhances submaximal swimming performance, and this increase is dependent on the OW swimmer's characteristics. The higher stroke rate and lower stroke length detected with wetsuit could be related to movement constraints imposed by the suit.

Lower lung-volume level induces lower vertical center of mass position and alters swimming kinematics during front-crawl swimming

We examined the impact of lung-volume levels on the vertical center of mass (CoM) position and kinematics during submaximal front-crawl swimming at constant velocity. Thirteen well-trained male swimmers (21.2 ± 2.0 years) swam the front-crawl for 15 m at a target velocity of 1.20 m s^-1 while holding one of three lung-volume levels: maximal inspiration (MAX), maximal expiration (MIN), and intermediate between these (MID). The three-dimensional positions of 25 reflective markers attached to each participant's body were recorded using an underwater motion capture system and then used to estimate the body's CoM. The swimming velocity and the vertical CoM position relative to the water's surface were calculated and averaged for one stroke cycle. Stroke rate, stroke length, kick rate, kick amplitude, kick velocity, and trunk inclination were also calculated for one stroke cycle. Swimming velocity was statistically comparable among the three different lung-volume levels (ICC [2,3] = 0.875). The vertical CoM position was significantly decreased with the lower lung-volume level (MAX: -0.152 ± 0.009 m, MID: -0.163 ± 0.009 m, MIN: -0.199 ± 0.007 m, P < 0.001). Stroke rate, kick rate, kick amplitude, kick velocity, and trunk inclination were significantly higher in MIN than in MAX and MID, whereas the stroke length was significantly lower (all P < 0.05). These results indicate that a lower lung-volume level during submaximal front-crawl swimming induces a lower vertical CoM position that is accompanied by a modulation of the swimming kinematics to overcome the increased drag arising from a larger projected frontal area.

Front Crawl Is More Efficient and Has Smaller Active Drag Than Backstroke Swimming: Kinematic and Kinetic Comparison Between the Two Techniques at the Same Swimming Speeds

The purpose of this study was to investigate differences in Froude efficiency (η _F ) and active drag (D _A ) between front crawl and backstroke at the same speed. η _F was investigated by the three-dimensional (3D) motion analysis using 10 male swimmers. The swimmers performed 50 m swims at four swimming speeds in each technique, and their whole body motion during one upper-limb cycle was quantified by a 3D direct linear transformation algorithm with manually digitized video footage. Stroke length (SL), stroke frequency (SF), the index of coordination (IdC), η _F , and the underwater body volume (UWV _body ) were obtained. D _A was assessed by the measuring residual thrust method (MRT method) using a different group of swimmers (six males) due to a sufficient experience and familiarization required for the method. A two-way repeated-measures ANOVA (trials and techniques as the factors) and a paired t-test were used for the outcomes from the 3D motion analysis and the MRT method, respectively. Swimmers had 8.3% longer SL, 5.4% lower SF, 14.3% smaller IdC, and 30.8% higher η _F in front crawl than backstroke in the 3D motion analysis (all p < 0.01), which suggest that front crawl is more efficient than backstroke. Backstroke had 25% larger D _A at 1.2 m⋅s^-1 than front crawl (p < 0.01) in the MRT trial. A 4% difference in UWV _body (p < 0.001) between the two techniques in the 3D motion analysis also indirectly showed that the pressure drag and friction drag were probably larger in backstroke than in front crawl. In conclusion, front crawl is more efficient and has a smaller D _A than backstroke at the same swimming speed.

The energy cost of swimming and its determinants

The energy expended to transport the body over a given distance (C, the energy cost) increases with speed both on land and in water. At any given speed, C is lower on land (e.g., running or cycling) than in water (e.g., swimming or kayaking) and this difference can be easily understood when one considers that energy should be expended (among the others) to overcome resistive forces since these, at any given speed, are far larger in water (hydrodynamic resistance, drag) than on land (aerodynamic resistance). Another reason for the differences in C between water and land locomotion is the lower capability to exert useful forces in water than on land (e.g., a lower propelling efficiency in the former case). These two parameters (drag and efficiency) not only can explain the differences in C between land and water locomotion but can also explain the differences in C within a given form of locomotion (swimming at the surface, which is the topic of this review): e.g., differences between strokes or between swimmers of different age, sex, and technical level. In this review, the determinants of C (drag and efficiency, as well as energy expenditure in its aerobic and anaerobic components) will, thus, be described and discussed. In aquatic locomotion it is difficult to obtain quantitative measures of drag and efficiency and only a comprehensive (biophysical) approach could allow to understand which estimates are "reasonable" and which are not. Examples of these calculations are also reported and discussed.

Effect of leg kick on active drag in front-crawl swimming: Comparison of whole stroke and arms-only stroke during front-crawl and the streamlined position

The purpose of this study was to examine the effect of leg kick on the resistance force in front-crawl swimming. The active drag in front-crawl swimming with and without leg motion was evaluated using measured values of residual thrust (MRT method) and compared with the passive drag of the streamlined position (SP) for the same swimmers. Seven male competitive swimmers participated in this study, and the testing was conducted in a swimming flume. Each swimmer performed front-crawl under two conditions: using arms and legs (whole stroke: WS) and using arms only (arms-only stroke: AS). Active drag and passive drag were measured at swimming velocities of 1.1 and 1.3 m s^-1 using load cells connected to the swimmer via wires. We calculated a drag coefficient to compare the resistances of the WS, AS and SP at each velocity. For both the WS and AS at both swimming velocities, active drag coefficient was found to be about 1.6-1.9 times larger than that in passive conditions. In contrast, although leg movement did not cause a difference in drag coefficient for front-crawl swimming, there was a large effect size (d = 1.43) at 1.3 m s^-1. Therefore, although upper and lower limb movements increase resistance compared to the passive condition, the effect of leg kick on drag may depend on swimming velocity.