The effect of using paddles on hand propulsive forces and Froude efficiency in arm-stroke-only front-crawl swimming at various velocities

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.

Effects of exceeding stroke frequency of maximal effort on hand kinematics and hand propulsive force in front crawl

This study aimed to assess kinematic and kinetic changes in front crawl with various stroke frequency (SF) conditions to investigate why swimming velocity (SV) does not increase above a certain SF (SFmax). Eight male swimmers performed 20 m front crawl four times. The first trial involved maximal effort, whereas SF was controlled during the next three trials. The instructed SFs were 100 (T100%), 110 (T110%), and 120% (T120%) of the SFmax. Through pressure measurement and underwater motion analysis, hand propulsive force (calculated by the difference between the palm and dorsal pressure value and the hand area) and the angle of attack of the hand were quantified, and differences between trials were assessed by a repeated-measures ANOVA. There was no difference in SV between the conditions, while the angle of attack during the latter half of the underwater stroke at T120% was smaller by 25.7% compared with T100% (p = 0.007). The lower angle of attack induced a lower pressure value on the palm that consequently caused a smaller hand propulsive force at T120% than T100% (p = 0.026). Therefore, the decrease in the angle of attack must be minimised to maintain the hand propulsive force.

How Technique Modifications in Elite 100m Swimmers Might Improve Front Crawl Performances to Podium Levels: Swimming 'Chariots of Fire'

In this paper ways in which performance in 100 m front crawl might be improved are explored. Researchers were identified as 'primary sources' to provide a rationale for how swimmers might improve their performance and to estimate the potential magnitude of improvement. The researchers selected as the primary sources were identified from an initial search of the Scopus and Web of Science data bases using keywords appropriate for the race phases including start, stroking, turn, and finish and their component sub-phases. Recent research was prioritised to ensure that the latest knowledge was considered. Based on an analogy drawn from the 'Chariots of Fire' movie, the hypothetical question was asked: how can we reduce the 100 m time by 0.5s of a swimmer who is already an elite performer? Estimates of potential improvement ranged from 0.013s for the reaction time in the start phase to 1.0s by optimising mid-pool kicking to minimise drag. It is concluded that even at the very elite level, fine-tuning to optimise performance in the different phases of the race could elevate an elite swimmer to podium level performance.

Kinematic and kinetic parameters to identify water polo players' eggbeater kick techniques

This study aimed to clarify the kinematic and kinetic parameters that identify the technical differences in the eggbeater kick. Twelve water polo players performed the eggbeater kick, and its kinematics were recorded by a motion capture system. Pressure distributions around the feet were measured by sixteen pressure sensors attached to the dorsal and plantar surfaces of the feet, from which the resultant fluid force acting on the feet and the vertical component of the force (i.e., propulsive force) were estimated. Repeated-measures analysis of variance (including post hoc test) results showed that the pressure difference, due to negative pressure on the dorsal side of the foot, around the first toe was significantly larger than the other foot segments (difference of up to 7 kN/m2, P < 0.01). Moreover, cluster analysis (including Fisher information) results showed that the kinetic (fluid force and pressure) data had a major influence on clustering; the highest Fisher information was 10.42 for the mean propulsive force. Among the kinematic foot parameters, the influence of the foot angle data on clustering was large, suggesting its importance as a technical parameter of the eggbeater kick in relation to the kinetic data.

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.

The role of the biomechanics analyst in swimming training and competition analysis

Swimming analysts aid coaches and athletes in the decision-making by providing evidence-based recommendations. The aim of this narrative review was to report the best practices of swimming analysts that have been supporting high-performance athletes. It also aims to share how swimming analysts can translate applied research into practice. The role of the swimming analyst, as part of a holistic team supporting high-performance athletes, has been expanding and is needed to be distinguished from the job scope of a swimming researcher. As testing can be time-consuming, analysts must decide what to test and when to conduct the evaluation sessions. Swimming analysts engage in the modelling and forecast of the performance, that in short- and mid-term can help set races target-times, and in the long-term provide insights on talent and career development. Races can be analysed by manual, semi-automatic or fully automatic video analysis with single or multi-cameras set-ups. The qualitative and quantitative analyses of the swim strokes, start, turns, and finish are also part of the analyst job scope and associated with race performance goals. Land-based training is another task that can be assigned to analysts and aims to enhance the performance, prevent musculoskeletal injuries and monitor its risk factors.

Propulsive forces on water polo players' feet from eggbeater kicking estimated by pressure distribution analysis

The purpose of this study was to characterise the unsteady propulsive force during eggbeater kicking by a fluid force estimation method based on pressure distribution analysis. The eggbeater kick was performed by six male water polo players. The participants' eggbeater kicking motions were recorded by three cameras, and the kinematic foot variables were analysed. The pressure distributions around the foot were measured by four pairs of pressure sensors attached to the dorsal and plantar surfaces of the participants' right foot. The resultant fluid force acting on the foot was estimated from the measured pressure and area of the foot. The calculated propulsive force increased with the pressure difference between the plantar and dorsal sides of the foot, which was mainly related to the decrease in pressure on the dorsal side, and peaked when the foot passed its maximum velocity and began to decelerate. These results cannot be elucidated only by conventional biomechanical theories of swimming propulsion (Newton's laws of motion and the quasi-steady approach) but instead indicate a high possibility that the exerted propulsive force is induced by the effects of unsteady water flow.

Performance Tiers within a Competitive Age Group of Young Swimmers Are Characterized by Different Kinetic and Kinematic Behaviors

The present study aimed to analyze swimmers' in-water kinetic and kinematic behaviors according to different swimming performance tiers within the same age group. An amount of 53 highly trained swimmers (girls and boys: 12.40 ± 0.74 years) were split up into 3 tiers based on their personal best performance (i.e., speed) in the 50 m freestyle event (short-course): lower-tier (1.25 ± 0.08 m·s^-1); mid-tier (1.45 ± 0.04 m·s^-1); and top-tier (1.60 ± 0.04 m·s^-1). The in-water mean peak force was measured during a maximum bout of 25 m front crawl using a differential pressure sensors system (Aquanex system, Swimming Technology Research, Richmond, VA, USA) and defined as a kinetic variable, while speed, stroke rate, stroke length, and stroke index were retrieved and considered as kinematic measures. The top-tier swimmers were taller with a longer arm span and hand surface areas than the low-tier, but similar to the mid-tier. While the mean peak force, speed and efficiency differed among tiers, the stroke rate and stroke length showed mixed findings. Coaches should be aware that young swimmers belonging to the same age group may deliver different performance outcomes due to different kinetic and kinematic behaviors.

Using Statistical Parametric Mapping to Compare the Propulsion of Age-Group Swimmers in Front Crawl Acquired with the Aquanex System

Understanding the difference in each upper limb between age groups can provide deeper insights into swimmers’ propulsion. This study aimed to: (1) compare swimming velocity and a set of kinematical variables between junior and juvenile swimmers and (2) compare the propulsion outputs through discrete and continuous analyses (Statistical Parametric Mapping—SPM) between junior and juvenile swimmers for each upper limb (i.e., dominant and non-dominant). The sample was composed of 22 male swimmers (12 juniors with 16.35 ± 0.74 years; 10 juveniles with 15.40 ± 0.32 years). A set of kinematic and propulsion variables was measured at maximum swimming velocity. Statistical Parametric Mapping was used as a continuous analysis approach to identify differences in the propulsion of both upper limbs between junior and juvenile swimmers. Junior swimmers were significantly faster than juveniles (p = 0.04, d = 0.86). Although juniors showed higher propulsion values, the SPM did not reveal significant differences (p < 0.05) for dominant and non-dominant upper limbs between the two age groups. This indicates that other factors (such as drag) may be responsible for the difference in swimming velocity. Coaches and swimmers should be aware that an increase in propulsion alone may not immediately lead to an increase in swimming velocity.

Understanding the Role of Propulsion in the Prediction of Front-Crawl Swimming Velocity and in the Relationship Between Stroke Frequency and Stroke Length

Introduction: This study aimed to: 1) determine swimming velocity based on a set of anthropometric, kinematic, and kinetic variables, and; 2) understand the stroke frequency (SF)–stroke length (SL) combinations associated with swimming velocity and propulsion in young sprint swimmers.

Methods: 38 swimmers (22 males: 15.92 ± 0.75 years; 16 females: 14.99 ± 1.06 years) participated and underwent anthropometric, kinematic, and kinetic variables assessment. Exploratory associations between SL and SF on swimming velocity were explored using two two-way ANOVA (independent for males and females). Swimming velocity was determined using multilevel modeling.

Results: The prediction of swimming velocity revealed a significant sex effect. Height, underwater stroke time, and mean propulsion of the dominant limb were predictors of swimming velocity. For both sexes, swimming velocity suggested that SL presented a significant variation (males: F = 8.20, p < 0.001, η² = 0.40; females: F = 18.23, p < 0.001, η² = 0.39), as well as SF (males: F = 38.20, p < 0.001, η² = 0.47; females: F = 83.04, p < 0.001, η² = 0.51). The interaction between SL and SF was significant for females (F = 8.00, p = 0.001, η² = 0.05), but not for males (F = 1.60, p = 0.172, η² = 0.04). The optimal SF–SL combination suggested a SF of 0.80 Hz and a SL of 2.20 m (swimming velocity: 1.75 m s⁻¹), and a SF of 0.80 Hz and a SL of 1.90 m (swimming velocity: 1.56 m s⁻¹) for males and females, respectively. The propulsion in both sexes showed the same trend in SL, but not in SF (i.e., non-significant variation). Also, a non-significant interaction between SL and SF was observed (males: F = 0.77, p = 0.601, η² = 0.05; females: F = 1.48, p = 0.242, η² = 0.05).

Conclusion: Swimming velocity was predicted by an interaction of anthropometrics, kinematics, and kinetics. Faster velocities in young sprinters of both sexes were achieved by an optimal combination of SF–SL. The same trend was shown by the propulsion data. The highest propulsion was not necessarily associated with higher velocity achievement.

Three-dimensional front crawl arm-stroke efficiency and hand displacement in male and female swimmers

This study aimed (i) to verify if underwater horizontal, vertical and medio-lateral hand displacements (HD), in pull and push phases of the front crawl stroke, can be associated with arm-stroke efficiency (ƞp) and (ii) to compare np and selected kinematic variables between male and female swimmers. Ten male and 10 female swimmers performed an all-out front crawl 25-m test. Data were obtained with six synchronised video cameras (60 Hz) and analysed with a three-dimensional method. Results for males and females were respectively, as follows: (i) horizontal HD: 0.55 ± 0.06 m and 0.61 ± 0.09 m (p = 0.062; d = 0.78); vertical HD: 0.68 ± 0.06 m and 0.58 ± 0.07 m (p < 0.001; d = 1.53); and medio-lateral HD: 0.22 ± 0.07 m and 0.16 ± 0.03 m (p = 0.012; d = 1.11); (ii) ƞp: 0.33 ± 0.02 and 0.32 ± 0.03 (p = 0.48; d = 0.39); (iii) vCOM: 1.77 ± 0.06 m∙s-1 and 1.55 ± 0.10 m∙s-1 (p < 0.001; d = 2.42). Multiple linear regression (p = 0.019) indicated that horizontal and medio-lateral HD were able to predict np. The lower the horizontal hand displacement, the higher the ƞp.

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.

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.

Adaptability in Swimming Pattern: How Propulsive Action Is Modified as a Function of Speed and Skill

The objectives of this study were to identify how spatiotemporal, kinetic, and kinematic parameters could (i) characterize swimmers' adaptability to different swimming speeds and (ii) discriminate expertise level among swimmers. Twenty male participants, grouped into (a) low-, (b) medium-, and (c) high-expertise levels, swam at four different swim paces of 70, 80, 90% (for 20 s), and 100% (for 10 s) of their maximal speed in a swimming flume. We hypothesized that (i) to swim faster, swimmers increase both propulsion time and the overall force impulse during a swimming cycle; (ii) in the frequency domain, expert swimmers are able to maintain the relative contribution of the main harmonics to the overall force spectrum. We used three underwater video cameras to derive stroking parameters [stroke rate (SR), stroke length (SL), stroke index (SI)]. Force sensors placed on the hands were used to compute kinetic parameters, in conjunction with video data. Parametric statistics examined speed and expertise effects. Results showed that swimmers shared similarities across expertise levels to increase swim speed: SR, the percentage of time devoted to propulsion within a cycle, and the index of coordination (IdC) increased significantly. In contrast, the force impulse (I ⁺) generated by the hand during propulsion remained constant. Only the high-expertise group showed modification in the spectral content of its force distribution at high SR. Examination of stroking parameters showed that only high-expertise swimmers exhibited higher values of both SL and SI and that the low- and high-expertise groups exhibited similar IdC and even higher magnitude in I ⁺. In conclusion, all swimmers exhibit adaptable behavior to change swim pace when required. However, high-skilled swimming is characterized by broader functional adaptation in force parameters.

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.