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News and Comment: Conference Report

MAKING A SPLASH:  The VIII International Symposium of Biomechanics and Medicine in Swimming, Jyvaskyla, Finland

Andrew M Stewarta PhD and Hideki Kagakib PhD

aScottish Institute of Sports Medicine and Sports Science, University of Strathclyde, Glasgow, Scotland; bFaculty of Education, Mie University, Tsu, Japan. aCorresponding author: andy.stewart=AT=strath.ac.uk

Sportscience 2(4), sportsci.org/jour/9804/ams.html, 1998 (3284 words)

More than 160 delegates from around the globe gathered at the University of Jyvaskyla for the VIII International Symposium of Biomechanics and Medicine in Swimming from June 28-July 2, 1998.  Over 130 presentations in various formats (podium, poster, pool demonstration) were given at the symposium.  For those of you interested in obtaining more detailed information than what we present here, there is a book of abstracts available for purchase at the conference web site, and proceedings will be published early in 1999.  The next swim research conference is FINA's (Federation Internationale de Natation Amateur) in April, 1999 in Hong Kong, and the next International Symposium of Biomechanics and Medicine in Swimming is scheduled for St Etienne, France in 2002.

We've chosen a few presentations to highlight in this conference report; among them, keynote addresses by David Costill and Mitsumasa Miyashita.  First, Costill's presentation on training intensity and tapering.

Intensity and Tapering

The opening session of the conference was an invited lecture given by David Costill (Ball State University) entitled "Training adaptations for optimal performance in swimming".   Development of upper body strength is related highly to swim performance; and in looking at effects of training on muscular power and strength, Costill discussed the issue of quality vs quantity (or intensity vs volume).   He pointed out that training volume is not related to performance and showed evidence that in periods of high-volume training, muscle power was actually less than during periods of no training.  Thus the only way to recover that power in time for competition was for swimmers to taper.  Although there is debate surrounding the optimal taper period and how it should be constructed, Costill suggested that if athletes respond to training as expected, the taper should last approximately 14 to 21 days and consist of high-intensity sessions with a gradual reduction in volume.  For those athletes who show signs of overtraining, training volume should be reduced immediately in one large step, and then maintained at a low level until athletes start to show positive signs of adapting to the training stimulus.

Costill presented several theories that attempted to explain the mechanisms behind the effectiveness of tapering, but ruled out  psychological and motor unit recruitment theories for lack of convincing evidence.  Instead,  muscle fiber contractility appeared to be the more likely explanation behind tapering effectiveness.  Single muscle fiber studies that he and Scott Trappe performed at Ball State supported the view that tapering worked primarily through an increase in power (brought about by an increase in the muscle protein, myosin) in the fast twitch fibers.  They also found some increase in the power output of slow twitch fibers.

In addition, Costill  touched upon the debate surrounding the use of dry-land training for swim performance.  While such training is common practice in the swim world, Costill presented evidence that supported the view that there does not appear to be any further benefit to swim performance from dry-land training performed in addition to water-based workouts.

Historical Perspectives

Mitsumasa Miyashita (Toyo Eiwa Woman's University, Japan) has been involved in the scientific study of swimming for many years, and he has participated in this symposium since the first meeting in 1970.  Therefore, he was well-qualified to provide an historical perspective in his presentation entitled "Biomechanics of swimming: Past, present, and future".  During his talk, Miyashita discussed propulsive and resistive forces, factors in determining swimming velocity.  He pointed out that a swimmer's velocity varies during a single stroke cycle: it increases when the propulsive force exceeds the resistive force, and it decreases when the propulsive force falls below resistive force.

The measurement of propulsive and resistive forces has been a matter of concern to many researchers over the years, because accurate measurement of these forces would allow stroke technique to be evaluated quantitatively.  The history of biomechanical research in swimming has been one of trying to improve scientific methodology in order to measure propulsion and resistive force accurately.  In the early 1900s, resistive force was measured as passive drag and assessed while towing a swimmer behind a rowboat.  We now know that passive drag is somewhat different from active drag, which is the resistive force acting on a self-propelling swimmer.

Considerable developments have been made over the years in the techniques of biomechanical analysis.  Since 1970, three-dimensional cinematography has allowed propulsive forces in free swimming to be estimated.  In 1980, researchers in the Netherlands developed a system to measure active drag and the propelling efficiency of the front crawl stroke.  Miyashita pointed out that, even though such developments have taken place,  the relationship between propulsion, resistive force, and stroke technique is still not completely understood. (See the Sportscience article on swim biomechanics by Ross Sanders.)  Miyashita also suggested that the relationship between mean velocity and fluctuation of velocity during a single cycle stroke should be investigated, especially in breaststroke and butterfly.

Technique and Efficiency

Minoru Fujishima (Tokyo University, Japan) tried to clarify the effect of intracycle velocity fluctuation on average sustainable race velocity (a problem pointed out by Mitsumasa Miyashita).  By assuming that resistive drag is proportional to the square of the velocity, he showed that the smaller the fluctuation in velocity during a stroke cycle, the greater the average velocity.  He suggested that the reduction of resistive force would increase the velocity in strokes with a large resistive component (i.e. breaststroke and butterfly), and pulling equally with the left and right arm would reduce oscillations in velocity during freestyle and backstroke.  Swimmers should therefore concentrate on maintaining constant velocity within a stroke cycle by avoiding surges from a dominant limb (e.g. right arm) or a particular part of a stroke cycle (e.g. breaststroke kick).

Training-Load Model

Jean-Claude Chatard (St Etienne, France) presented a model of training loads, which consisted of a combination of intensity, volume, frequency, and dry-land training. Individual differences must be taken into account, and he agreed with David Costill's earlier presentation that intensity was the key to successful swim performance, not volume.  Much of the work that he presented was based upon the research of Mujika et al. (1995) Can. J. Appl. Physiol. 20: 395-406.  We questioned Jean-Claude about the theoretical basis of his new modeling approach, as it was based on Eric Bannister's original TRIMP (training impulse) model, which was developed on only two subjects.  His response was that his model held for the majority of the time, but it needed training data from at least 12 swimmers in order for it to work.  His model:

MITS = (1*km1 + 2*km2 + 3*km3 + 5*km4 + 8*km5 + dry-land equivalent)/(training volume)

where MITS is the mean intensity of training session, and 1*km1, 2*km2, etc. are the "stress indices" for each intensity times the km swum at that intensity. The stress index ranges from 1 (corresponding to a blood lactate concentration of 2 mmol/L) through 8 (maximum intensity sprint swimming). For dry-land training, sessions composed on average 50% warmup and stretching (intensity = 1), 25% submaximal strength workouts (intensity = 4), and 25% maximal strength training (intensity = 8). Coaches and swimmers estimated that 1 hr of dry-land training was equivalent to 1 km swum at intensity 1, 0.5 km at intensity 4, and 0.5 km at intensity 5.

Jean-Claude also noted that the better the performance at the start of the season, the better the performance at end-of-season competition.  In addition to advocating year-round high-intensity workouts, he suggested that medley swimming and weight training should be avoided during the taper period.

3-D Techniques

Jane Cappaert (International Center for Aquatic Research, USA) discussed the application of 3-D analysis to quantifying swim technique.  Such analysis has allowed her group to acquire a greater understanding of the underwater technique of all four swim strokes than conventional biomechanical analyses had previously allowed.  The knowledge gained from 3-D analysis formed the basis of all the biomechanical support given to the US swim team.  Jane explained that 3-D analysis of a swimmer's stroke was possible from the film footage of four cameras: two cameras in underwater housing and two cameras placed in the spectator stands. Separate direct linear transformations (DLT) were performed for the above-water and below-water views to determine the 3-D coordinates of body landmarks from the sets of 2-D coordinates digitized from each video frame of each camera.  Various body angles, displacements, and velocities of swimmers were then obtained to determine differences between swimmers of different abilities in each of the four strokes.  Jane indicated that, within each stroke, swimmers differed in their stroke patterns.  She pointed out that elite athletes did not always possess great strength and power, but the common trait among all elite swimmers was that they had the ability to apply power to the water more effectively than less-skilled swimmers.   In addition, elite swimmers would rather have better whole body streamlining that reduces resistive forces than use significantly higher propulsive force.  In short, reducing active drag is essential.

Altitude

Futoshi Ogita (National Institute of Fitness and Sports, Japan) reported positive effects from a train-high live-low study.  Nine well-trained swimmers were exposed to hypobaric conditions (simulated 3000 m above sea level) for two, two-hour sessions per day for five days per week for two weeks.  During each session the swimmers performed repeated bouts of 20-s exercise at 130% of maximal oxygen uptake, with 10-s rest intervals.   There was no change in maximal oxygen uptake following the intervention period, but anaerobic capacity (as assayed by maximal accumulated oxygen deficit) improved by 10%.

Drafting

Jean-Claude Chatard presented work that he and his colleagues had undertaken on the effects of drafting on swim performance and resistive drag in triathletes.  They found that drafting enhanced performance by an average of nearly 10 s in a 400-m race (more than a 3% improvement in performance).  Gains in performance were greater for faster swimmers.  In another drafting study, Gregoire Millet (University of Besancon, France) indicated that kicking frequency of the lead swimmer, that is 2-beat or 6-beat, had little effect on the advantage gained by a drafting swimmer.

Swim Tests

New underwater system and tests.  A group from Finland, lead by Kari Keskinen (University of Jyvaskyla) developed a new system of underwater pace-maker lights to control swim speed during tests.  The system was used to investigate the appropriateness of a new non-invasive test of performance utilizing a combination of stroke length, stroke rate, and swim velocity data.  The major finding: aerobic training intensities could be obtained from swimming velocity versus stroke length curves at the point where stroke length attained a maximum.

Non-invasive vs invasive testing.  Masaru Matsunami (Beppu Women's Junior College) led a group of Japanese scientists comparing swimming speed during non-invasive and invasive testing protocols.  The non-invasive tests were a 30-min swim test, 600-m swim test, 2000-m swim test, and critical speed test.  The invasive protocol consisted of lactate measurements taken during an incremental 7x200 m swim test.  The non-invasive test that elicited the most comparable swim speed to that of the so-called anaerobic threshold (as determined by lactate deflection point) was that of critical speed.

Don Maclaren (Liverpool John Moores University, UK) presented data on critical swim speed and how it could be used to track changes in training status.  He found that a two-distance (100-m and 200-m) model could be used to obtain critical swim speed rather than conventional three- or four-distance models.  He suggested that a 50-m swim could be used in a three-distance model, as long as the longest distance in the model was at least 200 m (although preferably at least 400 m).  He also found a significant increase in critical swim speed for sprinters following a period of aerobic training in tandem with a reduction in their anaerobic capability.  It seems, therefore, that aerobic training will benefit performance in the endurance-based events (200 m and greater), but not the sprint events (50 m and 100 m).

Training and Performance

Training practices survey.  Andy Stewart presented the results of a survey that he conducted with Will Hopkins on the training practices of most of the top swim coaches in New Zealand.  Twenty-four coaches and almost 200 age-group competitive swimmers completed the questionnaires, mailed out at the end of a summer and winter season. Periodization of training and differences in training between sprint and middle-distance were broadly in accord with principles of specificity.  Middle-distance swimmers were prescribed higher mileage and longer repetitions of lower intensity than sprinters. Repetition intensity and rest duration increased as competition approached. In the taper, repetition intensity increased while repetition volume and distance decreased. Average session volume for sprint and middle-distance swimmers reduced gradually from 5000 m at the beginning of the season to around 2000 m at the end of taper, while the average intensity of interval workouts rose steadily from around 83% of seasonal-best pace at the start of the season to approximately 90% by the time of competition.  These effects ranged in magnitude from small to very large.

Some training practices showed a lack of specificity.  For example, the proportion of easy swimming increased from 25% of volume in the build-up to 35% by the end of taper.  Easy and moderate swimming together accounted for slightly more than 50% of volume. Interval training decreased steadily from 40% of volume during the build-up to 30% by the end of the season.  And more than half of the volume was prescribed in the front crawl stroke for those swimmers who did not specialize in that stroke!

On the relationship between training and performance... well, there wasn't much!   Coaches preferred the long, slow, distance method over the race-specific approach.   But this was a descriptive study--good to find out what's going on, but not to find out what ought to be going on.  For that you need to do experiments.

Intervals, velocity, and rest.  Kohji Wakayoshi (Nara University of Education, Japan) led a group investigating various physiological responses to different combinations of swimming velocity and rest period during interval swimming.  The investigators used typical interval sets to determine whether there was a threshold of fatigue during interval swimming.  The test involved nine sets of 10x100 m at three velocities, with three rest durations.  From those intervals, it was shown that swimmers could perform the workouts without exhaustion at a pace equivalent to 105% of the mean swim velocity obtained during a maximal-effort 20-min test, with 20-s rests between intervals; they could also manage 110% of the mean swim velocity with 55-s rests.

A novel approach to the estimation of 200-m freestyle performance from 100-m freestyle bests was presented in poster form by Teruo Nomura (Kyoto Institute of Technology, Japan).  Performance data were collected from 232 national-class swimmers at the Japanese National Championships over a four-year period.  Stroke rates, stroke lengths, and various start, turn, and finishing split times within the 100-m and 200-m events were also recorded.  The multiple regression equations for estimating 200-m performances were:

Males:
200 m performance = 2*100 m record + 1.707*type + 9.890
Females:
200 m performance = 2*100 m record + 1.719*type + 8.872

where performance and records are in seconds, and type = 0, 1, or 2 for swimmers specializing in both 100-m and 200-m freestyle events, or only the 100-m, or only the 200-m respectively.  The 95% confidence intervals for estimated performances were 1.6 s for male and 1.4 s for females.  The authors speculated that swimmers whose 200-m performance is beyond the upper confidence limit of the predicted time should concentrate on the shorter events and/or increase the endurance component of their training program.  On the other hand, those swimmers whose 200-m performance is below the lower confidence limit of the predicted time should concentrate on longer events and/or increase the sprint component of the training program.

High intensity prevails.  Albert Termin (University of Buffalo, USA) provided further evidence of high-intensity training favoring better performance outcomes than traditional high-mileage programs.  In his study, 22 male university swimmers were followed for a four-year period, during which they performed various high-intensity workouts.  He compared performance to a group of swimmers who followed the traditional mileage program.  Favorable changes in stroke rate and stroke length were noted in the experimental group, but the most important change was that the experimental group improved their performance three to four times (~9% as opposed to ~2 to 3%) that of those swimmers following traditional training methods.

Estimating Hydrodynamic Forces

Hideki Takagi introduced a new method to evaluate hydrodynamic forces acting on the hand during swimming.  Most often the 3-D cinematographic analysis technique (Scheihauf, 1979) has been used for estimating forces on the hand, but this method involves the lengthy process of digitizing.  Hideki developed a new pressure-difference method that estimated the hydrodynamic force by using the pressure difference between the palm and the back of the hand.   The hydrodynamic force was obtained by multiplying the entire mean pressure difference by hand plane area.  A key characteristic of the new method is that it's possible to measure the hydrodynamic force more correctly than traditional techniques by using a total of eight waterproof micro pressure sensors.  Moreover, the new method has the advantage of immediate visual diagnostics and continuous monitoring. It may become a useful way to improve stroke effectiveness.

Reducing Drag During Glides

Does a swimmer's depth in the water make a difference in glide speed?  Andrew Lyttle (University of Western Australia, Australia) performed trials with 31 experienced male swimmers towed in a prone position through the water using a pulley system to determine the optimal depth for the glide and push-off phase.   Drag force acting on each swimmer was measured in trials performed at four depths (surface, 0.2, 0.4, and 0.6 m).  The drag at the surface was significantly higher than at depth for all towing velocities (range from 1.6 m/s to 3.1 m/s).  For velocities of 2.2 to 3.1 m/s, the drag at 0.2 m underwater was significantly higher than the drag recorded at 0.4 and 0.6 m, but no significant difference was found between 0.4 and 0.6 m underwater.  Conclusion: it may be beneficial for swimmers to perform their glides at a depth of approximately 0.4 m to gain maximum benefit from reduction of resistance.

Flume Swimming

Are swimming flumes as effective as pools for swimming research?  Scientists have conducted experiments in swimming flumes assuming that there is no hydrodynamic difference between pool and flume.  Barry Wilson (University of Otago, New Zealand) compared stroke rates in front crawl for flume swimming and free swimming.  Fourteen experienced swimmers swam at five different speeds in the pool and flume on each of two separate days.  The mean stroke rate was determined at each swimming speed for each condition.  A repeated measures within-subjects design was used to compare stroke rates in the two environments at the same swimming speed.  The findings:  no meaningful difference in stroke rate for flume or free swimming.  However,  it is essential to have adequate familiarization sessions in the flume prior to any experiment if you are to have confidence in your flume data.