This thesis examined the benefits of physiological and performance testing of elite swimmers.
The study considered the following research questions: the degree to which physiological and
performance measures in training contribute to swimming performance; sources and
magnitude of variability in testing, training and competition performance; the magnitudes of
changes in test measures during routine training; and the reliability, validity and utility of
miniaturised and automated smart sensor technology to monitor the stroke and performance
times of swimmers in training. The experimental approach involved the retrospective
analysis of five years of physiological and performance testing of elite level swimmers, the
development of a new accelerometry-based smart sensor device to monitor swimmers in the
pool, a cross-sectional study comparing the physiological and performance responses of
swimmers of different levels, and the effects of an intensive 14-day training program on
submaximal physiological and performance measures. Collectively, the outcomes of these
studies provide a strong justification for the physiological and performance testing of elite
swimmers, a quantitative framework for interpreting the magnitude of changes and
differences in test scores and sources of variation, and highlight the potential utility of new
smart sensor technology to automate the monitoring of a swimmer�s training performance.
The first study (Chapter 2) characterises the changes and variability in test performance,
physiological and anthropometric measures, and stroke mechanics of swimmers within and
between seasons over their elite competitive career. Forty elite swimmers (24 male, 16
female) performed a 7 x 200-m incremental swimming step test several times each 6-month
season (10 � 5 tests, spanning 0.5 to 6.0 y). Mixed linear modeling provided estimates of
change in the mean and individual responses for measures based on submaximal performance
(fixed 4-mM lactate), maximal performance (the seventh step), and lean mass (from skinfolds
and body mass). Submaximal and maximal swim speed increased within each season from
the pre to taper phase by ~2.2% for females and ~1.5% for males (95% confidence limits
�1.0%), with variable contributions from stroke rate and stroke length. Most of the gains in
speed were lost in the off-season, leaving a net average annual improvement of ~1.0% for
females and ~0.6% for males (�1.0%). For submaximal and maximal speed, individual
variation between phases was �2.2% and the typical measurement error was �0.8%. In
conclusion, step test and anthropometric measures can be used to confidently monitor
progressions in swimmers in an elite training program within and between seasons.
The second study (Chapter 3) quantified the relationship between changes in test measures
and changes in competition performance for individual elite swimmers. The primary question
addressed was whether test measures could predict a swimmers performance at the major end-of-season competition. The same sample group as in Study 1 was examined. A 7 x 200-m
incremental swimming step-test and anthropometry were conducted in up to four training
phases each season. Correlations of changes in step-test and anthropometric measures
between training phases between and within seasons, with changes in competition
performance between seasons, were derived by repeated-measures mixed modeling and linear
regression. Changes in competition performance were best tracked by changes in test
measures between taper phases. The best single predictor of competition performance was
skinfolds for females (r = -0.53). The best predictor from the step-test was stroke rate at 4-mM lactate (females, r = 0.46; males, r = 0.41); inclusion of the second-best step-test
predictor in a multiple linear regression improved the correlations marginally (females, r =0.52 with speed in the seventh step included; males, r = 0.58 with peak lactate concentration
included). Changes in test measures involving phases other than the taper provided weak and
inconclusive correlations with changes in performance, possibly because the coaches and
swimmers took corrective action when tests produced poor results. In conclusion, a
combination of fitness and techniques factors are important for competitive performance. The
step test is apparently a useful adjunct in a swimmer�s training preparation for tracking large
changes in performance.
These initial studies identified stroke mechanics as a major determinant of a swimmer�s
performance. Chapter 4 details the development of a small tri-axial accelerometry-based
smart sensor device (the Traqua) that enables continual monitoring of various
performance/stroke characteristics in swimming. The initial focus was to develop a device
that automated the detection of a swimmer�s movements, specifically lap times, stroke rate
and stroke count. The Traqua consists of a tri-axial accelerometer packaged with a
microprocessor, which attaches to the swimmer at the pelvis to monitor their whole body
movements while swimming. This study established the failure/error rate in the first
generation algorithms developed to detect the swimming-specific movements of stroke
identification, laps (start, turn and finish), and strokes (stroke count and stroke rate) in a
cohort of 21 elite and sub-elite swimmers. Movements were analysed across a range of
swimming speeds for both freestyle and breaststroke. These initial algorithms were
reasonably successful in correctly identifying the markers representing specific segments of a
swimming lap in a range of swimmers across a spectrum of swimming speeds. The first
iteration of the freestyle algorithm produced error-rates of 13% in detection of lap times, 5%
for stroke rate, and 11% for stroke count. Subsequent improvements of the software reduced
the error rate in lap and stroke detection. This improved software was used in the following
two studies.
The next study (Chapter 5) evaluated the reliability and validity of the Traqua against
contemporary methods used for timing, stroke rate and stroke count determination. The
subjects were 14 elite and 10 sub-elite club-level swimmers. Each swimmer was required to
swim seven evenly paced 200-m efforts on a 5-min cycle, graded from easy to maximal.
Swimmers completed the test using their main competitive stroke (21 freestyle, 3
breaststroke). Timing was compared for each 50-m lap and total 200-m time by electronic
touch pads, video coding, a hand-held manual stopwatch, and the Traqua. Stroke count was
compared for video coding, self-reported counting, and the Traqua, while the stroke rate was compared via video coding, hand-held stopwatch, and the Traqua. Retest trials were
conducted under the same conditions 7 d following the first test. All data from the Traqua presented in this and the subsequent studies were visually inspected for errors in the
automated algorithms, where the algorithms had either failed to correctly identify the start,
turn, finish or individual strokes and corrected prior to analysis. The standard error of the
estimate for each of the timing methods for total 200 m was compared with the criterion
electronic timing. These standard errors were as follows: Traqua (0.64 s; 90% confidence
limits 0.60 � 0.69 s), Video (0.52 s; 0.49 � 0.55 s); Manual (0.63 s; 0.59 � 0.67 s). Broken
down by 50-m laps, the standard error of the estimate for the Traqua compared with the
electronic timing for freestyle only was: 1st 50-m 0.35 s; 2nd and 3rd 50-m 0.13 s; 4th 50-m
0.65 s. When compared with the criterion video-coding determination, the error for the stroke
count was substantially lower for the Traqua (0.6 strokes.50 m-1; 0.5 � 0.6 strokes.50 m-1)
compared to the self-reported measure (2.3 strokes.50 m-1; 2.5 � 2.9 strokes.50 m-1).
However, the error for stroke rate was similar between the Traqua (1.5 strokes.min-1; 1.4 � 1.6
strokes.min-1) and the manual stopwatch (1.8 strokes.min-1; 1.7 � 1.9 strokes.min-1). The
typical error of measurement of the Traqua was 1.99 s for 200-m time, 1.1 strokes.min-1 for
stroke rate, and 1.1 strokes.50 m-1 for stroke count. In conclusion, the Traqua is comparable
in accuracy to current methods for determining time and stroke rate, and better than current
methods for stroke count. A substantial source of error in the Traqua timing was additional
noise in the detection of the start and finish. The Traqua is probably useful for monitoring of
routine training but electronic timing and video are preferred for racing and time trials.
Having established the reliability and validity of the Traqua, Chapter 6 addressed the ability
to discriminate the pattern of pacing between different levels of swimmers in the 7 x 200-m
incremental step test. This study also sought to quantify the differences in pacing between
senior and junior swimmers. Eleven senior elite swimmers (5 female, 6 male) and 10
competitive junior swimmers (3 female, 7 male) participated in this study. Each swimmer
was required to swim seven evenly paced 200-m freestyle efforts on a 5-min cycle, graded
from easy to maximal. The Traqua was used to measure time, stroke rate and stroke count.
The senior swimmers were better able to descend in each of the 200-m efforts. Overall the
senior swimmers were ~2-3 s per 50 m faster than the junior swimmers. Both groups were
fastest in the first 50-m lap with the push start. The senior swimmers then descended the 50-
m time for each of the subsequent laps, getting ~0.5 s faster per lap, with the final lap the
fastest. In contrast, the junior swimmers swam a similar time for each of the subsequent laps.
The junior swimmers were marginally more variable in their times (coefficient of variation:
~2%) compared with the senior swimmers (~1.8%). In comparison to junior swimmers, the
senior swimmers in this study were faster, adopted a more uniform negative split strategy to
pacing within a 200-m effort, and were more consistent in reproducing submaximal and
maximal swimming speeds.
The final study (Chapter 7) analysed the effect of 14-d of intensive training on the
reproducibility of submaximal swimming performance in elite swimmers. Submaximal
physiological and performance testing is widely used in swimming and other individual sports
but the variability in test measures, and the effects of fatigue, during intensive training have
surprisingly not been quantified systematically. Seven elite swimmers (3 male and 4 female)
participated in an intensive 14-d training camp one month prior to the National
championships. The aim of the study was to characterise the intra-session, daily and training
block variability of submaximal swimming time, physiological and stroke characteristics in
elite swimmers. The swimmers performed a specified submaximal 200-m effort in most
sessions, after the warm-up and at the end of the session for both morning and afternoon
sessions. During the efforts, swimming time and stroke mechanics were measured and
physiological measures were recorded immediately on completion. The Traqua was worn by
all swimmers in every training session. Mixed linear modeling was used to provide estimates
of changes in the mean and individual responses (within-athlete variation as a coefficient of
variation) for all measures. The swimmers were moderately slower (1.4%; �1.4%) over the
14-d training camp. The mean submaximal 200-m effort was very likely to be faster (0.7%;
confidence limits �0.7%) in the afternoon compared with the morning session. The females
were more variable in their submaximal performance times (CV=2.6%) than the male
swimmers (1.7%). Blood lactate concentration was almost certainly lower (-23%; �10%)
following higher volume in the previous session; however a higher intensity workout the
previous session almost certainly leads to higher lactate (21%; �15%) in the current session.
Considered together, these results indicate that the 200-m submaximal test is useful in
monitoring submaximal physiological and performance measures and the negative effects of
cumulative fatigue.
In conclusion, changes in the physiological and performance measures derived from the poolbased
progressive incremental step test are moderately correlated with changes in end-ofviii.
season competition performance. The magnitudes of changes and differences in test measures
between phases within a season, from season to season, and between males and females,
established in this study can be applied to similar elite level swimmers preparing for major
competition. The quantification of typical error of the same measures demonstrates that
coaches and scientists can distinguish real and worthwhile improvements using the 7 x 200-m
step test. Continual pool-based monitoring with the automated smart sensor Traqua device
may provide more accurate and detailed information about a swimmer�s training adaptation
than current fitness tests and monitoring methods. Finally, submaximal testing in trained
swimmers is useful in monitoring progress in physiological and performance measures, and
the impact of cumulative fatigue during an intensive period of training. Collectively, the
outcomes of these studies indicate that routine physiological and performance testing can
provide measurable benefits for elite swimmers and their coaches.
| Identifer | oai:union.ndltd.org:ADTP/219568 |
| Date | January 2006 |
| Creators | Anderson, Megan, n/a |
| Publisher | University of Canberra. Health Sciences |
| Source Sets | Australiasian Digital Theses Program |
| Language | English |
| Detected Language | English |
| Rights | ), Copyright Megan Anderson |
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