Physiological correlates of simulated sprint-distance triathlon

The purpose of this study was to examine the relationship between simulated triathlon performance and physiological variables measured during conventional laboratory tests. Seven non-elite, competitive male triathletes completed incremental cycling and running tests in a random order, in addition to a simulated sprint-distance triathlon trial (750 m swim, 500 kJ bike, 5 km run) using a 25 m pool, an electromagnetically braked cycle ergometer and motorised treadmill. There were no significant correlations between overall performance time and either running or cycling incremental tests, however significant correlations were found between triathlon run time and both running and cycling incremental tests (Vpeak, r = -.900, p<0.05; V4mmol, r = -.822, p<0.05; Wpeak, r = -.844, p<0.05). Total simulated triathlon time was highly correlated to cycle time (r = .930, p<0.05) and mean cycling power output (r = -.956, p<0.05), whilst there was no significant correlation between either swim time or run time and overall performance time. For non-elite, competitive male triathletes, a performance assessment which better reflects the demands of the cycle phase of triathlon (i.e. a time-trial protocol) may provide a better indication of simulated sprint-distance triathlon performance in comparison to commonly used incremental laboratory tests. Furthermore, cycling performance appears more important to overall performance in simulated sprint-distance triathlon than swimming or running

Reliability of simulated sprint-distance triathlon

To assess reliability of simulated sprint-distance triathlon seven non-elite, male triathletes completed three trials (750 m swim, 20 km bike, 5 km run), using a 25 m pool, an electromagnetically braked cycle ergometer and motorised treadmill. Total times (h, min and s) were 1:17:37 ± 0:06:41, 1:18:22 ± 0:08:59 and 1:18:47 ± 0:09:56. Coefficient of variation (CV) for total performance time was 2.7% between trials 1&2 (CI = 1.7-6.0) and 2.3% between trials 2&3 (CI = 1.5-5.1). Performance CV’s for swim, cycle and run phases were also <5% between trials 2&3. These results show that for non-elite, competitive male triathletes, performance time in simulated sprint-distance triathlon is highly reproducible, with a CV comparable to endurance performances of similar duration (<5%)

Associations between cardiorespiratory responses, perceived exertion and affect during isolated and triathlon-specific cycling time-trials

Introduction Compared to other cardiorespiratory parameters, respiratory frequency (fR) is suggested as one of the most important contributors to self-paced endurance performance. This is based on the strong relationship fR shares with RPE, irrespective of event duration (Nicolò et al., 2016). However, it is yet to be established if fR and RPE interaction differs during multi-modal events (i.e. triathlon). Indeed, the complexity of such exercise may well alter the relationships that are typically seen between perceptual and physiological status during single-mode events (Taylor & Smith, 2013). Furthermore, it is suggested that affective status may be more important than RPE to the pacing of endurance performance. This study therefore examined the associations between cardiorespiratory responses, RPE and affect during isolated and triathlon-specific cycling performance. Methods Eleven non-elite male triathletes (mean ± SD: age 36.9 ± 8.4 yrs, VO2max 4.1 ± 0.3 L·min-1, Wmax 344 ± 21 W) completed two laboratory-based trials 9 ± 4 days apart, each incorporating a 500 kJ (~20 km) cycling time-trial (CTT) performed on an SRM ergometer. The first CTT was completed in isolation, whilst the second CTT formed part of a simulated sprint-distance triathlon (0.75 km flume swim, 500 kJ bike, 5 km treadmill run). Cardiorespiratory (fR, VE, VO2, VT, HR) and perceptual (RPE and affect) responses were obtained every 100 kJ. Relationships between these measures were examined by calculation of within-subject correlation coefficients. Results During isolated CTT’s, RPE was significantly related (P < 0.05) with fR (r = 0.80), VE (r = 0.58), VO2 (r = 0.57), VT (r = 0.49) and HR (r = 0.79), whilst affect was significantly related (P < 0.05) with fR (r = 0.70), VE (r = 0.37), VT (r = 0.63) and HR (r = 0.67) but not VO2 (r = 0.26). During triathlon-specific CTT’s, RPE was significantly related (P < 0.05) with fR (r = 0.51), VO2 (r = 0.30), VT (r = 0.43) and HR (r = 0.51) but not VE (r = 0.03), whilst affect was significantly related (P < 0.05) with fR (r = 0.47), VT (r = 0.60) and HR (r = 0.43) but not VO2 (r = 0.09) or VE (r = 0.08). Discussion In accordance with Nicolò et al. (2016) fR demonstrated the strongest relationship with RPE across both CTT’s, relative to other cardiorespiratory measures. This trend was also apparent for the relationships between cardiorespiratory responses and affect, though the strength of these was generally lower compared to those seen with RPE. Associations between perceptual and cardiorespiratory responses were also consistently weaker during triathlon-specific CTT. These findings support the view that fR and RPE interaction may be one of the most important contributors to pacing during single and multi-modal events, whilst also illustrating unique relationships between perceptual and physiological responses during triathlon cycling

What if there's more to performance than just cycling? Examining the perceptual basis of pacing during sprint-distance triathlon.

Whilst pacing is frequently highlighted as a key aspect of successful athletic performance, there has been little consideration of how theories of pace regulation relate specifically to multi-modal endurance events. This presentation therefore aims to summarise a series of studies which have collectively examined performance, pacing, physiology and perception during sprint-distance triathlon, to try to better understand how athletes prioritise and distribute their effort across successive modes of exercise in the pursuit of optimum overall performance. Of these studies, particular attention will be paid to that which has examined the effects of deceptively aggressive bike pacing on performance and psychophysiological status during simulated sprint-distance triathlon. In doing so, evidence will be presented which i) illustrates the potential for expectations and beliefs to have a practically meaningful effect on pacing and performance during multi-modal athletic performance, and ii) suggests that particular psychophysiological and emotional constructs (e.g. RPE and affect) may be less closely tied with pace optimisation than has been inferred previously. As such, the work presented will question whether existing ‘mainstream’ pacing theories can adequately explain the complex anticipatory processes which underpin performance during multi-modal (i.e. triathlon) or multi-stage (i.e. Tour de France) sporting events, and will hopefully serve to stimulate further discussion regarding the future exploration of this topic

Effects of residual fatigue on pace regulation during sprint-distance triathlon running

Introduction: It has been suggested that unique relationships exist between perceived exertion, pacing and physiological responses during triathlon. However, research to date has not clearly established how the interaction of these factors is affected by residual physiological fatigue, particularly during running performance over distances relevant to sprint-distance triathlon. This study therefore investigated the effects of the preceding swim and cycle on pacing strategy, perceived exertion, and physiological status during sprint-distance triathlon running. Methods: Eight amateur male triathletes (mean ± SD: age 36.0 ± 5.7 yrs, mass 75.7 ± 5.3 kg) completed two field-based performance trials. The first was a sprint-distance triathlon (0.75 km swim, 20 km cycle, 5 km run) and the second an isolated 5 km run time-trial, each separated by 7-18 days and utilising the same flat out-and-back road course. Wrist-mounted GPS devices (Garmin 310XT, UK) recorded performance time, running speed (km•h-1) and heart rate during each trial. Participants recorded ratings of perceived exertion (Borg 6-20 scale) every kilometre using a wrist-mounted recording sheet and pen. Core temperature (CorTemp, HQInc, USA), blood lactate concentration (Lactate Pro, Kodak, Japan) and body mass (to 0.1 kg; Seca 875) were also measured immediately prior to, and after, each run. Results: Performance time for isolated running (19:28 ± 00:32) was ~7% quicker than triathlon running (20:48 ± 00:43) (p<0.01), with a similar positive pacing strategy displayed throughout both trials (figure 1). Initial core temperature, blood lactate concentration and heart rate values were all significantly higher for the triathlon run compared to the isolated run (p<0.01), with no differences in final values for these measures. No significant differences were observed for initial RPE, rate of RPE increase, or final RPE between runs. Discussion/Conclusion: Prior swimming and cycling impair performance but do not affect pacing strategy during sprint-distance triathlon running. Reduced performance may be attributed to the residual physiological strain observed at the start of the triathlon run. However, the maintenance of scalar-linear increases in RPE appears to be the primary regulator of pacing strategy during triathlon running, with physiological responses only indirectly related to this process

The influence of mid-event deception on psychophysiological status and pacing can persist across consecutive disciplines and enhance self-paced multi-modal endurance performance

Purpose: To examine the effects of deceptively aggressive bike pacing on performance, pacing, and associated physiological and perceptual responses during simulated sprint-distance triathlon. Methods: Ten non-elite, competitive male triathletes completed three simulated sprint-distance triathlons (0.75 km swim, 500 kJ bike, 5 km run), the first of which established personal best ‘baseline’ performance (BL). During the remaining two trials athletes maintained a cycling power output 5% greater than BL, before completing the run as quickly as possible. However, participants were informed of this aggressive cycling strategy before and during only one of the two trials (HON). Prior to the alternate trial (DEC), participants were misinformed that cycling power output would equal that of BL, with on-screen feedback manipulated to reinforce this deception. Results: Compared to BL, a significantly faster run performance was observed following DEC cycling (p < .05) but not following HON cycling (1348 ± 140 vs. 1333 ± 129 s and 1350 ± 135 s, for BL, DEC and HON, respectively). As such, magnitude-based inferences suggest HON running was more likely to be slower, than faster, compared to BL, and that DEC running was probably faster than both BL and HON. Despite a trend for overall triathlon performance to be quicker during DEC (4339 ± 395 s) compared to HON (4356 ± 384 s), the only significant and almost certainly meaningful differences were between each of these trials and BL (4465 ± 420 s; p < .05). Generally, physiological and perceptual strain increased with higher cycling intensities, with little, if any, substantial difference in physiological and perceptual response during each triathlon run. Conclusions: The present study is the first to show that mid-event pace deception can have a practically meaningful effect on multi-modal endurance performance, though the relative importance of different psychophysiological and emotional responses remains unclear. Whilst our findings support the view that some form of anticipatory ‘template’ may be used by athletes to interpret levels of psychophysiological and emotional strain, and regulate exercise intensity accordingly, they would also suggest that individual constructs such as RPE and affect may be more loosely tied with pacing than previously suggested

The Effect of Real-Time Constraints on Automatic Speech Animation

Machine learning has previously been applied successfully to speech-driven facial animation. To account for carry-over and anticipatory coarticulation a common approach is to predict the facial pose using a symmetric window of acoustic speech that includes both past and future context. Using future context limits this approach for animating the faces of characters in real-time and networked applications, such as online gaming. An acceptable latency for conversational speech is 200ms and typically network transmission times will consume a significant part of this. Consequently, we consider asymmetric windows by investigating the extent to which decreasing the future context effects the quality of predicted animation using both deep neural networks (DNNs) and bi-directional LSTM recurrent neural networks (BiLSTMs). Specifically we investigate future contexts from 170ms (fully-symmetric) to 0ms (fullyasymmetric