New Study: Effects of consecutive domestic and international tournaments on HRV in an elite rugby sevens team

A quick summary of our latest paper follows the abstract below…

Effects of consecutive domestic and international tournaments on
heart rate variability in an elite rugby sevens team

JSAMS title HRV rugby

Rugby seven players often compete in 2-day tournaments over consecutive weekends, leaving only 5 days to recover and prepare for the next tournament. Many tournaments are held internationally, adding substantial travel demands to the already-taxing nature of the sport. We hypothesized that the added stress of travel for an international tournament may result in greater decrements in HRV relative to a local tournament.

The main findings were that despite no significant difference in match-physical demands (high speed running, total distance and sRPE), significant reductions in LnRMSSD were observed only in response to the international tournament (see figure below). Despite non-significant p values at other time-points, individual analysis showed that ~80% of the players showed meaningful reductions in LnRMSSD relative to baseline following the local tournament and on the day of travel (see bottom of figure). Thus, it seems that HRV was still affected by these events, though to a lesser magnitude than the international tournament.

The decrements in LnRMSSD at the international tournament were preceded by significant decrements in perceived sleep quality and energy levels reported on or after a chaotic travel day. The travel day involved an earlier than usual wake-time and a missed flight connection. This forced the team to complete the travel by bus, delaying their hotel arrival to 3 am.

Given that HRV is sensitive to a variety of physiological, psychological and environmental factors, we cannot say for certain that travel stress accounted for the differences in HRV responses, though it seems likely. We state: “LnRMSSD responses to the international tournament were therefore likely influenced by a combination of variables associated with, but not limited to altered sleep, a disrupted travel itinerary and the process of relocation which interacted with the physical and psychological stress associated with tournament-play.”

Differences in collision/body contact loads between tournaments may have contributed to differences in LnRMSSD responses, but were not assessed. Additionally, this was the first pair of consecutive tournaments for this team in at least six weeks, which may have served as a relatively novel stimulus. Therefore, we’re not sure if similar LnRMSSD responses would be observed when the team was re-familiarized with consecutive tournaments or when travel isn’t so hectic.

JSAMS Fig 1 HRV rugby 7 consecutive tournaments Flatt et al.

Advertisements
Posted in Heart Rate Variability | Tagged , , , , | Leave a comment

New study: Association between Subjective Indicators of Recovery Status and Heart Rate Variability among Divison-1 Sprint-Swimmers

Our latest study investigates the relationship between subjective indicators of recovery status and HRV among NCAA Division 1 sprint-swimmers. The main findings were:

1) Perceived sleep quality showed the strongest relationship with post-waking LnRMSSD.

2) LnRMSSD demonstrated stronger associations with subjective parameters than resting heart rate.

We report both group and individual relationships. The full text is available here.

Association between Subjective Indicators of Recovery Status and Heart Rate Variability among Divison-1 Sprint-Swimmers

Abstract

Heart rate variability (HRV) is a physiological marker of training adaptation among athletes. However, HRV interpretation is challenging when assessed in isolation due to its sensitivity to various training and non-training-related factors. The purpose of this study was to determine the association between athlete-self report measures of recovery (ASRM) and HRV throughout a preparatory training period. Ultra-short natural logarithm of the root mean square of successive differences (LnRMSSD) and subjective ratings of sleep quality, fatigue, muscle soreness, stress and mood were acquired daily for 4 weeks among Division-1 sprint-swimmers (n = 17 males). ASRM were converted to z-scores and classified as average (z-score −0.5–0.5), better than average (z-score > 0.5) or worse than average (z-score < −0.5). Linear mixed models were used to evaluate differences in LnRMSSD based on ASRM classifications. LnRMSSD was higher (p < 0.05) when perceived sleep quality, fatigue, stress and mood were better than average versus worse than average. Within-subject correlations revealed that 15 of 17 subjects demonstrated at least one relationship (p < 0.05) between LnRMSSD and ASRM variables. Changes in HRV may be the result of non-training related factors and thus practitioners are encouraged to include subjective measures to facilitate targeted interventions to support training adaptations.

Figure 1 Effect Size SPORTS jpeg

Figure 1

Effect sizes ± 90% confidence interval for resting heart rate parameters relative to subjective categorization.

Posted in Heart Rate Variability | Tagged , , , , , , , | Leave a comment

Effects of varying training load on HRV and running performance among an Olympic rugby sevens team

This study is the first of a few collaborations between Dan Howells and I involving HRV in elite rugby sevens players. Here we evaluated HRV and running performance responses  to peak training loads during preparation for the 2016 Olympic games. A practical summary follows the abstract below.

Effects of varying training load on HRV and running performance among an Olympic rugby sevens team

JSAMS Abstract Flatt Howells HRV rugby sevens

How do elite seven’s players respond to substantial increments in training load? Based on previous studies, we’d expect the weekly LnRMSSD mean (LnRMSSDm) to decrease and the coefficient of variation (LnRMSSDcv) to increase relative to baseline. We’ve observed this in collegiate soccer players and sprint-swimmers.

In contrast to this hypothesis, the players showed no change in LnRMSSDmean throughout two weeks of intensified training relative to a baseline week of low loads. LnRMSSDcv demonstrated a small increase during the first week of increased load (expected response) but then showed a moderate decrease during the second week of increased load, which involved greater loads than the previous week (unexpected response).

No change (or an increase) in LnRMSSDm and a reduction in LnRMSSDcv is typically observed when training loads are reduced. Less training stress results in less fluctuations in LnRMSSD. However, these players demonstrated less fluctuation in LnRMSSD despite significant increments in training load.

The discrepancy here appears to be related to how players are tolerating and adapting to the training load. We often assume that increased loads will result in fatigue accumulation and temporary negative responses. However, these elite players demonstrated no reductions in subjective indicators of recovery status during the weeks of increased load. Additionally, there was no significant decrement in running performance (maximum aerobic speed) mid-way through the intensified microcycles.

Thus, the preservation of autonomic activity (no change in LnRMSSDm) and less fluctuations (reduced LnRMSSDcv) seem to reflect a postive coping response to the training. In fact, individuals who demonstrated the lowest LnRMSSDcv during week 1 of increased load showed the most favorable changes in running performance (r = -0.74).

This is yet another study that demonstrates that reduced fluctuations in LnRMSSD (i.e., decrease in LnRMSSDcv) is associated with positive training responses in athletes.

The Practical Implications of the study were:

•When evaluated as a group, LnRMSSDcv may be a more sensitive training response marker than LnRMSSDm during training load variations among elite players.

•LnRMSSDcv did not display a linear dose–response relationship with training load. Rather, LnRMSSDcv seems to reflect an adaptive physiological response to the imposed training stimulus which may be useful for identifying individuals responding undesirably to training.

•Elite rugby players presenting large day-to-day fluctuations in LnRMSSD in response to training load variation should be monitored closely for performance decrements, particularly when nearing important competitions.

 

 

 

 

Posted in Heart Rate Variability, Monitoring | Tagged , , , , , | 2 Comments

HRV-guided vs. pre-planned training at altitude in an elite wheelchair marathoner

This new paper is in collaboration with Santi Sanz-Quinto and colleagues from his dissertation work. The case study compares HRV-guided vs. pre-planned training at altitude in an elite wheelchair marathoner with CMT.

Influence of Training Models at 3,900-m Altitude on the Physiological Response and Performance of a Professional Wheelchair Athlete: A Case Study.

Abstract

This case study compared the effects of two training camps using flexible planning (FP) vs. inflexible planning (IP) at 3,860-m altitude on physiological and performance responses of an elite marathon wheelchair athlete with Charcot-Marie-Tooth disease (CMT). During IP, the athlete completed preplanned training sessions. During FP, training was adjusted based on vagally mediated heart rate variability (HRV) with specific sessions being performed when a reference HRV value was attained. The camp phases were baseline in normoxia (BN), baseline in hypoxia (BH), specific training weeks 1-4 (W1, W2, W3, W4), and Post-camp (Post). Outcome measures included the root mean square of successive R-R interval differences (rMSSD), resting heart rate (HRrest), oxygen saturation (SO2), diastolic blood pressure and systolic blood pressure, power output and a 3,000-m test. A greater impairment of normalized rMSSD (BN) was shown in IP during BH (57.30 ± 2.38% vs. 72.94 ± 11.59%, p = 0.004), W2 (63.99 ± 10.32% vs. 81.65 ± 8.87%, p = 0.005), and W4 (46.11 ± 8.61% vs. 59.35 ± 6.81%, p = 0.008). At Post, only in FP was rMSSD restored (104.47 ± 35.80%). Relative changes were shown in power output (+3 W in IP vs. +6 W in FP) and 3,000-m test (-7s in IP vs. -16s in FP). This case study demonstrated that FP resulted in less suppression and faster restoration of rMSSD and more positive changes in performance than IP in an elite wheelchair marathoner with CMT

Posted in Heart Rate Variability, Monitoring | Tagged , , , , , | Leave a comment

Modelling the HRV Response to Training Loads in Elite Rugby Sevens Players

New paper in collaboration with my colleagues Sean Williams, Dan Howells et al. Full-text link below.

Modelling the HRV Response to Training Loads in Elite Rugby Sevens Players

Key Points

  • A systems theory approach can be used to describe the variation in chronic HRV responses to training within elite Rugby Sevens players.
  • For the majority of athletes, model parameters can be used to accurately predict future responses to training stimuli.
  • Responses that diverge from the predicted values may serve as a useful flag for the investigation of changes in lifestyle factors.
  • Internal training load measures (sRPE) markedly outperformed external load measures (HSD) in predicting future HRV responses to training stimuli.

Abstract

A systems modelling approach can be used to describe and optimise responses to training stimuli within individuals. However, the requirement for regular maximal performance testing has precluded the widespread implementation of such modelling approaches in team-sport settings. Heart rate variability (HRV) can be used to measure an athlete’s adaptation to training load, without disrupting the training process. As such, the aim of the current study was to assess whether chronic HRV responses, as a representative marker of training adaptation, could be predicted from the training loads undertaken by elite Rugby Sevens players. Eight international male players were followed prospectively throughout an eight-week pre-season period, with HRV and training loads (session-RPE [sRPE] and high-speed distance [HSD]) recorded daily. The Banister model was used to estimate vagallymediated chronic HRV responses to training loads over the first four weeks (tuning dataset); these estimates were then used to predict chronic HRV responses in the subsequent four-week period (validation dataset). Across the tuning dataset, high correlations were observed between modelled and recorded HRV for both sRPE (r = 0.66 ± 0.32) and HSD measures (r = 0.69 ± 0.12). Across the sRPE validation dataset, seven of the eight athletes met the criterion for validity (typical error <3% and Pearson r >0.30), compared to one athlete in the HSD validation dataset. The sRPE validation data produced likely lower mean bias values, and most likely higher Pearson correlations, compared to the HSD validation dataset. These data suggest that a systems theory approach can be used to accurately model chronic HRV responses to internal training loads within elite Rugby Sevens players, which may be useful for optimising the training process on an individual basis.

Posted in Heart Rate Variability | Tagged , , , , , , | Leave a comment

Podcast Interview: HRV in football and rugby

I recently had the pleasure of discussing HRV in football and rugby on the Rugby Renegade Podcast. Soundcloud and iTunes links below.

 

iTunes link: https://itunes.apple.com/zw/podcast/rugby-renegade-podcast/id1102026866?mt=2

 

Posted in Heart Rate Variability | Tagged , , , , | Leave a comment

Revisiting 60-s HRV recordings vs. Criterion in athletes

I’ve recently had the pleasure of peer-reviewing a few very well-written and carried out studies investigating duration requirements for stabilization preceding HRV recordings by different research groups. I look forward to seeing the published versions as the quality of the papers was very high.

In reviewing these papers it prompted me to reconsider what we all have been using as the criterion period. My colleagues and I have published 5 papers using a 5-min R-R sample preceded by a 5-min ‘stabilization’ period (10 min total duration) as the criterion (as has other groups), which is in line with traditional procedures. But I think we failed to address an important limitation of these procedures…

The issue is that the ‘traditional procedures’ were not devised for the purposes of establishing LnRMSSD specifically (rather, they needed to accommodate spectral analysis), nor were they devised for reflecting fatigue and adaptation to training programs. Therefore, for these specific purposes, it can be argued that the traditional procedures may not be as relevant, or at the very least, calls into question whether the 5-10 min period following the 0-5 min stabilization is in fact a criterion within this context.

Some things to consider:

  • 10 min is a long time to lay or sit still, especially for athletes who struggle to go 30-sec without checking their iPhone (I don’t think anyone disputes this). Are they more relaxed and stable in this situation or are they growing impatient and restless?
  • Are ANS responses and adaptation to training best measured in a completely relaxed state, or perhaps in response to a mild stimulus such as orthostasis (sitting or standing) (previous thoughts on this here)?
  • Should we be as skeptical with the ‘criterion’ recordings as much as as we are with 60-s recordings? How do we know if one is better than the other in the context of monitoring athletes? There’s now numerous studies by different groups showing the usefulness of 60-s measures for reflecting training responses, associating with fitness, etc.
  • Perhaps the question shouldn’t be regarding the optimal duration of the recording but rather, what is the shortest, most convenient procedure possible that still provides meaningful training status information? I don’t think an athlete or coach cares if their 60 sec HRV isn’t the same as the criterion if it’s still providing useful information.
  • I’m doubtful we would have completed any longitudinal training studies where HRV recordings were >60 sec on a near-daily basis. In my experience, >60 sec measures are not feasible with teams. Therefore, it’s ~60 s or we don’t bother.
  • Should future research instead try to determine what are the best ways to perform a ~60 sec HRV measure to limit noise from confounding factors? How can we improve the validity and reliability of 60-sec measures? How long from food/fluid ingestion should we wait? Can we obtain this with PPG rather than HR straps? What is the best position to measure in? etc.

To be clear, I still think that research evaluating stabilization requirements and comparing to the ‘criterion’ is absolutely meaningful and an important starting point. This was not intended to be critical, but rather to open discussion on future research directions.

 

 

Posted in Heart Rate Variability, Monitoring | Tagged , , , , , | 1 Comment