Heart Rate Variability in College Football Players throughout Preseason Camp in the Heat

Here’s a quick look at our latest study examining cardiac-autonomic responses to preseason camp in the heat among college football players. The free full text can be accessed here: Heart rate variability in college football players throughout preseason camp in the heat IJSM

Intensive training periods tend to increase RHR and decrease HRV, reflecting stress and fatigue. However, adaptations to heat exposure (e.g., plasma volume expansion) tend to have the opposite effects. So we wanted to see what happens when players were exposed to both intense training and intense heat stress during preseason camp.

Despite increases in perceived fatigue throughout the 2-week period, RHR and HRV reflected responses consistent with heat acclimation.

HRV initially decreased in linemen, then peaked after a day of rest. Non-linemen faired a little better with smaller decrements in perceived fatigue and more frequent day-to-day improvements in RHR and HRV.

These results indicate that heart rate parameters and perceived fatigue are independent markers of training status, and that desirable cardiovascular adaptations can occur in the presence of soreness and fatigue.

This is especially important for tech companies who try to infer recovery status from HRV alone. As HRV improved throughout camp, an app’s algorithm would report to coaches that players are well-recovered. Given that no player feels well-recovered during preseason camp in the heat, the technology suddenly loses credibility for being wrong and will likely be dismissed.

This is unfortunate because the heart rate parameters are likely reflecting important adaptations that may indicate better tolerance to training in the heat, a reduced exercising heart rate, and improved fitness. Thus, I encourage users to ignore “recovery” scores and interpret the data in appropriate context.

ABSTRACT 

We aimed to characterize cardiac-autonomic responses to a 13-day preseason camp in the heat among an American college football team. Players were categorized as linemen (n=10) and non-linemen (n=18). RHR, natural logarithm of the root-mean square of successive differences multiplied by twenty (LnRMSSD), and subjective wellbeing (LnWellness) were acquired daily. Effect sizes±90% confidence interval showed that for linemen, LnRMSSD decreased (moderate) on day 2 (71.2±10.4) and increased (moderate) on day 12 (87.1±11.2) relative to day 1 (77.9±11.2) while RHR decreased (small–moderate) on days 6, 7, and 12 (67.7±9.3–70.4±5.5 b∙min-1) relative to day 1 (77.1±10.1 b∙min-1). For non-linemen, LnRMSSD increased (small–large) on days 3–5, 7, 12, and 13 (83.4±6.8–87.6±8.5) relative to day 1 (80.0±6.5) while RHR decreased (small–large) on days 3–9, 12, and 13 (62.1±5.2–67.9±8.1 b∙min-1) relative to day 1 (70.8±6.2 b∙min-1). Decrements in LnWellness were observed on days 4–10 and 13 for linemen (moderate) and on days 6–9, 12, and 13 for non-linemen (small–moderate). Despite reductions in LnWellness, cardiac-autonomic parameters demonstrated responses consistent with heat-acclimation, which possibly attenuated fatigue-related decrements.

HRV Monitoring During Strength and High-Intensity Interval Training Overload Microcycles

Thanks to Christoph Schneider for inviting my collaboration on this new study from his PhD work. The full-text can be viewed here.

Heart Rate Variability Monitoring During Strength and High-Intensity Interval Training Overload Microcycles

Abstract

Objective: In two independent study arms, we determine the effects of strength training (ST) and high-intensity interval training (HIIT) overload on cardiac autonomic modulation by measuring heart rate (HR) and vagal heart rate variability (HRV).

Methods: In the study, 37 well-trained athletes (ST: 7 female, 12 male; HIIT: 9 female, 9 male) were subjected to orthostatic tests (HR and HRV recordings) each day during a 4-day baseline period, a 6-day overload microcycle, and a 4-day recovery period. Discipline-specific performance was assessed before and 1 and 4 days after training.

Results: Following ST overload, supine HR, and vagal HRV (Ln RMSSD) were clearly increased and decreased (small effects), respectively, and the standing recordings remained unchanged. In contrast, HIIT overload resulted in decreased HR and increased Ln RMSSD in the standing position (small effects), whereas supine recordings remained unaltered. During the recovery period, these responses were reversed (ST: small effects, HIIT: trivial to small effects). The correlations between changes in HR, vagal HRV measures, and performance were weak or inconsistent. At the group and individual levels, moderate to strong negative correlations were found between HR and Ln RMSSD when analyzing changes between testing days (ST: supine and standing position, HIIT: standing position) and individual time series, respectively. Use of rolling 2–4-day averages enabled more precise estimation of mean changes with smaller confidence intervals compared to single-day values of HR or Ln RMSSD. However, the use of averaged values displayed unclear effects for evaluating associations between HR, vagal HRV measures, and performance changes, and have the potential to be detrimental for classification of individual short-term responses.

Conclusion: Measures of HR and Ln RMSSD during an orthostatic test could reveal different autonomic responses following ST or HIIT which may not be discovered by supine or standing measures alone. However, these autonomic changes were not consistently related to short-term changes in performance and the use of rolling averages may alter these relationships differently on group and individual level.

 

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

HRV responses to in-season training among D-1 college football players

During spring training camp, we found that Linemen demonstrate the greatest reductions in LnRMSSD at ~20 h post-training, followed by Mid-Skill and Skill, possibly reflecting inadequate cardiovascular recovery between consecutive-day sessions for the larger players, despite lower PlayerLoad values. (Full-text available here)

Our first follow-up study during the early  part of the competitive season found the same position-based trend, where Linemen demonstrated the greatest reductions in LnRMSSD at ~20 h post-training, followed by Mid-Skill and Skill. However, the magnitude of the reductions in LnRMSSD during the in-season were smaller relative to spring camp. We speculate that both reduced PlayerLoad values (15-22% lower than spring camp) and adaptation to intense preseason training in the heat and humidity during the preceding weeks account for the smaller LnRMSSD reductions observed during the early part of the competitive season. (Full-text available here)

Cardiac-Autonomic Responses to In-Season Training Among Division-1 College Football Players.

Despite having to endure a rigorous in-season training schedule, research evaluating daily physiological recovery status markers among American football players is limited. The purpose of this study was to determine if recovery of cardiac-autonomic activity to resting values occurs between consecutive-day, in-season training sessions among college football players. Subjects (n = 29) were divided into groups based on position: receivers and defensive backs (SKILL, n = 10); running backs, linebackers and tight-ends (MID-SKILL, n = 11) and linemen (LINEMEN, n = 8). Resting heart rate (RHR) and the natural logarithm of the root-mean square of successive differences multiplied by twenty (LnRMSSD) were acquired at rest in the seated position prior to Tuesday and Wednesday training sessions and repeated over three weeks during the first month of the competitive season. A position × time interaction was observed for LnRMSSD (p = 0.04), but not for RHR (p = 0.33). No differences in LnRMSSD between days was observed for SKILL (Tuesday = 82.8 ± 9.3, Wednesday = 81.9 ± 8.7, p > 0.05). Small reductions in LnRMSSD were observed for MID-SKILL (Tuesday = 79.2 ± 9.4, Wednesday = 76.2 ± 9.5, p < 0.05) and LINEMEN (Tuesday = 79.4 ± 10.5, Wednesday = 74.5 ± 11.5, p < 0.05). The individually averaged changes in LnRMSSD from Tuesday to Wednesday were related to PlayerLoad (r = 0.46, p = 0.02) and body mass (r = -0.39, p = 0.04). Cardiac-parasympathetic activity did not return to resting values for LINEMEN or MID-SKILL prior to the next training session. Larger reductions in LnRMSSD tended to occur in players with greater body mass despite having performed lower workloads, though some individual variability was observed. These findings may have implications for how coaches and support staff address training and recovery interventions for players demonstrating inadequate cardiovascular recovery between sessions.

Figure 1

 

Our next paper, currently in production, will feature HRV responses among positions throughout the entire preparatory and competitive season.

Illness, recovery time, travel stress, monitoring, etc.

I think many would agree that the biggest obstacle in making continued training progress is experiencing illness or injury. This assumes of course that the programming is appropriate and progressive in nature for the individual. Therefore, monitoring training status is essential to appropriately manipulate training loads in effort to; a) maximize progress and b) avoid set backs. This gives you much more control over the process of training and in many cases can potentially allow you to avoid illness, injury, overtraining etc.

Unfortunately sometimes, illness or injury happens despite careful monitoring. However, it’s how you handle these unfortunate situations with proper training loads that can make a huge difference in continuing where you left off before the incident, or seeing massive performance decrements that take much longer to recover from. I have experienced both situations. I’ve fallen ill and seen my strength plummet for quite some time after the illness. This was most likely from insufficient recovery from before I resumed intense training again, lifting too heavy, too soon. More recently however, I handled illness much more appropriately and have been able to continue from where I left off without suffering significant performance decrements.

ILLNESS

My nephew Kevin and I at the park


When I was visiting some family in Cincinnati this spring I was very excited to see my twin nephews. I hadn’t seen them in over a year since they were born. A few days before they arrived in Cincinnati (coming from New Hampshire) they contracted hand, foot and mouth disease. My sister warned us that it was contagious for anyone who has never had it before. I wasn’t too concerend and we all wanted to see the twins even if it meant getting a little sick. Well, long story short I picked up the virus and it destroyed me. If you’ve ever had this as an adult you know how awful this can be.

My nephew Ethan and I on the back porch

In my chart below you can see a distinct disruption in my HRV trend occuring when I experienced the first symptoms of the illness. On June 9th I woke up with a resting heart rate of 108bpm and an HRV score of 42.9! I had a terrible sleep that night and had a high fever that morning. The fever persisted for about 72 hours at which point I assumed the worst was over. I saw my HRV start to climb back up a bit, however at this point some new symptoms appeared and my HRV again dropped. As you can see in the chart, I didn’t train (the vertical purple bars represent training load). Once all of my symptoms subsided and HRV returned to previous baseline levels I resumed training at very moderate loads (session RPE of 7).

You’ll notice that these moderate loads were apparently very stressful on my body reflected by large HRV fluctuations. Typically a workout rated as a 7 is a deload workout for me. Being able to see my body’s responsiveness to these moderate loads showed me that although my symptoms were gone, my body was still trying to overcome the illness. In the past I likely would’ve resumed intense training once symptoms subsided, however by monitoring HRV, I was able to hold off on more intense loading until my body was capable of handling it sufficiently. You can see that it was nearly 3 weeks until I performed a more intense workout (sRPE 8). I can happily say that althought there was some minor strength loss (bound to happen after nearly 3 weeks of 0-moderate training loads), I was able to gain it all back very quickly unlike previous instances.

Purple Vertical Bars = Training Load
Horizontal Blue Wavy Line = HRV Baseline
Horizontal White Line = Day to Day HRV Fluctuations

Travel/Moving Stress

In the image above on the right hand side of the chart, you will see about a week’s worth of low HRV scores indicated by red and amber deflections. This was the week that I moved from grad school (I completed my Masters) back to Toronto. Clearly this was a very stressful week settling into a new place and dealing with all of the typical issues associated with a move. After appropriately manipulating my training loads (reducing them) I was able to maintain strength and see a return to baseline once I felt settled in. In the past after my first day of being back I likely would’ve continued with intense training. As you can see, this likely would’ve been detrimental to my progress.

Take Home Messages

First and foremost, have an effective monitoring strategy with yourself/athletes. Without one, it’s nearly impossible to make critical manipulations in training load to avoid running into problems. I’m obviously a proponent of HRV and recommend you track yours. Once you have your monitoring in place, have the discipline to reduce loads when you know you should. Sometimes you may not even perceive yourself as being under significant stress, however this is often how people end up hitting a wall with their training. You can’t necessarily ‘feel’ if your adaptive capacity is high or low. In previous posts I showed what happens when you train hard with low HRV. You simply delay recovery and potentially hurt progress.

Think outside the box a little. Training hard for 3 weeks and deloading on the 4th week is pretty standard and for the most part effective. However, just because your program tells you it’s week 3 and therefore you need to train heavy, doesn’t actually meant you HAVE to. I used to do this and thought that if I missed a workout or didn’t hit my goals that day, that I wouldn’t make progress. I’ve learned that the opposite is actually the case.

Lastly, have a plan in place for when certain events occur such as moving or illness. Have a strategy for how you will deal with it (hopefully in response to your monitoring data). This should help you maintain training progress better by allowing your body the appropriate time to recover while imposing loads that remain within your body’s ability to adapt.