New Podcast: Discussing Smartphone HRV Apps

I recently had a chance to sit down and discuss all things HRV monitoring with James Darley of the Historic Performance Podcast. There’s also a number of great interviews in the podcast archives worth checking out.

Topics discussed:

  • Background
  • Physiological basis for HRV as a recovery status metric
  • Preferred HRV parameter for athletes
  • HRV recording methodology (position, conditions, time of day, etc.)
  • Considerations for chosing the right HRV app for your situation
  • Recent research
  • Interpreting HRV data

Link to Podcast with show notes 

Show in Overcast App



Early HRV changes relate to the prospective change in VO2max in female soccer players

It’s been a good start to the Thanksgiving break with the  acceptance of our latest study entitled “Initial weekly HRV response is related to the prospective change in VO2max in female soccer players” in IJSM (Abstract below).

We’re currently working on supporting these findings with a much larger sample size in the new year.


The aim of this study was to determine if the early response in weekly measures of HRV, when derived from a smart-phone application, were related to the eventual change in VO2max following an off-season training program in female soccer athletes. Nine female collegiate soccer players participated in an 11-week off-season conditioning program. In the week immediately before and after the training program, each participant performed a test on a treadmill to determine maximal oxygen consumption (VO2max). Daily measures of the log-transformed root mean square of successive R-R intervals (lnRMSSD) were performed by the participants throughout week 1 and week 3 of the conditioning program. The mean and coefficient of variation (CV) lnRMSSD values of week 1 showed small (r = -0.13, p= 0.74) and moderate (r = 0.57, p = 0.11), respectively, non-significant correlations to the change in VO2max at the end of the conditioning program (∆VO2max). A significant and near-perfect correlation was found between the change in the weekly mean lnRMSSD values from weeks 1 and 3 (∆lnRMSSDM) and ∆VO2max (r = 0.90, p = 0.002). The current results have identified that the initial change in weekly mean lnRMSSD from weeks 1 to 3 of a conditioning protocol was strongly associated with the eventual adaptation of VO2max.


New Study: Smartphone-derived HRV and Training Load in a Female Soccer Team

About a week ago our latest study was published ahead of print in the International Journal of Sports Physiology and Performance.

Smartphone-derived Heart Rate Variability and Training Load in a Female Soccer Team.

This study was 4 years in the making and is without a doubt the biggest project we’ve done to date. Since my Masters in 2011/2012, it’s been my number one priority to study the usefulness of smartphone-derived HRV in a team of athletes. Every project we’ve done leading up to this was simply to enable us to conduct this study. This includes:

  • Validation of the smartphone app (link)
  • Evaluating the agreement between standard HRV recordings (5-min) and ultra-short recordings utilized by the app (60-s) (link)
  • Evaluating the time-course of HRV stabilization in athletes to determine the most convenient and valid recording methodology (link)
  • And some case study work (link)

Finally, in 2014 we implemented smartphone-HRV monitoring with a collegiate female soccer team throughout their spring season. The icing on the cake was having this paper accepted in IJSPP, a journal that I’ve been reading for years and that has published some very important papers that have advanced the practical application of HRV monitoring in field settings. The following will serve as a brief overview of the study.


  • Up until recently, HRV data has been traditionally recorded via ECG in the laboratory or with heart rate monitors in the field. The cost and time consuming nature of data collection and analysis procedures with these systems make them prohibitive in team-sport settings. Smartphone HRV technology is an affordable, user-friendly and new alternative that has yet to be studied in the field.
  • Smartphone apps utilize ultra-short recording procedures for HRV data acquisition (brief stabilization period followed by ~1 min recording). These modified recording procedures have not been studied in field settings and therefore it is unclear if meaningful training status information can be acquired with such short R-R interval recordings.
  • It is unclear which position is more preferable for HRV recording. Parasympathetic saturation has been observed in highly fit athletes in the supine position. This is when HRV is low despite very low resting heart rates. Therefore, HRV measures following an orthostatic stimulus (upright posture) have been proposed for use in highly fit athletes to counteract saturation effects. More research to determine which position is most suitable for team-sport athletes is required.
  • The weekly HRV mean and CV have been proposed to be more meaningful than isolated (once per week) measures. No previous research has assessed the evolution of mean and CV values in response to varying weekly training load in collegiate female team-sport athletes. Particularly from ultra-short, smartphone-derived measures.
  • Lastly, previous work has demonstrated that HRV measured between 3 and 5 days per week was sufficient for reflecting weekly mean values in endurance athletes. It is unclear if this applies to team-sport athletes engaged in regular strength and conditioning and soccer training. Reducing HRV measurement requirements to between 3 and 5 days per week would make HRV monitoring much more practical for coaches and athletes by reducing compliance demands.


HRV data was recorded daily by the athletes after waking with the ithlete smartphone app over 3 weeks of moderate, high and low training load. As this study took place before the Wellness feature was added to the application, Wellness measures (fatigue, sleep, soreness, mood and stress) were acquired on M-W-F of each week via SurveyMonkey (see guide here).

photo 2

Training load was quantified via sRPE which was acquired between 15-30-min following all resistance training, conditioning and soccer practice sessions via email (SurveyMonkey) delivered to each athletes smartphone.


The weekly mean and CV for HRV in both standing and supine measures was determined first intra-individually and then averaged as a group. This was also done for sRPE and Wellness values.

The supine and standing HRV mean and CV were then determined for M-W-F of each week for 3-day values and again for M-T-W-R-F for 5-day values. These were then compared to the 7-day values (the criterion).


The 5 and 3-day measures within each week provided very good to near perfect intraclass correlations (ICCs ranging from 0.74 – 0.99) with typical errors ranging from 0.64 – 5.65 when compared with the 7-day criteria. The supine values demonstrated a smaller CV compared to standing. Therefore the supine measures over 3 and 5 days agreed strongly with the 7-day measures. The standing measures, particularly when measured across 3-days showed the lowest agreement.

HRV mean values demonstrated small effects in response to varying TL where the lowest HRV mean occurred during the high load week and highest HRV mean occurred during the low load week. The CV values were highest during the high load week and lowest during the low load week. The CV was more sensitive to changes in TL than the mean values (moderate effects). Wellness values were lowest during the high load week (moderate effects) and similar between moderate and low load weeks (trivial effects).

ijspp fig

Brief Discussion and Practical Applications

This study demonstrated that the HRV CV showed greater sensitivity to the changes in TL over the 3-week training period. Essentially, during high load training, the athletes experienced greater fluctuation in their scores. Greater training stress caused greater homeostatic perturbation, reflected in their Wellness and HRV scores in both standing and supine positions. In contrast, during the low load week, there was less day-to-day fluctuation in HRV because there was less fatigue from training stress. Therefore, monitoring CV changes throughout training may provide insight regarding training adaptation. Athletes experiencing greater fatigue will likely show greater CV values. More experienced athletes and those with higher fitness will likely demonstrate lower CV values. When these athletes show increases in the CV, it may be due to non-training related stressors. Comparing individual values to the group average will help identify athletes who may require further follow-up to determine if training of lifestyle modification is necessary.

Quoting from the paper:

Smart-phone derived, ultra-short HRV is a potentially useful, objective internal training status marker to monitor the effects of training in female team-sport athletes as part of a comprehensive monitoring protocol. Coaches and physiologists are encouraged to evaluate the weekly CV in addition to the weekly mean when interpreting HRV trends throughout training as this marker was more sensitive to TL adjustment in the short-term (i.e, 3 weeks). An increase in lnRMSSDmean and decrease in lnRMSSDcv were observed when TL was reduced following moderate and high TL weeks and interpreted as a positive response. Both supine and standing CV measures related well to TL in this study but only supine CV values acceptably maintained this relationship when assessed in 5 and 3 days. Therefore, caution should be used when evaluating standing HRV when only 5 or 3-day measures are used. Seated measures may provide a lower CV relative to standing while still providing an upright posture to counteract possible saturation effects. This may make seated measures preferable to standing as a lower CV is more likely to be captured in fewer than 7 days as demonstrated with the supine values. Reducing HRV data collection to 5 days per week may alleviate compliance demands of athletes and thus may make HRV implementation a more practical monitoring tool among sports teams.

Making HRV More Practical For Athletes: Measurement Frequency?

Perhaps the biggest limitation with HRV monitoring in a team setting is obtaining and maintaining compliance from athletes. Daily HRV measurements can become monotonous, particularly for athletes who may not fully understand the value of the data. One question I’ve had in mind for a while now is; what is the minimal frequency of HRV measurements we can acquire that can still offer meaningful information regarding training status in athletes?

If you’ve read any of the research on HRV and athletes, you’d note that HRV is rarely measured daily. This is likely because having each subject report to the lab everyday to have their HRV measured on an ECG is impractical. However, with the advent of valid and reliable devices such as the Polar RS800, R-R intervals can be collected in the field making more frequent measurements a little more practical in the research setting. However, for the practitioner in the field, an even more practical, economical and user friendly device is desired. Thankfully smart phone app’s such as ithlete were created to accommodate this.

So now we have very affordable, very user friendly smart phone applications that can provide us with HRV data. The trick is getting the athletes to use them often enough so that we can use the data for monitoring purposes. Is it more of a reasonable expectation of our athletes to collect only one or two HRV measurements per week as opposed to every day? Will this provide us with enough information to draw meaningful interpretations from?

After giving it some thought, I decided to review some data over a 3 month period. With my own HRV data, I recreated trends in excel with; once per week, twice per week and daily measurements. The purpose of this is to see what these varying frequencies of measurement reveal in the trend. I’ve also included sleep score data which is graded 1-5 based on perceived quality and quantity after waking.

Daily Measurement 3 Month Trend



–          There is a period of time between the 4th week of December to the 2nd week of January that my HRV trend declines and I rarely see scores over 80. During this time (the Christmas Holidays)I was not lifting regularly and experienced some detraining.

–          Daily measurements allow for sRPE to be recorded providing the coach with a good indication of how the athlete is perceiving and responding to the workouts. Conversely, the sRPE allows the coach to see when the athlete is experiencing high stress in the absence of a high load training day.

–          Daily measurements allow the coach to see acute changes in HRV which can be important in planning or manipulating training.

–          It’s worth mentioning that my highest levels of strength were displayed over the last week of February and early March (early March not included). This is expected as I am nearing the end of my training cycle which has transitioned from moderate intensity/high volume to high intensity/low volume. Coincidentally, my HRV is reaching peak heights. I’m not entirely sure what to attribute these high scores to as I have been doing less aerobic work than normal. This may or may not have any meaning. Some vid’s are posted below from this “realization” phase. 



 Once Per Week HRV Measurement 3 Month Trend


–          I chose Monday as the reference day because it is the day of the week furthest from training stress that can influence HRV. My goal was to find a day that gives me the best indication of baseline HRV. Since I train Mon-Fri and rest on weekends this left Sunday or Monday as the best options. I selected Monday over Sunday because Saturday nights can be social, late, etc. and therefore affect Sunday morning results.

–          This trend clearly shows my detraining period over the holidays.

–          Given that I adjust my training when necessary to avoid excessive fatigue accumulation, my baseline HRV is relatively consistent apart from the detraining period. Training is being well tolerated because I’m intentionally adjusting my training for that purpose. However, in a more pre-planned setting such as a collegiate weight room the result/trend would likely differ; particularly in a preparation phase (pre-season, early off-season, etc)

–          Coaches should be cautious when using weekly measurements due to potentially low scores caused by non training related stressors that may obscure interpretation. For example, if an athlete has a rough sleep Sunday night, HRV may be lower than usual Monday morning. This does not mean the athlete is fatigued or should have training loads reduced. Therefore, coaches need to keep tabs on performance and feedback from the comments section.  Clearly, weekly measurements have its limitations however it still may offer some value.

Twice Per Week HRV Measurements 3 Month Trend


–          I chose Monday and Saturday as my reference days because Monday represents HRV at rest while Saturday represents HRV after fatigue has been accumulated all week from training. This may provide some insight as to how stressful the training was based on Mon-Fri change in HRV. I am a bad example for this as I try and allow for HRV to reach baseline at least once during the week using Wednesday as an active recovery day. Data from an athlete involved in training, practices, class, etc. would have a different trend.

–          This trend allows for comparison of Sleep quality pre and post microcycle. In my trend, Mondays sleep scores never fall below 4 while there are 2’s and a 3 from Friday night’s sleep.

– As with the weekly measurement, this trend fails to capture major acute changes (highs and low’s).

Final Thoughts

Weekly measurements performed after a day or two of rest to allow for a true measure of baseline HRV can be useful in determining how an individual is coping with training on a week to week basis. However, I would urge you to be very cautious when interpreting trends as a low score caused by poor sleep or something other than training fatigue can provide a false sense of training response. This is where subjective measures, performance indications and regular communication is important.

Twice per week measurements might be the frequency which provides us with the most meaningful information from the least amount of data and therefore demand from the athlete. Seeing how HRV changes from pre to post training over a one week period likely provides much more meaningful information about training status verses weekly measures. It goes without saying that this needs to be manipulated according to the team’s training/practice/competition schedule. I used myself as the example today but most teams will not have Saturday and Sunday completely off from training.

Perhaps starting with weekly or twice weekly measurements is sufficient for getting athletes started and comfortable with the device. The goal should be to eventually get them to take daily measurements as this will provide more complete information including sRPE, daily sleep score and comments. The comments section is highly underrated and I intend to elaborate more on it’s value in a future post.

Correlation between HRV, sRPE and subjective fatigue in athletes

Today I will review the research I’ve read that investigates the relationship between perceived exertion ratings of a workout session (sRPE), subjective levels of fatigue and HRV in effort to examine the usefulness of HRV in reflecting training load in athletic populations. Like all of my articles, this report is based on my interpretation of the research and perspectives from personal experience.

The Research

In a brand new study from the JSCR, Sartor and colleagues (2013) followed elite male gymnasts (n=6, age 16) over 10 weeks of training. HRV was monitored daily every other week while sRPE was collected immediately following each workout. HRV strongly correlated to previous day sRPE in both supine (HF%, HF%/LF%) and supine to seated measurements (mean RR, mean HR, HF%, SD1). Relationships were also seen between HRV, and perceived wellness (foster’s index). HRV correlated with training load (sRPE) and psychophysiological status.

Though sRPE wasn’t used in this next study, KeTien (2012) monitored HRV, blood-urine nitrogen (BUN) and profile of mood states (POMS) in 24 national level rugby players over an 8 week conditioning program. The program progressed from more aerobic based work to more anaerobic/interval based work. Spectral measures of HRV correlated with both POMS and BUN at each time point throughout the training period.

During the 2006 World Cup, Parrado and colleagues (2010) set out to determine if perceived tiredness could predict cardiac autonomic response to overload in elite field hockey players (n=8).  A strong correlation was found between per­ceived tiredness scores and HRV. Higher levels of perceived tiredness (acquired from questionnaire) were related to lower values of parasympathetic tone (RMSSD), pNN50 and higher LF/HF ratio. In order to discern changes in HRV brought on by fatigue from changes in HRV caused by pre-competitive anxiety, the researchers had the athletes complete anxiety questionnaires.

“Results show that cognitive anxiety and self-confidence sub­scales of the CSAI–2 were not related to perceived tiredness nor to heart rate variability. In the absence of a relation between cognitive anxiety and heart rate variability, it can be assumed that the relationship established between heart rate variability indexes and perceived tiredness scores are attributable to the fatigue state.”

Accounting for pre-game anxiety is very important as previous research has shown this to affect HRV (Edmonds et al. 2012, Mateo et al. 2012, Murray et al. 2008), thus making it difficult to distinguish fatigue from acute anxiety on the morning of a competition.

Edmonds et al. (2012) found that HRV (HF) correlated with sRPE in youth rugby players (n=9) during a one week microcycle of practices and a game. However, game day HRV values were lower which was attributed to the aforementioned pre-game anxiety since training loads were reduced before the competition.

Smith and Hopkins (2011) monitored performance, HRV, sRPE and subjective fatigue in elite rowers (n=10) throughout an intense 4 week training period. Interestingly, the most improved athlete and the only overtrained athlete both had statistically similar levels of perceived fatigue and changes in LF/HF ratio. However, after looking closely at the data, RMSSD showed a noticeable decline in the OT athlete compared to the most improved who had a moderate increase in RMSSD. The determining factor however in this case was performance changes.

Thiel at al. (2012) found that in 3 elite male tennis players, HRV, serum urea and psycho-physical state (assessed by EBF-52 questionnaire) each responded to overload training. As training load increased, HRV (RMSSD) decreased, perceived fatigue increased and serum urea increased. However, performance increased (V02 max, Single Leg CMJ, DJ index) and therefore performance metrics should always be considered when trying to discern functional overreaching (FOR) from non-functional overreaching (NFOR). HRV changes act as an early warning sign while performance decrements may represent the initial transition from FOR to NFOR.

Cipryan et al (2007) found that HRV correlated to performance in hockey players (age 17, n=4) but did not correlate to self-reported health status. Therefore, coaches should use caution when using perceived stress to predict ANS status and thus an objective measure (like HRV) is still recommended.

In elite female wrestlers, perceived stress (in the form of; excessive competition schedule, social, education, occupational, economical, travel, nutritional, etc) contributed to NFOR when HRV parameters were significantly increased (Tian et al. 2012). There was no mention of perceived stress/recovery in the NFOR group with significant decreases in HRV parameters. Regardless, subjective measures of stress including non-training related events require consideration when planning training. Monitoring the global stress of an athlete is more meaningful then simply training load.

Plews et al. (2012) monitored HRV and perceived measures of recovery (sleep, soreness, etc.) in two elite triathletes over a 77 day period leading up to competition. One athlete was considered NFOR. Perceived levels of recovery were not associated with HRV. However, the NFOR athlete admitted that she felt deterred from  reporting  low scores as anything below a certain score would be automatically sent to the coach. Therefore, when relying on perceptual measures from athletes, coaches must be prudent in ensuring honest reports. HRV was a better indicator of fatigue in this study.

The last study I’d like to mention only appears to be available in German at the moment. I translated the paper with google, however it was very rough to say the least. Therefore I will simply quote the pertinent information from the abstract:

“6 endurance athletes measured morning heart rate, heart rate variability (HRV) and mood state during a normal training period, a 17 day ultrarace (Deutschlandlauf) and following a recovery period. 4 out of 6 runners could not finish the race due to injury or exhaustion. 3 of them showed diagnostically relevant criteria of overreaching. All runners who quit the race showed increased morning heart rate, decreased HRV and a decreased mood state during competition. The studied parameters showed individually different adaptations but there were early changes that preceded the abortion of the run that gave diagnostically relevant information.” (Bossmann 2012)


Though there appears to be a strong tendency for HRV to reflect perceived training load and subjective fatigue, an objective measure of ANS status should still be considered. Subjective measures from athletes are only meaningful if honestly reported.

I’ve personally seen a strong correlation between morning HRV score and session rating of perceived exertion (sRPE) of the previous day’s workout. However, I’ve learned that this relationship isn’t perfect. I’ve experienced situations where;

–          Perceived exertion may be high but HRV response may be minimal if the workout is familiar (exercise selection, order, intensity, etc.).

–          In direct contrast to the above, perceived exertion may be moderate but HRV response may be significant if the workout is unfamiliar.

–          Non-training related factors affect HRV. Sleep, aerobic fitness, mental stress, nutrition, etc. can all impact ANS activity, possibly obscuring the relationship between training load and HRV.

–          Stress from travel, illness, occupation, etc. may have a larger impact on ANS than is perceived and reported.

–          More on other factors effecting HRV here.

In conclusion, obtaining both objective and subjective measures of fatigue along with performance indicators will provide a more accurate indication of training status. Monitoring of these variables regularly should enable the coach to better manipulate training loads to ensure progression and avoid unintentional overreaching.


Bossman, T. (2012) Effects of ultra-long-distance running on selected physiological and psychological parameters as a possible marker of overloading. Swiss Journal of Sports Medicine, 60(1): 21-5. Full Text

Cipryan, L., Stejskal, P., Bartakova, O., Botek, M., Cipryanova, H., Jakubec, A., Petr, M., & Řehova, I. (2007)  Autonomic nervous system observation through the use of spectral analysis of heart rate variability in ice hockey players.  Acta Universitatis Palackianae Olomucensis. Gymnica, 37(4): 17-21. Free Full-Text

Edmonds, RC., Sinclair, WH., and Leicht, AS. (2012) The effect of weekly training and a game on heart rate variability in elite youth Rugby League players. Proceedings of the 5th Exercise & Sports Science Australia Conference and 7th Sports Dietitians Australia Update. Research to Practice  Abstract

Ke-Tien, Y.(2012) Effects of Cardiovascular Endurance Training Periodization on Aerobic performance and Stress Modulation in Rugby Athletes. Life Science Journal, 9(2): 1218-25. Full-Text

Mateo, M. et al. (2012) Heart rate variability and pre-competitive anxiety in BMX discipline. European Journal of Applied Physiology, 112(1): 113-23.

Murray, N. P. et al. (2008) Heart rate variability as an indicator of pre-competitive arousal. International Journal of Sport Psychology, 39: 346-355.

Plews, DJ., Laursen, PB., Kilding & Buchheit, M. (2012) Heart rate variability in elite triathletes, is variation in variability the key to effective training? A case comparison. European Journal of Applied Physiology, 112(11): 3729-41.

Parrado, E.  et al. (2010)Perceived tiredness and HRV in relation to overload during a field hockey world cup. Perceptual and Motor Skills, 110(3): 699-713 Abstract

Sartor, F. et al. (2013) Heart rate variability reflects training load and psychophysiological status in young elite gymnasts. Journal of Strength & Conditioning Research, Published ahead of print.

Smith, T.B., & Hopkins, WG. (2011) Heart rate variability and psychological stress in an elite female rower who developed over-training syndrome. New Zealand Journal of Sports Medicine, 38(1): 18-20.

Thiel, C. et al. (2012) Functional overreaching in preparation training of elite tennis professionals. Journal of Human Kinetics, DOI: 10.2478/v10078-011-0025-x

Tian, Y., He, ZH., Zhao, JX., Tao, DL., Xu, KY., Earnest, CP. & McNaughton, LR. (2012) Heart rate variability threshold values for early-warning non-functional overreaching in elite women wrestlers. Journal of Strength & Conditioning Research, Published ahead of print


HRV and Strength Research: Implications for Strength/Power Athletes?

At this point there is quite a bit of research pertaining to HRV and aerobic exercise/endurance training. However, the application of HRV for strength/power (S/P) athletes is less clear. Today I will discuss the available research pertaining to resistance training (RT) and HRV and share some of my thoughts on the topic.

Unfortunately for S/P athletes, the majority of the research that exists involving RT and HRV do not involve athletes. Rather, most of the research tests the effects that RT has on resting HRV for the purposes of improving health/reducing mortality in elderly or diseased populations. Nevertheless, I will summarize what I’ve read.

Heffernan and colleagues (2007) found no change in HRV following 6 weeks of RT and after 4 weeks of detraining in 25 year old male untrained subjects (n=14).

Cooke and Carter (2005) saw non-significant increases in HRV following 8 weeks of RT compared to control in healthy young adults (n=22).

In middle aged folks with pre-hypertension, aerobic exercise increased HRV while RT resulted in decreases in HRV (Collier et al. 2009). In healthy young adults aerobic training improved HRV (in men but not women) while RT had no effect (Sloan et al. 2009).

Elite endurance athletes had higher HRV at rest compared to Elite power athletes but the power athletes had better resting HRV than control (Kaltsatou et al. 2011). No surprise here.

Following 16 weeks of resistance training, a high intensity group and a low intensity group of healthy older women both improved strength with no significant changes in HRV (Forte et al. 2003). These results were consistent with findings by Madden et al (2006) with the same population however they included an aerobic training group who did see increases in HRV.

RT improved HRV in women with fibromyalgia in a study by Figueroa et al. (2007) but failed to improve HRV in the same population in work by Kingsley et al. (2010).

Compared to 3 months of low intensity training (calisthenics and breathing training), intense training (combined aerobic and strength training) improved HRV at rest and in response to orthostasis (standing) in COPD patients (Camillo et al. 2011). The researchers found that better baseline HRV, muscle force and daily levels of activity were predictors of HRV changes after exercise intervention.

In healthy older men, 12 weeks of eccentric RT resulted in decreased HRV. (Melo et al. 2008)

If one’s goal is to increase HRV via exercise then I would definitely go with aerobic work as this seems to be more effective than RT, though the results are conflicting. Training protocols, subjects, health status, age, HRV measurement position and duration, etc. all vary quite a bit which likely accounts for the conflicting results. I assume that there is a volume/intensity threshold that must be met during RT periods to cause a change in resting HRV. For optimal health it is likely that a combination of aerobic work and RT will offer the most benefits.

From personal experience, I see much higher scores when I incorporate more aerobic or intermittent conditioning work. In reviewing my all time HRV trend, I can clearly see that over the spring and summer (03-09) of 2012 I had considerably more green scores and higher deflections. This is in line with the time that the weather got nicer and I started doing 30-40 minute runs 3-4x/week (March was unusually warm last year). I got really sick for 2 weeks in June as I discussed here, otherwise I would expect  my trend to be even higher. Once Sept. rolled around I started working full-time again and reduced my aerobic work to 2x/week for about 2o minutes and at a lower intensity at which point baseline declines back to pre-spring/summer levels.


Implications for S/P Athletes

The application of HRV for S/P athletes is obviously different than for elderly or diseased populations. RT is incorporated in training as a means to increase performance, not to increase vagal tone. Therefore, the utility of HRV for this population revolves around its potential ability to:

(Any research I discuss in this section has been cited previously and will not be cited again today, see my older posts for references.)

  • Predict training outcomes

–       Higher HRV at baseline results in improvements in aerobic performance (see here). Would higher baseline HRV result in better S/P improvements? If so, would purposeful manipulation of ANS prior to intensive RT periods via “aerobic” (read “work capacity”) training be of benefit? We already know the importance of GPP but is this relationship mirrored in HRV? If so, HRV may be worth monitoring during these periods.

–       Better basketball and ice hockey performance as well as endurance performance has been correlated with HRV (specifically parasympathetic tone) as I’ve discussed in previous posts. I’m not sure this relationship exists with S/P athletes but it would still be worth testing. Anecdotally, I’ve experience reduced strength performance when HRV is low due to physical fatigue. However, I haven’t really seen strength affected when HRV is low caused by other factors (sleep, other stressors, etc.) Therefore, establishing this relationship must involve careful consideration of these variables.

  • Reflect Recovery Status/Training Load, Overreaching/Non-Functional Overreaching

–       Does overreaching in S/P athletes result in a concomitant decrease in performance and HRV?  Elite female wrestlers were considered non-functionally overreached when performance decreased and HRV was significantly above or below baseline for greater than 2 weeks. Elite tennis players saw significant decreases in HRV but improved performance. Generally in endurance athletes, overreaching will result in decreased performance and a significant increase or decrease in HRV (from baseline).

–       I feel that in S/P athletes, performance probably won’t decrease concurrently with HRV assuming it is a gradual decline as a result progressively increasing training loads. Rather, HRV will probably change first indicating an accumulation of fatigue and performance will fall at some point after if loading persists. Monitoring HRV may be useful to prevent excessive fatigue/overreaching if that isn’t the goal. Perhaps it is also useful in detecting transitions from functional to non-functional overreaching (the point at which HRV changes from overly sympathetic to highly parasympathetic).

–       Does the return to baseline HRV (after overreaching) happen concurrently with return or increase in S/P performance? This was the for case elite swimmers as peak performance occurred concurrently with peak HF values (parasympathetic tone). If so HRV would be a good tool for guiding tapers and establishing best protocols for meet/competition preparation.

–       HRV is an effective tool for guiding aerobic training. Does this apply to S/P athletes? Given that HRV reflects recovery status in S/P athletes (both in the research and anecdotally) and that HRV is sensitive to pretty much all forms of stress, it would seem logical to at least consider HRV in determining daily training. HRV may serve as a guide for determining training frequency and intensity/volume based on individual recovery. More on this topic here. It would be interesting to see HRV guided vs. Pre-planned RT compared in S/P athletes.

  • Guide Periodization

–       HRV will decrease in response to an intense workout. When you perform that workout again and again, your body adapts. The workout is no longer as stressful (decrease in soreness, lack of HRV response, quick recovery, etc. What benefits can HRV offer for adjusting volumes, intensities, exercise selections, frequencies etc. in effort to continually stimulate progress? Is HRV response after a workout any indication of how effective that workout is? Of course there are other factors to consider, not just the amount of stress/fatigue a workout causes. I have repeated workouts with high perceived exertion that have had little effect on HRV. Does that indicate that a change is needed in programming?

It goes without saying that several other factors and variables should be considered when analyzing HRV. HRV is only one variable and is sensitive to a variety of factors that  can influence a result (non-training related stressors, pre-competition anxiety, etc.).


This March I will be relocating to Alabama to work in the Human Performance Lab at Auburn University (Montgomery campus) with Dr. Mike Esco. I met Dr. Esco at the NSCA National Conference in RI last summer. Dr. Esco has been researching HRV for several years now. We have several projects tentatively planned and doing an HRV and RT study is one that we’ve been considering. Hopefully we can make it happen.


Camillo, C.A. et al. (2011) Improvements of heart rate variability after exercise training and its predictors in COPD. Respiratory Medicine, 105(7): 1054-1062

Cook, W.H., & Carter, J.R. (2005) Strength training does not effect vagal-cardiac control or cardiovascular baroreflex sensitivity in young healthy subjects. European Journal of Applied Physiology, 93: 719-725

Forte, R. et al. (2003) Effects of dynamic resistance training on heart rate variability in healthy older women. European Journal of Applied Physiology, 89: 85-89

Heffernan, K.S. et al. (2007) Heart rate recovery and complexity following resistance exercise training and detraining in young men. American Journal of Physiology – Heart & Circulation Physiology, 293: H3180-H3186

Kaltsatou, A. et al. (2011) The use of pupillometry in the assessment of cardiac autonomic function in elite different type trained athletes. European Journal of Applied Physiology, 111: 2079-2087

Kingsley, J.D., et al (2010). The effects of 12 weeks of resistance exercise training on disease severity and autonomic modulation at rest and after acute leg resistance exercise in women with fibromyalgia. Archives of Physical Medicine & Rehabilitation, 91: 1551-1557

Madden, K.M. et al. (2006) Exercise training and heart rate variability in older adult female subjects. Clinical & Investigative Medicine, 29: 1 – ProQuest

Melo, R.C. et al. (2008) High Eccentric strength training reduces heart rate variability in healthy older men. British Journal of Sports Medicine, 42: 59-63

Sloan, R. P., Shapiro, P.A., DeMeersman, R.E., Bagiella, E., Brondolo, E., McKinley, P.S., Slavov, I., Fang, Y., & Myers, M.M. (2009). The effect of aerobic training and cardiac autonomie regulation in young adults. American Journal of Public Health, 99(5), 921-928

A collection of thoughts on HRV and Sports Training

I’ve been having a lot of different thoughts running through my mind recently on various topics surrounding HRV and sports training. A lot of what I say today is based on a lot of the research I’ve been reading and comparing it to my personal experience with my own training and that of my athletes. I’ll try and organize it as best I can but it will be pretty random for the most part. Below are several topics that really deserve entire posts on their own however today I will just provide some quick thoughts on each one.


HRV as a predictor of Performance and or Adaptation

–          HRV appears to predict performance in aerobic athletes. I’ve discussed and cited this research in previous posts. However, in a new study by Chalencon et al. (2012) swim performance in elite athletes was related to parasympathetic activity.

 “the delay needed to return to the initial performance level was highly correlated to the delay required to return to the initial HF power level (p<0.01). The delay required to reach peak performance was highly correlated to the delay required to reach the maximal level of HF power (p = 0.02). Building the ANS/performance identity of a subject, including the time to peak HF, may help predict the maximal performance that could be obtained at a given time.”

See the full text here.

–          Prior to the initiation of intensive training, HRV values appear to predict training outcomes, again, mostly in aerobic athletes. Higher HRV values prior to training lead to better improvements in aerobic performance.  See here for more on this.

–          Higher HRV values on game day are correlated to better performance in amateur Basketball players (Di Fronso et al. 2012).

–          There are several factors that affect an athlete’s performance on any given day. By no means am I suggesting that one is doomed to poor performance if HRV isn’t high. I like the saying “psychology trumps physiology every time”. I think it was Alwyn Cosgrove who said that? Regardless, it’s very true. Furthermore pre-game anxiety can provide a skewed HRV result. More research on this needs to be done.

–           At the moment I do not believe that strength/power can be predicted by HRV on a day to day basis based on my experience. It likely play’s a factor but is certainly not determinant.

HRV as a reflection of recovery status

–          I believe this is one of HRV’s greatest attributes. Your level of fatigue after an intense workout or competition will be reflected in your HRV score. This is valuable for planning the weekly training so as not to load the athlete too soon after competition or too much before competition. In my experience this will usually correlate to perceived recovery. You can typically feel this. However, we cannot feel what our athletes are feeling. See Edmonds et al. (2012) for a study on elite youth rugby players for data on this subject.

–          Chen et al. (2011) showed that after an intense strength workout in elite weightlifters strength and HRV dropped. Strength did not return to baseline (or even above) levels until HRV returned to at or above baseline. This is one of the few studies that used HRV in strength athletes. Most coaches/trainee’s should already be aware that 1RM strength will be reduced for the net 24-48 hours after an intense workout but is cool to see that HRV may reflect the actual time period.

HRV as an early warning sign

–          Fatigue is ok, extreme fatigue is not. HRV is probably one of the first warning signs of fatigue. How much fatigue is okay? I think that first HRV will reflect that physical stress is accumulating. However, until performance changes, we likely needn’t change anything. If training is set up appropriately there should be enough rest/recovery for HRV to approach baseline at the end of each week. This will allow for a slower, more steady decline in the trend as opposed to a more rapid and steep decline which indicates excessive fatigue and overload. Planned overreaching should include the monitoring of several training status markers. HRV will respond early.

–          Researchers found that 3 elite tennis players saw significant reductions in HRV values over pre-season training however performance improved (Thiel et al. 2012). HRV alone does not indicate functional or non-functional overreaching. HRV did not correlate to performance markers but did correlate to other training status markers.

Limitations of Weekly or Monthly HRV Monitoring as opposed to higher frequency monitoring

–          Many studies I’ve read pertaining to athletes have measured HRV periodically (weekly, monthly, pre-post training phase, etc). This is much more practical for coaches as daily HRV measurements can be tedious and compliance can be hard to get from athletes. However, day to day measurements are more valuable as they allow the coach to make training adjustments before excessive fatigue builds up. However, if a coach could only use weekly HRV measurements with athletes I think these measurements would best be done the morning after a recovery day. HRV score at rest will provide the most meaningful information about training load/fatigue.

HRV in Elite vs. Non Elite Athletes

–          I have a lot of thoughts on this but will reserve comment until I do some more research on this. In short, I think there is a difference in how HRV data should be interpreted among these groups.

HRV in competitive athletes vs. Recreation lifters/athletes

–          HRV guided training (planning higher loads when HRV is at or above baseline and reducing them when HRV is below baseline) is likely safer and possibly more effective over longer term training. However, I don’t see how this method will work with athletes during shorter term training periods. Overload is required followed by a taper. Conversely, if your training results are not limited by requiring optimal performance at a certain date, HRV guided training will likely reduce risk of injury, illness, nagging join/soft tissue problems, etc. Recreational lifters would certainly benefit from this style of training.

Final thoughts for today

To be clear, the above are all simply thoughts/hunches I’ve been having. These are all incomplete at the moment and require further elaboration. Moreover, my stance on many of these topics are subject to change. My thoughts are limited by my experience and the research I’ve read. There is still a lot of work that needs to be done on HRV to uncover its potential as a monitoring tool in athletes.


Chalencon S, Busso T, Lacour J-R, Garet M, Pichot V, et al. (2012) A Model for the Training Effects in Swimming Demonstrates a Strong Relationship between Parasympathetic Activity, Performance and Index of Fatigue. PLoS ONE 7(12): e52636. doi:10.1371/journal.pone.0052636

Chen, J., Yeh, D.,  Lee, J., Chen, C.,  Huang, C.,  Lee, S., Chen, C.,  Kuo, T., Kao, C., & Kuo, C. (2011) Parasympathetic nervous activity mirrors recovery status in weightlifting performance after training. Journal of Strength and Conditioning Research, 25(6):  1546-1552

Di Fronso, S. et al. (2012) Relationship between performance and heart rate variability in amateur basketball players during playoffs. Journal for Sports Sciences & Health, 8 (Suppl 1):S1–S70 45

Edmonds, RC., Sinclair, WH., and Leicht, AS. (2012) The effect of weekly training and a game on heart rate variability in elite youth Rugby League players. Proceedings of the 5th Exercise & Sports Science Australia Conference and 7th Sports Dietitians Australia Update. Research to Practice , 19-21 April 2012, Gold Coast, QLD, Australia , p. 183.

Oliveira, RS. et al. (2012a) Seasonal changes in physical performance and HRV in high level futsal players. International Journal of Sports Medicine. DOI: 10.1055/s-0032-1323720

Thiel, C. et al. (2012) Functional overreaching in preparation training of elite tennis professionals. Journal of Human Kinetics, DOI: 10.2478/v10078-011-0025-x

Reflections, Thoughts & Some HRV Data Analysis from 2 Athletes

This week Carl Valle had a great article posted on Mladen’s site here. It’s definitely worth the read if you train athletes. This article inspired me to reflect on where HRV fits in to training, for whom it may work best for and why. I monitor HRV in a very small number of athletes who are the minority of the overall pool of athletes I work with.

To get the most out of HRV tracking, I believe it should be measured daily, in the morning after waking. With ithlete this requires less than 2 minutes of your time to perform the measurement and make any comments, input training load, etc. Though this is a simple task, it is not easy to get full compliance from individuals. Therefore, I don’t even consider getting an athlete taking measurements unless he possesses a great deal of intrinsic motivation, is responsible, reliable, and perhaps most importantly, is interested. Though I would prefer they know nothing about the device, it’s hard to convince people to commit to using it every day if they don’t understand why. After a few sessions I will mention it to them and give them some basic details. If they appear interested or ask if they can use it then it’s a go.

I have several motivations for tracking HRV in select athletes. Below, these motivations are listed with some follow-up thoughts and elaborations.

  • To observe ANS response to training, daily stressors, recovery modalities, etc.

What was HRV score the day following a workout? What else did the athlete do that day that may influence this score? What has the overall trend been that week (positive or negative)?  I like to compare HRV score to other training status markers like strength levels (did he hit target weights for the day?), movement ability (how does he look during warm-ups, jumps, etc.?), perceived recovery/readiness levels (Does he feel great when HRV is high, when its low?), etc.

This motivation serves two purposes.

  1. It gets the athlete more engaged in his life style and training (more on this in a bit)
  2. It satisfies my curiosity. I’ve got questions I want answered.
  • To observe HRV trends over times of illness, injury, etc. to determine if there were early warning signs in the trend and if the trend reflects recovery/return to play readiness.

In the event of an injury during practice or competition, what was the trend indicating? In the past year or so I hurt myself once during training and it happened with 60% of my 1RM during squats (hardly a threatening situation). My HRV that day was well below baseline. Possibly a coincidence, or possibly injury risk is heightened when HRV is really low. To my knowledge, there is no research on this in human athletes, but this seems to be the case in race horses. I discussed some very interesting research by Dr. Christine Ross in this post from last winter.

Here’s an excerpt from that post.

“Dr. Christine Ross monitored the HRV of 16 competitive race horses, all of which were in training. Of the 16, 13 had HRV readings that were associated with pain, fatigue, illness or injury. It was stated that even though the horses appeared healthy and energetic, they were considered “at risk” based on their HRV. There were no outward signs or symptoms to suggest these horses were currently sick or hurt. Within 3 months, 12 of the 13 at-risk horses got injured or sick requiring veterinary intervention and cessation of race training.”

Furthermore, I work with plenty of football players and hockey players who by nature are at risk of concussion. What insight can HRV provide regarding recovery and return to play after concussion? (Perhaps a post on this in the future)

  • In rare cases, to manipulate training if HRV has been consistently below baseline and the athlete displays signs of fatigue.

This is an interesting topic. Working with an athlete is rarely long term. In many cases you may only have 6-8 straight weeks of consistent training before interruption. That means we need to get them better quickly. Getting better can be defined in many ways but in the training realm this means improving strength, speed, power, work capacity, etc. To do this we need to apply stress. In some cases, a lot of stress, of various kinds. Naturally, HRV will drop. The organism has to work hard to adapt to the stress (and thus improve). We don’t have time to wait for “optimal” recovery and this is likely not even desirable.

Let me use an example. Below is the HRV trend of a 25 year old hockey player I’m working with. He’s come to me to get in shape for a try-out he’s been invited to for a pro team in Germany.


He is a former NCAA hockey player and has been training relatively consistently throughout school. After this summer he thought he was done with competitive hockey and stopped training however he did start playing men’s league hockey.  Since he hasn’t been training I knew we’d probably see some pretty big downward deflections after our first few workouts. He missed a few mornings of HRV measurements but it’s been about 2 weeks since we started. The “week change” is -8 and his HRV trend is steadily decreasing. His strength is steadily improving as is his conditioning. He’s adapting fast and re-acquiring lost strength and fitness. Training loads are steadily increasing every week. Now that it’s Christmas I expect to see his HRV bump back up due to some extra rest and likely extra calorie intake. So long as HRV approaches baseline levels after a few days of rest then I think things are looking good. However, if HRV continues downward I will evaluate performance markers and make adjustments if necessary. The physical stress load is high as reflected by his HRV but it’s only been 2 weeks and his performance markers are improving. The weekly trends will likely continue to decrease until about 2 weeks out from the try-out at which point I’ll steadily reduce loads. HRV should climb back up and fatigue should dissipate. This is what happens when I have a relatively short period of time to work with an athlete.

In contrast, the trend below is of a high school sprinter I’m working with. He trains with his sprint coach and works with me for recovery/restoration, mobility, etc. He has a sub 11s 100m time and is one of the fastest high school sprinters in Canada. He is much more long term and his training load reflects that. His weight training volume has been reduced quite a bit and has transitioned into more sprint work and power development in the weight room (controlled and implemented by his Sprint Coach).

ZW Trend

This is an athlete who takes care of himself and is extremely motivated to get better, to say the least. He reports that training is going well, he’s hitting PR’s and it looks as though he’s handling training almost too well. Higher loads would be likely well tolerated. If I can just start getting him to get to bed at a decent hour on weekends he’ll be doing everything right.

In both cases the athletes have learned how lifestyle factors outside of training effect their recovery, soreness levels, etc. This is directly attributed to seeing their HRV trend, recognizing what events may have caused the additional stress and re-evaluating there decision making. One of the main things I like about HRV is that it forces you (and the athlete) to be more engaged in the process. It allows them to see how their actions (good or bad) can effect the quality of their training and their progress.

Final Thoughts

Having HRV records as an objective measure of training status helps guide the training process when taken with other markers of performance and fatigue. If the athlete is a high level athlete, mature enough to handle daily measurements and wants to use it then I am all for it. I don’t use it with many athletes because it would be a waste of time and energy for both parties. However, with the right athletes it can be a great tool to for monitoring training.

HRV Values: Indications of Training Readiness

In my recent articles on HRV in Team Sports, I discussed the idea of having our athletes report to pre-season camp with favorable autonomic profiles prior to the initiation of intensive training. The goal of this being to enhance adaptation and reduce injury potential. Today I’d like to delve into this topic a little deeper.

First I’d like to review some important research that helped form the basis of this thought process. Other, more intelligent minds thought of this stuff way before I did and have produced what I consider to be, some pretty compelling research.


Vesterinen and colleagues (2011) found that recreational endurance runners who had high baseline HRV levels prior to intensive training improved their performance significantly more than runners who had low baseline HRV levels prior to training.

Oliveira and colleagues (2012) found a strong correlation between parasympathetic indices of HRV (analyzed before training) with the performance improvement in Yo-Yo IR1 in soccer players during pre-season training.

Hedelin and colleagues (2001) set out to investigate relationships between HRV and central and peripheral performance measures in various trained endurance athletes over a 7 month period. The authors reported that; “higher parasympathetic activity, at least in these fit subjects, rather was a cause than an effect of a further increase in aerobic fitness.”

Kiviniemi et al (2007) found that in fit males, training when HRV levels are at baseline or above results in significantly higher improvements in maximum running velocity and greater improvements in vo2 max compared to a group that followed pre-planned training, of which saw insignificant changes in both measures.

In a repeat study Kiviniemi et al (2010) included female groups and found that females take longer to recover from a training session and that fitness can be improved with fewer high intensity training days when guided by HRV compared to the pre-planned training group

Hautala et al (2003) reported that baseline HF Power was the most powerful determinant of future training response in healthy subjects. I strongly urge interested readers to read through this review by Hautala et al (2009) for a thorough discussion on this topic.

I’m certain I’m leaving out some good research but I think you get the idea. There is evidence to suggest that HRV levels can be a good indicator of training response in athletes and fit individuals.


A couple issues I’m having with the evidence as it applies to team sport settings;

  1. HRV measurement is different in much of the research. Some is nocturnal, some is morning, etc. Therefore, we can’t say for certain if we can draw similar conclusions based on a morning measurement if the researchers used nocturnal HRV measurements. Having said that, I do feel that morning measurements are sufficient, if not optimal.
  2. The research mostly pertains to aerobic athletes and aerobic training. However, given that most team sports require a sufficient level of aerobic capacity I still think the discussed research offers valuable information. Even in a sport like American Football, many of the drills are serial and repetitive in nature and thus places a greater dependence on energy production from aerobic metabolism. Further, repeated sprint ability is related to oxygen uptake during rest periods (Dupont et al. 2010).

It appears that having a high level of resting parasympathetic tone prior to intensive training results in more favorable responses and performance improvements in athletes. The research suggests that HRV levels appear to reflect adaptive potential. It should be of high priority to the coaching staff that players remain healthy throughout training. Keeping tabs on HRV levels throughout training, taken with other measures of training status, may reveal maladaptation and therefore a necessitation for intervention.

I’d personally like to see HRV levels monitored in Collegiate American Football players throughout pre-season training camp. It’s conceivable that injury risk is heightened in athletes showing consistent decrements in HRV. It surprises me that there is very little research on HRV and injury (risk, recovery, return to play, etc) in comparison to HRV and performance enhancement/monitoring.

Whether or not we can apply this to strength/power athletes is not clear as there is very little research on this. It’s been a personal goal of mine to investigate this issue and I hope to do this at some point in the future.

Provided that athletes are engaging in training throughout the off-season having a high level of parasympathetic tone at rest shouldn’t be an issue. Team sport athletes will generally have low resting heart rates and a high work capacity. The concern would be with athletes that are either not preparing themselves for intense training, or with those that may be over doing it.

Apart from aiming to have high HRV levels prior to training we may also want to use HRV as an indicator of recovery status day to day. During intense training periods, recovery and restoration modalities can aid in parasympathetic re-activation and therefore more rapid recovery. Paying closer attention to nutritional strategies, active recovery, cold water immersion (a controversial topic at the moment it seems) sleep quality and duration, etc. may help us in maintaining favorable ANS activity; perhaps a topic for another day.


Dupont, G., et al. (2010) Faster oxygen uptake kinetics during recovery is related to better repeated sprint ability. European Journal of Applied Physiology, (110)3: 627-34

Hautala, A.J., et al. (2003) Cardiovascular autonomic function correlates with the response to aerobic training in healthy sedentary subjects. American Journal of Heart & Circulatory Physiology, 285(5): H1747–52.

Hautala AJ, et al. (2009)Individual responses to aerobicexercise: the role of the autonomicnervous system. Neuroscience & Biobehavioral  Reviews, 33(2): 107–115.

Hedelin, R. et al. (2001) Heart Rate Variability in athletes: relationship with central and peripheral performance. Medicine & Science in Sports & Exercise, 33(8), 1394-1398.

Kiviniemi, A.M., Hautala, A., Kinnumen, H., & Tulppo, M. (2007) Endurance training guided by daily heart rate variability measurements. European Journal of Applied Physiology, 101: 743-751.

Kiviniemi, A.M., Hautala A.J., Kinnunen, H., Nissila, J., Virtanen, P., Karjalainen, J., & Tulppo, M.P. (2010) Daily exercise prescription on the basis of HR variability among men and women. Medicine & Science in Sport & Exercise, 42(7): 1355-1363.

Oliveira, RS. et al. (2012b) The correlation between heart rate variability and improvement in soccer player’s physical performance. Brazilian Journal of Kinanthropometry, 14(6)

Vesterinen, V. et al. (2011) Heart rate variability in prediction of individual adaptation to endurance training in recreational endurance athletes. Scandinavian Journal of Medicine & Science in Sports, DOI: 10.1111/j.1600-0838.2011.01365.x

HRV Monitoring in a Team Setting: The Research

Though my original interest in HRV monitoring was for personal usage with my powerlifting training (and still is), I have become much more interested in its application with my athletes. In July, I wrote a post discussing some of the research and my thoughts on HRV in a team setting. I’ve come across some more great research that pertains to HRV monitoring in team settings and would like to share some thoughts on the topic.

Below is a  list of questions I’d like to address:

  • How effective is HRV monitoring in a team setting really?
  • What difference is there, if any, when monitoring HRV in elite vs. sub-elite athletes?
  • How practical is HRV monitoring in a team setting?
  • Can we create favorable autonomic profiles in athletes prior to intensive training blocks to improve global (all players) responsiveness to training? (to avoid injury, overtraining, etc)
  • How can we apply research that used frequency domain measures (HF, LF, HF/LF) with mobile apps/devices like ithlete and Bioforce that use RMSSD, a time domain measure of parasympathetic tone?

Keep in mind that I do not train elite athletes and therefore much of what I discuss is based on my interpretations of the research, discussions I’ve had with others and some theory. I certainly am not capable of providing answers to any of the above question.

First, I’d like to present brief summaries of the research I’ve read on the topic. I’ve only included studies that used HRV to monitor fatigue, training load, etc. At this time I’m not including studies using HRV during exercise, or post-exercise.

In some cases I could not get access to the full-text which you will see noted in the respective tables. Please enlighten me of any research on this topic I may have not included. I apologize for the poor presentation of the table’s below. I originally had all of this in a more reader friendly format in Word but for some reason it does not transfer over to wordpress very well.

Author Ke-Tien (2012)
Sport Male, National Level Rugby (n=24)
Aim To verify biological and psychological stress markers during strenuous cardiovascular endurance training periodization, using Profile of Mood States questionnaires, HRV & blood urine nitrogen as the criteria measurements.
Main Findings HRV correlated to profile of mood states survey and blood-urnine nitrogen in elite male national rugby players (n=24).
HRV Analysis Non-daily, Frequency Domain
Author Edmonds et al. (2012)
Sport Male, Elite Youth Rugby (n=9)
Aim To investigate the influence of weekly training & a competitive game on HRV in elite youth rugby league players, & to identify the importance of HRV as a monitoring tool for Rugby League player preparation.
Main Findings Prior to a match, elite youth, players exhibited a significant reduction in HRV that was sustained for at least 24 hours post-game. This withdrawal of parasympathetic &/or increased sympathetic control of HR possibly may result from pre-match anxiety as well as the physical demands of the game. Strong relationships between HRV and training load at Pre-2 indicate that early monitoring may assist in identifying training workloads for the upcoming week.
HRV Analysis Daily, Time & Frequency Domain
Author Oliveira et al. (2012a)  – Abstract Only
Sport Male, Elite Futsal (n=11)
Aim The aim of this study was to determine the changes in physical performance and resting heart rate variability (HRV) in professional futsal players during the pre-season and in-season training periods.
Main Findings Players improved their RSA & Yo-Yo IR1 performance with concomitant improvements in HRV. These indices were maintained during the in-season period while RSAbest was improved & RSAdecrement impaired. Frequent monitoring of these performances and HRV indices may assist with identification of individual training adaptations and/or early signs of maladaption.
HRV Analysis Non-daily, Unknown
Author Vantinnen et al. (2007)
Sport Male, Elite Soccer (n=24)
Aim To introduce a method commonly used in Finnish sport to monitor the exercise intensity & changes in recovery state of players in team sports by examining their heart rate (HR/HRV) responses to training & relaxation stimulus.
Main Findings Individual differences do exist in practices & games. This would imply that coaches need to quantify each game or practice exercise intensity & recovery for each individual, in order to organize & optimally prepare an individual training plan for each athlete.
HRV Analysis Various over 3 weeks (daily, nocturnal, 24 hr), Time and Frequency Domain
Author Oliveira et al. (2012b) – Abstract Only
Sport Male, Caliber Unknown, Soccer (n=10
Aim The aim of this study was to analyze whether the heart rate variability (HRV), assessed at the beginning of a soccer preseason, reveals a correlation with the improvement of physical performance over this training period.
Main Findings There were significant improvements in Yo-Yo IR1 performance & in the 30-m sprint time. The qualitative analysis revealed that the differences in Yo-Yo IR1 performance were very likely positive, were almost certainly positive for the sprint, but were inconclusive for the vertical jump. There was a strong correlation between one parasympathetic index and the change in performance. The study showed a strong correlation between parasympathetic indices of HRV with the performance improvement in Yo-Yo IR1 in the athletes during pre-season.
HRV Analysis Non-daily, Unknown
Author Rodas, G. et al. (2011) – Abstract Only
Sport Elite, Field Hockey (n=? entire team)
Aim To determine the changes in HRV during the 2006 World Cup
Main Findings HRV decreases progressively & the values of the parameters related to parasympathetic system activity (RMSSD & HF) reduce, which are indicative of good psychic-physical adaptability to the workload. At the same time, the value of the parameters related to sympathetic system activity (LF and LF/HF) increases, suggesting an increase in fatigue, tiredness and poor adaptability in general. Consequently, the analysis of HRV may be a good marker for monitoring the psychic-physical state, cardiovascular adaptability during exercise & a possible state of physical overload in athletes participating in competitions.
HRV Analysis Day of competitions only – Time and Frequency Domain
Author Martin-Sanchez et al. (2011)
Sport Male Pro Soccer (n=12) & Age/Sex matched Amateur Soccer (n=9)
Aim To determine if an intensive preseason training program modifies the inflammatory status in professional soccer players and if this inflammatory profile may be associated with the physical state.
Main Findings A negative association between cardiac low frequency & the plasma content of alpha-1 antichymotrypsin isotype 4, & a positive association between cardiac low frequency & fibrinogen gamma-chain isotype 3 was found. Our results suggest that the cardiac functional state of soccer players may be correlated with these proteins. Pro soccer players showed a decreased content of circulating proteins associated with inflammation compared with those in recreational soccer players.
HRV Analysis Morning of analysis – Time and Frequency Domain
Author Cipryan et al. (2010)
Sport Male, Hockey Junior Level (n=8), Adult (N=10)
Aim To present inter-individual differences in the reaction of autonomic nervous system (ANS) activity to the same training program, and to thereby support the importance of individual training in team sports during the conditioning period.
Main Findings The SA HRV monitoring mostly revealed significant differences in the level of the ANS activity among the players. A number of junior & adult players were characterized by almost permanently high ANS activity whereas other players occurred below the ANS activity level of healthy individuals.  The training efficiency (overreaching and injury reduction) can be positively influenced by creating training groups of players with similar ANS activity.
HRV Analysis Non-daily – Frequency Domain
Author Cipryan et al. (2007)
Sport Male, U-18 National Level Hockey (n=4)
Aim To investigate the influence of regular sport training on the activity of the autonomicnervous system (ANS) and to disclose patterns of interrelations between them.
Main Findings The results demonstrated that the player with the highest average TS (total score)& the highest average PT(total power) also showed the most consistent results & objectively the best performance in sport. On the other hand, the player with the lowest average TS and the lowest average PT also obtained the lowest average mark in the coach’s evaluation of his sports performance. The tendency to progression of the ANS  activity was different for each subject. The self-reports health status survey, which was given before measurements were taken, did not correspond with the results of the SA HRV measurement.
HRV Analysis Non-daily, Frequency Domain
Author Hap et al. (2010)
Sport Male, High Level Volleyball (n=8)
Aim The goal of the work was to verify the possibility of volleyball playersʼ training load optimization during a one week training microcycle based on the longitudinal observation of dynamics of SA HRV complex indices.
Main Findings 2 Players had above average levels ANS activity indicating higher training loads could be tolerated.4 Players had low ANS activity (but not below average) showing evidence of some fatigue and adaptation. Training loads are appropriate.

2 Players had below average ANS activity and their training adaptability was reduced.

HRV Analysis Daily – Frequency Domain
Author Parrado et al. (2010) – Abstract Only
Sport Elite, Field Hockey (n=? entire team)
Aim The aim of the study was to examine the utility of perceived tiredness to predict cardiac autonomic response to overload among feld hockey players during the 2006 World Cup.
Main Findings Results showed a negative correlation between perceived tiredness scores & time domain indexes, & a positive correlation of perceived tiredness scores and the high frequency component ratio (LF/HF ratio) of heart rate variability. Anxiety did not influence the precompetitive cardiac response despite somatic anxiety’s correlation with sympathetic response (LF/HF ratio) & tiredness scores. Perceived tiredness predicted the autonomic cardiac response to competitive overload. Thus, the perceived tiredness assessment would be a good early marker of fatigue & overload states during competition
HRV Analysis Day of analysis, Frequency Domain
Author Mazon et al. (2011)
Sport Male, Volleyball (n=32)
Aim To investigate the effects of selective loads of periodization model (SLPM) on autonomic modulation of HRV and endogenous stress markers before and after a competition period in volleyball players.
Main Findings SLPM did not change the cardiac autonomic modulation of HRV, but promoted beneficial adaptations in athletes, including positive changes in the plasma concentration of the endogenous stress markers. The absence of changes in HRV indicates that there is no direct relationship between cardiac autonomic modulation & endogenous stress markers in the present study.
HRV Analysis Pre & Post Training Cycle, Frequency Domain
Author Di Fronso et al. (2012)  – Abstract On
Sport Male, Amateur Basketball (n=7)
Aim To investigate the relationship between Heart Rate Variability (HRV) and performance in players of a basketball team during playoffs.
Main Findings Findings of this study suggest that vagal activity, expressed by HF index of HRV, can be positively related to the athletes’ performance. In particular, higher values of HF index during the morning of the match were associated with higher levels of athletes’ performance during the game.
HRV Analysis Morning of Competitions – Frequency Domain
Author Dranitsin (2008)
Sport Elite Male (n=12) and Female (n=1) Rowers
Aim The aim of this study was to examine the simultaneous effect on HRV of acclimatization to a hot, humid environment and a transition of five time zones in elite junior rowers.
Main Findings Major physiological adaptation of HRV indices in the standing position during acclimatization to a humid, hot environment, with a transition across five time zones, occurs within the first 5 days in elite athletes before returning to baseline. Indices of heart rate variability in the supine position correlate with the length of high-intensity training sessions on the previous day.
HRV Analysis Daily, Time Domain
Author Iellamo et al. (2004)
Sport Elite Male Rowers (n=8)
Aim To test the hypothesis that training-induced variations in T-wave amplitude at higher training loads are paralleled by changes in HR spectral profile.
Main Findings From 50% to 100% of training load, there was a significant decrease in HRV and increase in sympathetic tone. As training reduced to 50% during the World Championships, HRV returned to base line and a return of autonomic indices to previous levels was seen. 
HRV Analysis Non-Daily – Frequency Domain

I’ll discuss my thoughts on the questions I listed above in my next post.

Please share any studies pertaining to HRV usage in a team setting that I may have missed in the comments below or e-mail me

I joined twitter recently too @andrew_flatt


Cipryan, L. & Stejskal, P. (2010) Individual training in team sports based on ANS activity assessments. Medicina Sportiva, 14(2):  56-62 Free Full-Text

Cipryan, L., Stejskal, P., Bartakova, O., Botek, M., Cipryanova, H., Jakubec, A., Petr, M., & Řehova, I. (2007)  Autonomic nervous system observation through the use of spectral analysis of heart rate variability in ice hockey players.  Acta Universitatis Palackianae Olomucensis. Gymnica, 37(4): 17-21. Free Full-Text

Di Fronso, S. et al. (2012) Relationship between performance and heart rate variability in amateur basketball players during playoffs. Journal for Sports Sciences & Health, 8 (Suppl 1):S1–S70 45

Dranitsin, O. (2008) The effect on heart rate variability of acclimatization to a humid, hot environment after a transition across five time zones in elite junior rowers. European Journal of Sport Science, 8(5): 251-258 Abstract

Edmonds, RC., Sinclair, WH., and Leicht, AS. (2012) Theeffect of weekly training and a game on heart rate variability in elite youth Rugby League players. Proceedings of the 5th Exercise & Sports Science Australia Conference and 7th Sports Dietitians Australia Update. 5th Exercise & Sports Science Australia Conference and 7th Sports Dietitians Australia Update Research to Practice , 19-21 April 2012, Gold Coast, QLD, Australia , p. 183. Abstract

Hap, P., Stejskal, P. & Jakubec, A. (2010) Volleyball players training intensity monitoring through the use of spectral analysis of HRV during a training microcycle. Acta Universitatis Palackianae Olomucensis. Gymnica, 41(3): 33-38 Free Full-Text

Iellamo, F., Pigozzi, F., Spataro, A., Lucini, D., & Pagani, M. (2004) T-wave and heart rate variability changes to assess training in world class athletes. Medicine & Science in Sports and Exercise, 36(8): 1342-1346. Abstract

Ke-Tien, Y.(2012) Effects of Cardiovascular Endurance Training Periodization on Aerobic performance and Stress Modulation in Rugby Athletes. Life Science Journal, 9(2): 1218-25. Full-Text

Martin-Sanchez, F. (2011) Functional status and inflammation after preseason training program in professional and recreational soccer players: a proteomic approach. Journal of Sports Science & Medicine, 10: 45-51 Free Full-Text

Mazon, J. et al. (2011) Effects of training periodization on cardiac autonomic modulation and endogenous stress markers in volleyball players. Scandinavian Journal of Medicine & Science in Sports, doi: 10.1111/j.1600-0838.2011.01357.x Free Full-Text

Oliveira, RS. et al. (2012a) Seasonal changes in physical performance and HRV in high level futsal players. International Journal of Sports Medicine. DOI: 10.1055/s-0032-1323720 Abstract

Oliveira, RS. et al. (2012b) The correlation between heart rate variability and improvement in soccer player’s physical performance. Brazilian Journal of Kinanthropometry, 14(6) Abstract

Parrado, E.  et al. (2010)Percieved tiredness and HRV in relation to overload during a field hockey world cup. Perceptual and Motor Skills, 110(3): 699-713 Abstract

Rodas, G. et al. (2011) Changes in HRV in field hockey players during the 2006 World Cup. Apunts Medicina de l’Esport, (46): 117-123 Abstract

Vantinnen, T. et al. (2007) Practical experiences from measuring exercise intensity and recovery state with HR monitoring in team sport. Symposium Proceedings 6th IACSS Calgary, Alberta. Full-Text