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Tuesday 1 October 2019

Heart rate variability – How can we use this to determine recovery?



Hello and welcome to another post on Strength is Never a Weakness Blog. 


This is a special one all about Heart Rate Variability 


Please give a warm welcome to the newest content creator at Strength is Never a Weakness, Mr Alec Ward! 


This is Alec's first post on the blog and it is a great one! 


We hope you all enjoy it 


Leave your comments below 


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What is heart rate variability?


The heart is a specialised pump that functions by regular and continuous contractions for delivery of oxygenated blood throughout the body (Boudalas et al., 2014). Heart rate (HR) is the number of heart beats per minute (BPM). Heart rate variability (HRV) is the fluctuation in the time intervals between these heartbeats (Shaffer and Ginsberg, 2017). These changes in time intervals are dependent on the environment and the physiological state one’s body may be in (MCcraty and Shaffer, 2015). At rest it is a favourable to have a high HRV, whereas when exercising it may be favourable to have a low HRV. A high HRV means the variability between adjacent heartbeats is high (spread out across a long variability of time). A low HRV means heartbeats are rather constant. Low HRV at rest has been shown to be a predictor of coronary heart disease (CHD) and mortality (Dekker et al. 2000).



                        
                             


Fig 1.  The science and application of heart rate variability (https://hrvcourse.com/heart-rate-variability-vs-heart-rate/)


The autonomic nervous system - what role does it play?

HRV has proved to be a simple, useful and non-invasive method for analysing the autonomic mechanisms through the measurement of continuous beat-to-beat variations (Amano et al., 2001). The understanding of the significance of HRV is still ongoing. However, it has been suggested that HRV is an important method for assessing cardiovascular autonomic parameters that are partially under the regulatory control of the sympathetic (fight or flight) and parasympathetic (rest) systems (Hemingway et al., 2015).











Reliability and Validity

Heart rate variability has been found to be a valuable measure in a variety of sports settings with the measurement of many factors including overtraining, recovery, endurance training, and exercise (Makivić, Djordjevic and Willis, 2013). HRV has been shown to decrease with age due to a decrease in vagal tone, produced by the vagus nerve (Ogliari et al., 2015). The vagus nerve regulates many bodily functions at rest under sub-conscious control (Heart rate, vasodilation, vasoconstriction, breathing etc…). However, exercise has been shown to reverse this and increase HRV (An increase in HRV means our bodies are responding well to the accumulated stimulus placed upon it). HRV is a potentially powerful method as a basic scientific tool for better understanding the regulation and control of the cardiovascular system. From a practical point of view 10-15 years ago it remained to be determined if it can also be used as a predictor of athletic condition (Aubert, Seps and Becker, 2003). However, new research has found that HRV guided training could be a good method to use to increase peak power in well-trained cyclists (Javaloyes et al. 2019).





What does the new research say?

New research conducted by Javaloyes et al. (2019) was conducted in the Sport Research Centre of Miguel Hernandez University in Alicante, Spain and the University of Stellenbosch in South Africa.
Seventeen well-trained cyclists were recruited for this study and the point of the study was to determine whether HRV could enhance the prescription of training load vs a traditional periodisation group.


Layout of the study

  1. Evaluation week
  2. 4 Baseline weeks (common)
  3. Evaluation week
  4. 8 Training weeks (HRV guided/Traditional)
  5. Evaluation week


HRV was measured by the cyclists at home every morning with a Polar H7 chest strap, and the heartbeat data was analysed by the researchers using lab software. From this, a 7-day moving average of HRV was calculated. During the four baseline weeks, participants performed about eight hours of training per week, during which the mean and standard deviation of the HRV measurements were calculated for each cyclist. This produced thresholds for the HRV-guided training weeks that followed.


HRV Group

During the 8-week training phase an algorithm used in a previous study conducted by Kiviniemi et al. (2007) on endurance runners was used. The daily guide was slightly altered to allow for splits between low intensity, threshold and HIIT days. The overall outcome of days ended up being in the split of 66/24/10 in the low, moderate and high intensity zones. A big difference between this and previous research was the fact that the HRV group were prescribed training based on a 7 day moving average


Periodisation Group

The group that performed the standard planned periodisation training schedule ended up training in a similar split (64/27/9). However, the plan was a fixed rotation and did not change according to HRV on given days. The average training time per week for each groups was 9 hours per day.



Major Findings

The HRV group increased their peak power, VT2 power and power over 40 mins by 5%, 14% and 7% whereas the periodisation group hardly increased their peak power and power over 40 mins by anything at all. These new findings could be exciting for potential practical implications for the future of athlete monitoring.



Practical implications and tips for coaches wanting to use this method

1.      7 day moving average – Watch out for changes in the 7 day moving average of HRV. If it decreases then lowering the intensity of training could be a good idea.
2.      Daily readings – Use daily readings to ensure consistency in the results and to see the changes in HRV frequently
3.      Morning readings – Ensure readings are taken in the morning before the athlete (or yourself) has consumed food or caffeine as these can stimulate the ANS to trigger misguided results
4.      Avoid keeping training the same all the time – Do not just stick to the same training because the 7-day moving average of HRV stays high. Introduce variation to avoid monotony of the athlete.





Fig 3. https://www.pinterest.co.uk/pin/320600067202573820/




How do I calculate my heart rate variability?

1.       Buy a heart rate monitor There are a few chest straps (e.g. Polar and Wahoo) and finger pulse sensors (e.g. Ithlete) that have been shown to be sufficiently accurate.
2.       There are many apps on smartphones that can be utilised to measure HRV (Apple health, OURA, HRV4Train, Elite HRV, Ithlete). However, not all have been validated in peer reviewed studies therefore I would recommend using ithlete.
3.       Run an evaluation week on what you want to improve on
4.       A baseline average should be recorded initially over the course of 4-6 weeks, once you have a baseline with your normal training stimulus you can adjust your training accordingly to results
5.      Devise an 8-10 week training schedule and adjust weeks accordingly to HRV
6.      Run another evaluation week to see if improvements have been made


Is measuring HRV expensive?

An average polar HR monitor costs on average £80-100 depending on the model and size of which one you purchase. Ithlete HRV app costs £7.99 and another well renowned app called elite HRV costs £4.99 to purchase for full use to them. For daily measurements of HRV you are looking at around £85-£110 of initial payment which in my opinion is not too expensive for an investment into your holistic health and performance.


Alternatives to HRV

Subjective athlete readiness scores

Subjective athlete readiness scores have been shown to be a valid measurement of acute and chronic fatigue in a recent systematic review conducted by Saw, Main and Gastin (2016). Wellness questionnaire are simply a questionnaire given to the athlete for them to rate how they feel. This will often cover a range of topics such as how they slept the previous night, their current stress-level, body soreness, and how tired they feel (Rushall, 1990). The list of questions, and the structure of the questionnaire, is commonly designed by the coach based on what they feel is most important factors in  their athletes life. For example, a coach working with  athletes that are in education may choose to include questions regarding educational workload, as this is known to impose a certain degree of stress and limit physical adaptations (Bartholomew et al. 2008). However, if you are a coach working with elite, older athletes the need for a question like this is not necessary allowing it to be withdrawn from the questionnaire.










Rating of fatigue scale

The rating of fatigue scale (ROF) has recently been showing to be a good measure of fatigue and has good convergent validity (Micklewright et al. 2017). This study was performed using cycling exhaustion and compared ROF against physiological measures (subjective) and an objective measure of fatigue, rating of perceived exertion (RPE). High convergence was found between ROF and several physiological measures of fatigue (HR, Blood lactate concentration, oxygen uptake, carbon dioxide production, respiratory exchange ratio and ventilation rate). ROF and RPE correlated in the exhaustion trial but not in the recovery stage, This demonstrated discriminant validity. ROF is done through an 11-point Likert scale with diagrammatic selections. This two-part system seems to make the rating easier for participants and, therefore, provides a more accurate way of determining perceived fatigue levels. ROF appears to have high levels of both convergent and discriminant validity making it a useful tool in monitoring an athletes fatigue levels during a training session and allowing for programs to be altered accordingly.


Conclusion


To conclude, the new findings on HRV are very interesting and open up a big window for further research into this growing area. Further research should look at whether or not HRV is a valid measure on elite and recreational athletes as the recent research only indicates that it can improve power in well-trained athletes. No recent studies to current knowledge have looked at whether or not HRV can be used to determine the response to resistance training in elite or recreational athletes, therefore this needs to be validified before recommendations can be created. I believe that if you are looking to improve performance and want a subjective measure to do so, HRV could be a very useful tool for you to use. It can be an indicator to you for holistic health and could allow you to subjectively choose which days can be of higher intensities in your training schedule, and which days you need to back off slightly to ensure we do not over train.


Authors Details

Alec Ward

Contact Number - 07453278459





References

1.       Amano, M., Kanda, Tomo., Ue, Hidetoshi. and Moritani, Toshio., (2001). “Exercise training and autonomic nervous system activity in obese individuals”. Medicine and science in sports and exercise, 33(8), pp.1287-1291.
2.       Aubert, A.E., Seps, B. and Beckers, F., 2003. Heart rate variability in athletes. Sports medicine, 33(12), pp.889-919.
3.       Bartholomew, J.B., Stults-Kolehmainen, M.A., Elrod, C.C. and Todd, J.S., (2008). “Strength gains after resistance training: the effect of stressful, negative life events”. The Journal of Strength & Conditioning Research, 22(4), pp.1215-1221.
4.       Buccelletti, E., Gilardi, E.M.A.N., Scaini, E., Galiuto, L.E.O.N., Persiani, R.O.B.E., Biondi, A.L.B.E., Basile, F.L.O.R. and Silveri, N.G., 2009. Heart rate variability and myocardial infarction: systematic literature review and metanalysis. Eur Rev Med Pharmacol Sci, 13(4), pp.299-307.
5.       Dekker, J.M., Crow, R.S., Folsom, A.R., Hannan, P.J., Liao, D., Swenne, C.A. and Schouten, E.G., (2000). “Low heart rate variability in a 2-minute rhythm strip predicts risk of coronary heart disease and mortality from several causes: the ARIC Study”. Circulation, 102(11), pp.1239-1244.
6.       Hemingway, H., Shipley, M., Brunner, E., Britton, A., Malik, M. and Marmot, M., (2005). “Does autonomic function link social position to coronary risk?” The Whitehall II study. Circulation, 111(23), pp.3071-3077.
7.       Javaloyes, A., Sarabia, J.M., Lamberts, R.P. and Moya-Ramon, M., 2019. Training Prescription Guided by Heart-Rate Variability in Cycling. International journal of sports physiology and performance, 14(1), pp.23-32.
8.       Javaloyes, A., Sarabia, J.M., Lamberts, R.P., Plews, D. and Moya-Ramon, M., 2019. Training Prescription Guided by Heart Rate Variability Vs. Block Periodization in Well-Trained Cyclists. Journal of strength and conditioning research.
9.       Kiviniemi, A.M., Hautala, A.J., Kinnunen, H. and Tulppo, M.P., 2007. Endurance training guided individually by daily heart rate variability measurements. European journal of applied physiology, 101(6), pp.743-751.
10.   Makivić, B., Nikić Djordjević, M. and Willis, M.S., (2013). “Heart Rate Variability (HRV) as a tool for diagnostic and monitoring performance in sport and physical activities”. Journal of Exercise Physiology Online, 16(3).
11.   McCraty, R. and Shaffer, F., (2015). “Heart rate variability: new perspectives on physiological mechanisms, assessment of self-regulatory capacity, and health risk”. Global advances in health and medicine, 4(1), pp.46-61.
12.   Micklewright, D., Gibson, A.S.C., Gladwell, V. and Al Salman, A., (2017). “Development and validity of the rating-of-fatigue scale”. Sports Medicine, 47(11), pp.2375-2393.
13.   Munoz, M.L., van Roon, A., Riese, H., Thio, C., Oostenbroek, E., Westrik, I., de Geus, E.J., Gansevoort, R., Lefrandt, J., Nolte, I.M. and Snieder, H., (2015). “Validity of (ultra-) short recordings for heart rate variability measurements”. PLoS One, 10(9), p.e0138921.
14.   Ogliari, G., Mahinrad, S., Stott, D.J., Jukema, J.W., Mooijaart, S.P., Macfarlane, P.W., Clark, E.N., Kearney, P.M., Westendorp, R.G., de Craen, A.J. and Sabayan, B., (2015). “Resting heart rate, heart rate variability and functional decline in old age”. Cmaj, 187(15), pp.E442-E449.
15.   Rushall, B.S., (1990). “A tool for measuring stress tolerance in elite athletes”. Journal of Applied Sport Psychology, 2(1), pp.51-66.
16.   Saw, A.E., Main, L.C. and Gastin, P.B., (2016). “Monitoring the athlete training response: subjective self-reported measures trump commonly used objective measures”: a systematic review. Br J Sports Med, 50(5), pp.281-291.
17.   Shaffer, F. and Ginsberg, J.P., (2017). “An overview of heart rate variability metrics and norms. Frontiers in public health”, 5, p.258.





 Andrew Richardson, Founder of Strength is Never a Weakness Blog





















I have a BSc (Hons) in Applied Sport Science and a Merit in my MSc in Sport and Exercise Science and I passed my PGCE at Teesside University. 
Now I will be commencing my PhD into "Investigating Sedentary Lifestyles of the Tees Valley" this October 2019. 

I am employed by Teesside University Sport and WellBeing Department as a PT/Fitness Instructor.  


My long term goal is to become a Sport Science and/or Sport and Exercise Lecturer. I am also keen to contribute to academia via continued research in a quest for new knowledge.


My most recent publications: 


My passion is for Sport Science which has led to additional interests incorporating Sports Psychology, Body Dysmorphia, AAS, Doping and Strength and Conditioning. 
Within these respective fields, I have a passion for Strength Training, Fitness Testing, Periodisation and Tapering. 
I write for numerous websites across the UK and Ireland including my own blog Strength is Never a Weakness. 
























I had my own business for providing training plans for teams and athletes. 
I was one of the Irish National Coaches for Powerlifting, and have attained two 3rd places at the first World University Championships, 
in Belarus in July 2016.Feel free to email me or call me as I am always looking for the next challenge. 



Contact details below; 

Facebook: Andrew Richardson (search for)

Facebook Page: @StrengthisNeveraWeakness

Twitter: @arichie17 

Instagram: @arichiepowerlifting

Snapchat: @andypowerlifter 

Email: a.s.richardson@tees.ac.uk

Linkedin: https://www.linkedin.com/in/andrew-richardson-b0039278 



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