The rate at which we recover during intra and post workout is a vital component when monitoring performance, both health and sport. Monitoring your heart rate via a monitor, such as Polar or Garmin, is a popular and fairly accurate tool (to hand) to be used by individuals to consistently check their heart’s beats per minute (BPM) status.
If we explore the physiology, our heart is controlled sub-consciously by two very sophisticated and adaptable parts of the autonomic nervous system; Sympathetic, which is a regulator for increasing the heart’s functionality and Parasympathetic, which regulates the decreases in the heart’s functionality. It has been suggested that monitoring the response of the autonomic nervous system may prove to be a useful monitoring tool to ascertain functional adaptations to an individual’s physiology when a training stimulus is applied, especially when this is cardiovascular centred.
Specific to endurance based athletes, it is typical for individuals to demonstrate low resting heart rates (RHR) in a recovered state i.e. 24 hours after exercise or upon wake. RHR values at 60 bpm or below demonstrate a condition called Bradycardia, which is the ability of an adult’s heart to beat under 60bpm at rest. In some cases it is common for individuals to dip under 50 bpm, however this would be demonstrated in well-trained individuals or athletes. This would suggest that an individual’s parasympathetic nervous system has had a positive response to a training stimulus. Traditionally, RHR would be used as a key indicator to monitor and asses an individual’s heart health and fitness status and this is further discussed by Matt Robert’s Senior Trainer Rob Aiken – his article can be found here. Nonetheless, the emergence of using heart rate recovery time as a barometer of cardiovascular fitness is becoming increasingly popular as a basic training modality within an individual’s programme.
So what exactly is the heart rate recovery (HRR) terminology? HRR can be simply defined as the heart’s ability to return to a baseline BPM, specific to the individual’s physiological status, during an intra or post-session recovery period. To create a baseline for your HRR, you simply apply the following equation:
HRR = 220 – age of individual x between 50% (beginner) to 60% (advance/elite)
220 – 25 x 0.5 = 98bpm
Dr Larry Creswell explains how to monitor correctly an individual’s efficiency in HRR; within the first minute after a bout of sub-maximal exercise typically the heart rate should drop between 15 to 20 bpm, however any values that dip under 12 bpm would be adverse. Nevertheless the use of HRR, in a subjective clinical setting, can be a useful predictor for changes and assessments cardiovascular health and (in some instances) mortality.
If we investigate this scientifically, researched performed by Lamberts et al. (2009) have explored the use of HRR within elite cyclists to examine whether its use as a performance indicator is necessary in an endurance athlete’s physiology portfolio. Elite cyclists went through a standardised test of 8 High Intensity Training (HIT) sessions in a 4 week period. The authors found that HRR, post time trials performed, improved significantly along with relative peak power (W-kg-1) (Lamberts et al., 2009). Therefore, the study established that the use of HRR monitoring can be a successful and non-invasive monitoring agent, providing it is used in a controlled training protocol, which applied correctly can potential assist in fine tuning an individual’s training during a training cycle (Lamberts et al., 2009).
Furthermore, an investigation carried out by Lamberts and associates (2010) examined the use of HRR to determine a relationship between cycling performance and HRR time during a HIT protocol. The study found that HRR responded positively to training stimuli, conversely this mainly correlates to recently applied training loads in an exercise protocol. Therefore the use of HRR can be used a useful physiological parameter or guide to detect potential under-recovery/overtraining, positive physiological training adaptations and intra/post training fatigue (Lamberts et al., 2010).
Using the information above, here are some examples in how we can apply this information to a training programme:
Example Programme #1: Sub-maximal
- Start at 70% of HRMax
- Hold for 2-3 minutes
- Recover until BPM drops to 50%
- Repeat with 3-5% increments until 85% HRMax. is reached and perform 3-5 sets at 85%
Example Programme #2: High Intensity Training (HIT) and Biofeedback
Before I provide Example Programme #2, let me clarify what Biofeedback exactly is (Zaichkowski & Fuchs, 1988)*. In its simplest form, it is the ability to control and manipulate one’s physiological responses or motor control by applying psychological stimuluses’/techniques for a desired outcome, in this instance controlling the parasympathetic nervous system. This can be done by applying a verbal cue or phrase that simultaneously matches the same rhythm as an individual’s RHR, repeated over a 60 second window. Focussing on the cue or phase will engage in more effective and faster HRR. Let’s put this into a practical example using a Tabata method:
- Gentle warm-up of mobility circuit, skipping or running allowing the HR to creep up to the desired training zone (85-95% HRMax.)
- Perform mountain climbers or plyometric step-ups and work up to hitting consistently 85-90% of your HR training zone (depending on health and fitness level) and hold for 60 seconds.
- 60 second recovery using the chosen biofeedback cue aiming to get to your RHR.
- Once RHR is reached, repeat as many times as you have prescribed until RHR is unable to drop in sufficient time.
* For more in information, please read Daniel Bishop’s article on Training for Heart Rate Recovery.
- Lamberts RP, Swart J, Noakes TD, Lambert MI. Changes in heart rate recovery after high intensity training in well-trained cyclists. European Journal of Applied Physiology, 2009: 5; 705-713
- Lamberts RP, Swart J, Capostagno B, Noakes TD, Lambert MI. Heart rate recovery as a guide to monitor fatigue and predict changes in performance parameters. Scandinavian Journal of Medicine and Science in Sports 2010: 20; 449-457