The concept of Heart Rate Variability (HRV) refers to the variance that exists between consecutive heart beats. Under normal circumstances, a heart rate of 60 beats-per-minute (bpm) does not necessarily mean that the heart is beating exactly every single second. Instead, a certain level of variability exists between consecutive heart beats, with beats coming closer or further apart over time. The level of variability encountered is controlled by the Autonomic Nervous System (ANS), which is in charge of maintaining overall body homeostasis, and its two main branches: the Sympathetic Nervous System (SNS) and the Parasympathetic Nervous System (PNS).
The SNS is also known as the fight-or-flight branch. When active, it sets the body in an optimal physiological state to cope with stressful situations by increasing heart rate (and reducing heart rate variability), enhancing contraction force, improving blood flow to the muscles, and secreting adrenaline and glucocorticoid hormones. These metabolic changes prime your body to successfully react to perceived dangers. For example, think about being chased by a stranger and how you may suddenly feel a rush that makes you run faster and further than ever; that is the SNS in action. The sympathetic system is also activated to some degree when you are exposed to daily life stresses such as work, family matters, exams, exercise, etc.
The PNS is known as the resting-and-digesting branch of the ANS. When active (in the absence of stress) the body carries on repair process that helps it adapt to stress during the day. The PNS will tend to reduce heart rate (increasing heart rate variability), increase digestion of nutrients, and enhance repair processes of body tissues, such as muscle, damaged during the stress response.
When we train, the ANS activates the SNS to create the necessary physiological changes to successfully cope with the training. Ideally, some time after training, the ANS will shut down the SNS and activate the PNS to start the repair processes of the damaged tissues, thus starting the adaptation process. Having the appropriate level of recovery before the next training session is crucial to ensure optimal performance and successful future adaptations. When there is an imbalance between training and recovery, the level of SNS activity will be higher (lower HRV), indicating the need for more rest and the introduction of recovery strategies.
Measuring HRV provides a non-invasive way to look at the body’s ANS activity and can determine whether an person is in a state of overtraining or in an optimal state to train. It can also reflect previous week’s training by looking at trends in your HRV: e.g., a gradual upward or downward trends. It can also serve as a good indicator of how well you cope with daily life stresses other than training and that may be affecting your training performance.
The research on HRV is promising. Recent research by Edmonds (2013) examined the effect of weekly training and competition on HRV in nine youth rugby players. Heart rate measurements were taken supine and standing 5 times over an 8-day period. Relationships between HRV and workload, via analysis of rate of perceived exertion, were statistically analyzed. Results showed a correlation between HRV and training workload. Higher heart rate and lower parasympathetic activity (reduced HRV) prior to competition and during the following days were attributed to pre-game stress and the gradual increase in workload experienced during training sessions. The authors suggested that day-to-day measurements of HRV may help monitor a player workload to maximize training and game performance.
Another study by Chen (2011) aimed to determine whether HRV measurements accurately reflected recovery status after weight training. Following a 10-day detraining period, 7 weightlifters performed a strenuous 2 hour-long training session. Weightlifting performance and HRV were analyzed 3, 24, 48, and 72 hours after training to determine the level of recovery. Results showed a decreased performance and suppressed parasympathetic response (lower HRV) immediately following training. Parasympathetic activity and lifting performance returned to baseline levels after 24 hours of recovery, and further increased above baseline in the following 48-72 hours of recovery. The authors concluded that the parasympathetic state indicated through HRV measurements accurately reflected recovery status as well as potential training performance and adaptation.
In order to see training improvements, a certain level of training stress is necessary for the body to adapt. However, it is imperative that there is enough quality recovery time to let the body carry out the physiological and metabolic adjustments, leading to improved sport performance. Measuring HRV may be a good way to keep track of training workloads, identify trends with respect to ANS activity, and make sure you are recovering from those tough workouts to keep on making progress.
References:
Chen JL, Yeh DP, Lee JP, Chen C,Y Huang CY, Lee SD, Chen CC, Kuo TB, Kao CL, Kuo CH. (2011). Parasympathetic nervous activity mirrors recovery status in weightlifting performance after training. Journal of Strength and Conditioning Research. 25(6), 1546-1552.
Edmonds RC, Sinclair WH, Leicht AS. (2013). Effect of a Training Week on Heart Rate Variability in Elite Youth Rugby League Players. Int J Sports Med. [Epub ahead of print].
Marieb, E. N., & Hoehn, K. (2010). Human Anatomy and Physiology. New York, NY: Benjamin Cummings; 8th edition.








Trainings, in order to be successful, needs time and recovery. If recovery is not monitored following exercise, fatigue may accumulate and become excessive prior to competition, resulting in reduced athletic performance and, potentially, overtraining syndrome. In its essence, overtraining syndrome is characterized by a combination of excessive overload in training stress and inadequate recovery, leading to fatigue and decreased. Recovery is also essential in hacking flow state. C Wilson Meloncelli website(https://www.cwilsonmeloncelli.com/) talks more about flow state and how to achieved it. Check it out.