Abstract
rt rate variability (HRV) is defined as the fluctuation of time intervals between adjacent heartbeats and is commonly used as a surrogate measure of autonomic function. HRV has become an increasingly measured variable by wearable technology for use in fitness and sport applications. However, with its increased use, a gap has arisen between the research and the application of this technology in strength and conditioning. The goal of this narrative literature review is to discuss current evidence and propose preliminary guidelines regarding the application of HRV in strength and conditioning. A literature review was conducted searching for HRV and strength and conditioning, aiming to focus on studies with time-domain measurements. Studies suggest that HRV is a helpful metric to assess training status, adaptability, and recovery after a training program. Although reduced HRV may be a sign of overreaching and/or overtraining syndrome, it may not be a sensitive marker in aerobic-trained athletes and therefore has different utilities for different athletic populations. There is likely utility to HRV-guided programming compared to predefined programming
suggest that HRV is a helpful metric to assess training status, adaptability, and recovery after a training program. Although reduced HRV may be a sign of overreaching and/or overtraining syndrome, it may not be a sensitive marker in aerobic-trained athletes and therefore has different utilities for different athletic populations. There is likely utility to HRV-guided programming compared to predefined programming in several types of training. Evidence-based preliminary guidelines for the application of HRV in strength and conditioning are discussed. This is an evolving area of research, and more data are needed to evaluate the best practices for applying HRV in strength and conditioning. Keywords:HRV-guided training; overtraining; training adaptations; training prescription 1. Introduction Sport and exercise scientists are increasing their efforts to quantify and monitor ath- letes’ psychophysiological loads (e.g., training, psychological, and environmental) to op- timize training adaptations. A promising inexpensive, time-efficient, and non-invasive method for monitoring athlete load is heart rate variability (HRV) [1,2]. HRV is defined as the fluctuation of time intervals between adjacent heartbeats (R-R intervals or inter-beat intervals (IBIs)) [1,3,4]. HRV is typically used as a surrogate measure of the autonomic balance of the sympathetic and parasympathetic nervous systems [1,3–6]. A normal heart has fluctuations in IBIs both at its baseline and in response to stimuli [4,5]. Although a core aspect of cardiac regulation is the pacemaker cells of the sinoatrial node, the heart rhythm is modulated by the autonomic nervous system (ANS) which receives feedback from baroreceptors and chemoreceptors from multiple blood vessels, information which is integrated in the medulla [5]. Given the regulatory role of the ANS as well as other top-down cortical processes augmenting the ANS response, HRV has been shown to be a helpful indicator of overall health of an individual [5,6]. A more in-depth review of the physiological mechanisms of HRV can be found in the work of Shaffer and colleagues [5]. While HRV has been measured and used in research applications as early as the 1970s, HRV J. Funct. Morphol. Kinesiol.2024,9, 93.
A more in-depth review of the physiological mechanisms of HRV can be found in the work of Shaffer and colleagues [5]. While HRV has been measured and used in research applications as early as the 1970s, HRV J. Funct. Morphol. Kinesiol.2024,9, 93.
J. Funct. Morphol. Kinesiol.2024,9, 93 2 of 14 has become an increasingly measured variable by wearable technology for use in fitness and sport applications [1,3,4]. HRV has shown promise as a tool for athlete monitoring and fitness or sport program modulation [7,8]. Additionally, HRV has become more accessible for sports science and sports performance professionals through the use of wearable devices. It is becoming increasingly important for strength and conditioning coaches, sports scientists, and sports medicine experts to be knowledgeable about how HRV should and should not be applied in their respective scopes of practice. While other reviews have evaluated the applica- tion of HRV in sports physiology [1,3,9], new data in the last 5–10 years prompt further comprehensive discussion. Lundstrom and colleagues discussed HRV’s application in endurance athletes and provided some preliminary recommendations for the literature [2]. While this is clearly beneficial, this may not fully reflect the training of athletes in which they incorporate both resistance and endurance training to maximize performance out- comes. Therefore, it is important to synthesize the current research on (a) the effects of resistance training on HRV, (b) the ability of HRV to assess physiological stress in response to resistance training, and (c) the use of HRV-guided resistance training. Furthermore, there is a lack of research connecting the effective utilization of HRV to guide training, specifically with strength training or combined modalities of strength and conditioning. No prior review has included multiple disciplines within strength and conditioning to create guidelines for the implementation of HRV. We provide preliminary guidelines to push HRV research forward and increase the standardized implementation of HRV in sports and fitness.Primary Aim:The current review proposes evidenced-based preliminary guidelines for the implementation of HRV in the practice of strength and conditioning and the expansion of the associated HRV literature. 2. Methods A literature review was conducted to address and contextualize the current state of time-domain measures of HRV in strength and conditioning. PubMed and Scopus databases were utilized with the keywords “heart rate variability”, “strength”, “condi- tioning”, “overreaching”, “overtraining”, and “HRV-guided training”. Inclusion criteria included original research and review papers
conditioning and the expansion of the associated HRV literature. 2. Methods A literature review was conducted to address and contextualize the current state of time-domain measures of HRV in strength and conditioning. PubMed and Scopus databases were utilized with the keywords “heart rate variability”, “strength”, “condi- tioning”, “overreaching”, “overtraining”, and “HRV-guided training”. Inclusion criteria included original research and review papers that discussed HRV, specifically time-domain- based measures, and its applications in the practice of strength and conditioning. Exclusion criteria included case reports and papers that did not include time-domain-based measures. 3. Heart Rate Variability Measurement HRV is regulated by the ANS. The standard methods of analysis of HRV fall into the time and frequency domains [3,4]. Time-domain metrics assess the difference between normal R-R intervals (NN), excluding ectopic beats. The time domain has been preferred in the field of strength and conditioning due to its stability and ability to be defined in short durations [10]. The most common time-domain units of measurement include the root mean square of the differences in successive R-R intervals (RMSSD), the standard deviation of NN intervals (SDNN), and the percentage of normal R-R intervals that differ by 50 ms (pNN50) [1,4]. The RMSSD time domain is commonly log-transformed for ease of interpretation by users [4]. RMSSD is preferred because it is more sensitive and less affected by respiratory rate, heart rate, or recording duration [1]. Other time-domain units, such as SDNN, must be standardized to a certain recording length to control for variance of HRV. This is very important with the increasing number of devices in the market that use various forms of HRV as metrics, as they cannot always be directly compared [11]. Several methodological approaches have been used to assess HRV including body position (i.e., supine, seated, and standing) and recording duration (i.e., 1, 5, and 7 min). A 5 min recording duration is recommended in the clinical setting [4], while ultra-short readings (i.e., 1 min) have been used with athletes [12], given their time constraints. Regardless of the position or measurement duration, consistency in measurement time and methodology is of foremost importance.
position (i.e., supine, seated, and standing) and recording duration (i.e., 1, 5, and 7 min). A 5 min recording duration is recommended in the clinical setting [4], while ultra-short readings (i.e., 1 min) have been used with athletes [12], given their time constraints. Regardless of the position or measurement duration, consistency in measurement time and methodology is of foremost importance.
J. Funct. Morphol. Kinesiol.2024,9, 93 3 of 14 Frequency-domain methods allow for the distinction between high-frequency (HF) and low-frequency (LF) components. HF components (between 0.14 and 0.40 Hz) re- flect the activity of the parasympathetic nervous system, while LF components (between 0.04 and 0.15 Hz) are generally accepted to reflect the activity of the sympathetic nervous system during longer recordings [10]. Examples of HF include respiration, and therefore respiratory sinus arrhythmia (this is how the respiratory rate can be back-calculated from the heart rate) are governed by vagal (parasympathetic) tones. LF signals that represent sympathetic tone include baroreflex activity and thermoregulation [13], and these require interpretive caution during short-term recordings (less than 24 h recordings) [5]. The ratio of HF/LF can assess the relationship between sympathetic and parasympathetic activity. Notably, frequency-domain measurements are confounded by respiration, which must be accounted for during the standardization of these metrics [14]. Frequency-domain measures are typically utilized to look at autonomic balance (parasympathetic withdrawal and/or sympathetic dominance). However, this has yet to be widely utilized in the strength and conditioning literature. Importantly, HRV has no standardized range as of the current research, meaning there is no agreed upon normal value [4]. Normative ranges exist [15] but cannot be applied with cutoff values for ease of interpretability, especially with an athlete population. Therefore, the terms “higher” or “lower” are all relative to an individual’s baseline HRV. A high HRV relative to baseline represents a healthy, flexible autonomic system and improved adaptability and recovery in response to a changing environment or stressor, such as travel or exercise [1,3,16]. A low HRV relative to baseline represents an imbalanced autonomic function, typically due to a withdrawal of the parasympathetic system, resulting in a sympathetic-dominant state associated with increased inflammation and a greater potential for a cardiac event [1,3,17]. Regardless of high or low HRV, stability of HRV around an individual’s baseline within the smallest worthwhile change window (SWC) is typically considered a long-term goal of training. An SWC has previously been defined as±0.5 or 1 standard deviations from an individual’s chosen HRV metric [18–21] (Figure).J. Funct. Morphol. Kinesiol.
inflammation and a greater potential for a cardiac event [1,3,17]. Regardless of high or low HRV, stability of HRV around an individual’s baseline within the smallest worthwhile change window (SWC) is typically considered a long-term goal of training. An SWC has previously been defined as±0.5 or 1 standard deviations from an individual’s chosen HRV metric [18–21] (Figure).J. Funct. Morphol. Kinesiol. 2024, 9, x FOR PEER REVIEW 3 of 14 of the position or measurement duration, consistency in measurement time and method- ology is of foremost importance. Frequency-domain methods allow for the distinction between high-frequency (HF) and low-frequency (LF) components. HF components (between 0.14 and 0.40 Hz) reflect the activity of the parasympathetic nervous system, while LF components (between 0.04 and 0.15 Hz) are generally accepted to reflect the activity of the sympathetic nervous sys- tem during longer recordings [10]. Examples of HF include respiration, and therefore res- piratory sinus arrhythmia (this is how the respiratory rate can be back-calculated from the heart rate) are governed by vagal (parasympathetic) tones. LF signals that represent sym- pathetic tone include baroreflex activity and thermoregulation [13], and these require in- terpretive caution during short-term recordings (less than 24 h recordings) [5]. The ratio of HF/LF can assess the relationship between sympathetic and parasympathetic activity. Notably, frequency-domain measurements are confounded by respiration, which must be accounted for during the standardization of these metrics [14]. Frequency-domain measures are typically utilized to look at autonomic balance (parasympathetic withdrawal and/or sympathetic dominance). However, this has yet to be widely utilized in the strength and conditioning literature. Importantly, HRV has no standardized range as of the current research, meaning there is no agreed upon normal value [4]. Normative ranges exist [15] but cannot be ap- plied with cutoff values for ease of interpretability, especially with an athlete population. Therefore, the terms “higher” or “lower” are all relative to an individual’s baseline HRV. A high HRV relative to baseline represents a healthy, flexible autonomic system and im- proved adaptability and recovery in response to a changing environment or stressor, such as travel or exercise [1,3,16]. A low HRV relative to
for ease of interpretability, especially with an athlete population. Therefore, the terms “higher” or “lower” are all relative to an individual’s baseline HRV. A high HRV relative to baseline represents a healthy, flexible autonomic system and im- proved adaptability and recovery in response to a changing environment or stressor, such as travel or exercise [1,3,16]. A low HRV relative to baseline represents an imbalanced autonomic function, typically due to a withdrawal of the parasympathetic system, result- ing in a sympathetic-dominant state associated with increased inflammation and a greater potential for a cardiac event [1,3,17]. Regardless of high or low HRV, stability of HRV around an individual’s baseline within the smallest worthwhile change window (SWC) is typically considered a long-term goal of training. An SWC has previously been defined as ±0.5 or 1 standard deviations from an individual’s chosen HRV metric [18–21] (Figure 1). Figure 1. Visualization of a rolling 7-day average along with rolling smallest worthwhile changes (SWCs) visualized from unpublished data. Measurement Considerations The gold standard of measurement of HRV is through an electrocardiogram (ECG) [3,4]. However, many commercially available wearable devices measure HRV through photoplethysmography (PPG) [22] and heart rate sensors. PPG measurements can be trusted when a healthy individual is at rest [23], but physical or mental stress causes HRV metrics to meaningfully disagree with each other when comparing PPG sensors to the gold-standard ECG [22]. PPG may also become unreliable at heart rates greater than 160 Figure 1.Visualization of a rolling 7-day average along with rolling smallest worthwhile changes (SWCs) visualized from unpublished data. Measurement Considerations The gold standard of measurement of HRV is through an electrocardiogram (ECG) [3,4]. However, many commercially available wearable devices measure HRV through photo- plethysmography (PPG) [22] and heart rate sensors. PPG measurements can be trusted when a healthy individual is at rest [23], but physical or mental stress causes HRV metrics to meaningfully disagree with each other when comparing PPG sensors to the gold-standard ECG [22]. PPG may also become unreliable at heart rates greater than 160 BPM and with significant motion (particularly with wrist-worn devices), making interpretation during difficult
PPG measurements can be trusted when a healthy individual is at rest [23], but physical or mental stress causes HRV metrics to meaningfully disagree with each other when comparing PPG sensors to the gold-standard ECG [22]. PPG may also become unreliable at heart rates greater than 160 BPM and with significant motion (particularly with wrist-worn devices), making interpretation during difficult workouts have limited utility. Furthermore, evidence exists showing that PPG
J. Funct. Morphol. Kinesiol.2024,9, 93 4 of 14 accuracy is dependent on skin tone, with darker-skinned individuals having larger variabil- ities than lighter-skinned individuals [24]. Therefore, utilizing PPG for HRV monitoring in strength and conditioning should only be applied if utilization of ECG or heart rate sensors is impractical. Whether choosing to use PPG- or ECG-based devices, practitioners should prioritize internal consistency by utilizing the same device for all measurements. Measurements of HRV are typically performed at rest, post-exercise, or continuously throughout the day or during exercise. Furthermore, HRV can be measured in various positions, including supine, seated, standing, or with orthostatic testing. Given that autonomic control of the cardiovascular system is moderated by several inputs detecting physiological changes [1], contextual factors such as period length, detection method, sampling frequency, removal of artifacts, body positioning, and respiration should be controlled when monitoring HRV, regardless of the method or metrics used [4]. Most importantly, HRV metrics provide limited utility during exercise given the sympathetic activation and parasympathetic withdrawal, preventing the intended measurement of autonomic balance. Therefore, most commercially available wearable devices monitor HRV during slow-wave (deep) sleep to minimize noise in the signal that is common when awake and moving [4]. Other wearable devices measure HRV immediately upon waking, standardizing the HRV measurement to exclude external stimuli (i.e., activities that would increase or decrease heart rate) without requiring devices to estimate sleep phases [4]. The key feature is standardization in the methodology of HRV measurement for each device, so it is internally consistent for the individual, and addressing the physiological or clinical question that is being investigated. A full discussion of the benefits and deficits of various HRV measurement techniques is outside of the current review’s scope but should be considered in future work. HRV is non-invasive, easy to measure, and can be measured daily without physical exertion. Therefore, it can be applied widely and cheaply. Other physiologic measures of physical fitness, such as VO2 max or maximum strength testing, require experienced practitioners and additional equipment, and are unreasonable to be used for testing on a normative basis. HRV should be
in future work. HRV is non-invasive, easy to measure, and can be measured daily without physical exertion. Therefore, it can be applied widely and cheaply. Other physiologic measures of physical fitness, such as VO2 max or maximum strength testing, require experienced practitioners and additional equipment, and are unreasonable to be used for testing on a normative basis. HRV should be considered in addition to the other established perfor- mance metrics rather than in isolation [1]. 4. Heart Rate Variability and Training Adaptations 4.1. Aerobic/Endurance-Trained Athletes Several studies have identified that night-time RMSSD can significantly increase following training programs [25,26] in endurance athletes, including runners [26–28], cyclists [29], swimmers [30,31], and endurance walkers [32]. Furthermore, RMSSD has been correlated with an increase in training adaptations such as VO2 max, max running velocity, and timed-trial performance in this population [26,27]. There is also evidence that increased baseline HRV may be a reliable marker of training status or training age and that a delayed return to baseline HRV may be associated with reduced training age and/or adaptability in response to training [28,33]. 4.2. Strength/Resistance-Trained Athletes HRV measures and their associations with training adaptations in strength and high- intensity interval training have not been studied extensively. However, there is likely a correlation between HRV and adaptations to strength-based training [34]. No studies were found that investigated the association of HRV with maximum strength gains, rate of force development, critical torque, critical power, or cross-sectional area after a training program. Furthermore, no studies were found that investigated the changes in HRV associated with different forms of resistance training, such as Olympic weightlifting, powerlifting, and multimodal resistance training, or different resistance training intensities or durations. Given the limited research discussing training adaptations specific to resistance training and their connection to HRV, HRV should be interpreted on an individual basis in strength- based athletes [35].
Description
This narrative review discusses HRV applications in strength and conditioning.