Reliability of HRV

Heart rate variability (HRV) has received extensive attention as a non-invasive indicator of autonomic nervous system activity and cardiovascular health (Tiwari, Kuma, Malik, Roj,& Kumar, 2021). It is commonly utilized in clinical settings, athletic training, and psychological research to assess stress, recovery, and overall well-being. Despite its popularity, the reliability of HRV as a measurement tool is questionable. Various factors contribute to the unreliability of HRV, including inconsistencies in measurement, individual variability, and the influence of external factors.

One of the main sources of unreliability in HRV measurement is the inconsistency in data collection methods. HRV can be assessed using various tools, including electrocardiograms (ECG), photoplethysmography (PPG ) devices, and the ubiquitous wearable fitness trackers. While ECG is considered the gold standard due to its precision, PPG-based devices, often used in wearables, are prone to inaccuracies as well. These devices may be affected by movement, poor sensor contact, and environmental conditions, leading to erroneous readings. The differences in measurement techniques and the sensitivity of devices to artifacts can result in significant variability in HRV readings, making it difficult to draw consistent conclusions from the data. Likewise, the time of day and the duration of the measurement can significantly impact HRV results. HRV tends to vary throughout the day due to natural circadian rhythms. Morning measurements may yield different results compared to those taken in the evening. Short measurement periods may not capture the full spectrum of HRV fluctuations (Shaffer, Meehan, & Zerr, 2020), while longer measurements can be influenced by external factors such as physical activity, mental stress, or even digestion (Damoun, Amekran, Talek, & El Hangouche, 2024). As a result, comparisons between studies or even within individuals over time can be challenging, further undermining the reliability of HRV as a consistent marker.

 Heart rate variability (HRV) is a highly individualized physiological factor, with considerable disparities observed among individuals. Factors such as age, gender (Voss, Schroeder, Peters, & Perez, 2015), fitness level (Souza, Philbois, Veiga, & Aguilar, 2021), and genetic predispositions (Golosheykin, Grant, Novak, Heath, & Anokhin, 2017) can all influence baseline HRV levels. For instance, younger individuals generally exhibit higher HRV compared to older adults, due to differences in autonomic nervous system function. Similarly, athletes tend to have higher HRV as a result of enhanced parasympathetic activity (Kiss et al., 2016). These individual differences imply that HRV cannot be interpreted in a universal manner, and comparisons between individuals may not be meaningful without considering these personal factors. Furthermore, individual variability in HRV can also be influenced by psychological states such as stress, anxiety, and depression (Kim, Cheon, Bai, Lee, & Koo,, 2018). However, the relationship between these factors and HRV is not straightforward. Some individuals may show significant decreases in HRV in response to stress, while others may exhibit minimal changes. This variability makes it challenging to use HRV as a reliable indicator of psychological well-being across different populations or even within the same individual over time.

External factors, including caffeine intake, alcohol consumption, and sleep quality, can all have an impact on HRV readings. For instance, caffeine (Koenig, et al., 2013) and alcohol (Ralevski, Petrakis, & Altemus, 2019) can stimulate the sympathetic nervous system, which may result in a temporary decrease in HRV. Poor sleep quality or sleep deprivation can also decrease HRV, reflecting the body's impaired ability to recover and regulate autonomic function (de Estrela, McGrath, Booij, & Gouin, 2021). These external factors introduce additional variability into HRV measurements, making it difficult to distinguish the effects of the variable of interest from these confounding factors. Environmental conditions, such as temperature and altitude, can also affect HRV (Sun et al., 2024). For example, high altitudes can result in increased HRV as the body adapts to lower oxygen levels (Schmitt et al., 2008). However, these environmental factors are often not controlled for in HRV studies, which can lead to potential misinterpretations of the data.

In sum, HRV has shown promising potential for tracking autonomic nervous system activity and promoting health and wellness monitoring. However, its reliability as a measurement tool is undermined by several factors. Variations in data collection methods, individual differences, and the influence of external factors collectively compromise the dependability of HRV readings. Consequently, it is essential to exercise caution when interpreting HRV data and not rely solely on it to gauge physiological or psychological states. Future research should concentrate on standardizing measurement protocols and devising more robust methods to account for individual and environmental variability to enhance the reliability of HRV as a valuable biomarker. HRV is a complex and multifactorial phenomenon that requires careful consideration of individual differences and contextual factors to be interpreted accurately.