Episode Transcript
[00:00:00] Welcome friends, to the Heart Rate Variability Podcast. This week in Heart Rate Variability Edition, each week we explore the latest research and news from the world of hrv. Before we begin, please remember that the information in this podcast is for informational and educational purposes only and should not be taken as medical advice. Always consult with your healthcare provider or a qualified professional before applying any strategies discussed here. Today we have a full lineup of nine studies that give us new insights into heart rate variability, stress physiology, autonomic regulation, and how our environments and technologies interact with our nervous systems. As always, my goal is to translate these findings into meaningful guidance for clinicians, mental health providers, researchers, and anyone curious about the science of regulation and resilience. We'll take each study one at a time, walking through the publication, the authors, the findings, and what it all means for those of you working with clients, patients or research participants. We begin with a study published in Scientific Reports titled Light Guided Resonant Breathing Enhances Psychophysiological Stress Recovery in a Simulated Office Environment by Kanazai, Glinser, Stagl, Drayson, Weninger, and Vice. This study stands out because it examines the immediate effects of resonant breathing guided by a light protocol in an office like setting. The authors recruited 80 university students and exposed them to two stressors, a modified cold pressure test and an 18 minute paced serial addition task. These stressors were designed to elicit both physical and cognitive stress responses. What is especially interesting about this paper is how precisely the authors measured stress responses. They used interbeat interval data to extract HRV metrics, including RMSSD and heart rate across each stage of the experiment. Resonant breathing was personalized to each participant's optimal breathing rate, which was identified before the stress induction. Participants breathed using a visual pacemaker built from LED strips arranged alongside a computer monitor guiding the inhale and exhale cycles. Across both stress tests, the resident breathing condition significantly increased RMSSD during recovery compared to passive rest.
[00:01:51] This effect emerged quickly and showed large effect sizes. Subjective strain also decreased following cognitive stress under the resonant breathing condition. Of importance for workplace wellness and behavioral health is how enjoyment ratings differed. Participants rated the resonant breathing experience as more enjoyable than passive rest and perceived it as more effective. This study reinforces two practical ideas. First, resident breathing continues to show substantial immediate benefits in stress recovery even in short sessions lasting only minutes.
[00:02:16] Second, pairing breathing practice with technology supported cues can be not only effective but also engaging for users. This is particularly relevant for clinicians who rely on brief interventions, telehealth, or remote monitoring tools. The more pleasant and intuitive the practice, the more likely clients are to engage with it outside of a clinical setting. Our second study keeps us in the world of stress physiology but shifts toward anticipatory stress. Also published in Scientific Reports, the study is titled Measures of the Psychophysiological Response to Recurrent Anticipatory Stress the Influence of Neuroticism on Heart Rhythm and Skin Resistance by Wagenblast, Seibed, Rieger, and Steinhelber. This exploratory study is a deep dive into how people respond to repeated anticipatory stress when they expect a potential painful electric shock. The researchers divided participants into groups based on neuroticism scores drawn from the Big 5 inventory. Participants completed three sequential conditions, first anticipating a neutral audio signal, second anticipating an electric shock, and third, anticipating another electric shock. During these expectation phases, the authors measured heart rate, hrv, and skin resistance. One of the most intriguing findings of this study is that some physiological markers responded robustly under both electric shock conditions, signaling sustained autonomic activation across repeated anticipatory periods. Skin resistance levels and skin resistance response values increased under both shock conditions compared to the neutral condition. Specific HRV parameters, particularly low frequency power, also increased during anticipation of the shock. A notable nuance emerged in the high neuroticism group. In this group, only the mean heart rate increased significantly during the first shock condition, the but this effect disappeared in the second shock condition. This tells us that individuals with high neuroticism may exhibit a distinct autonomic startle pattern during repeated anticipatory stress. The finding raises questions about habituation, stress appraisal, and autonomic rigidity for clinicians. This study highlights that anticipatory stress is not limited to situations such as public speaking or social interactions. It shows up in smaller everyday predictions of discomfort or threat, and those high in neuroticism may react more strongly. Notably, some physiological markers remain elevated across repeated exposures, signaling that individuals may not fully habituate. When designing HRV assessments or biofeedback interventions, clinicians should consider how repeated anticipatory cues shape autonomic responses. Our third study moves us beyond psychological threat into the growing world of immersive technology.
[00:04:27] Published in the journal Technologies, the paper titled Impact of Stereoscopic Technologies on Heart Rate Variability in Extreme VR Gaming Conditions by Lebomovsky and Gosponova, this study is a fascinating journey into how different stereoscopic devices influence autonomic physiology. During intense virtual reality gaming, the authors evaluated five groups using various display a control group with no stereoscopy, anaglyph glasses, passive glasses, active glasses and VR helmets. They assessed HRV using both time domain and frequency domain metrics, including mean RR, SD, NN, RM, SSD, PNN, 50, LF, HF, and the LF to HF ratio. The results were evident. Devices that created deeper immersion produced more substant physiological load. Active polarized glasses and VR helmets significantly reduced SDNN and rmssd, with VR helmets showing the most significant decrease. The authors reported a considerable drop in mean RR and RMSSD under VR helmet conditions, indicating increased heart rate and diminished parasympathetic activity and AGLIF glasses, by contrast, showed milder effects and the control group showed the least physiological load. The study also applied nonlinear HRV measures and found that greater immersion was associated with lower entropy, suggesting reduced complexity in heart rate dynamics. This is important because reduced HRV complexity often signals autonomic inflexibility in cognitive or emotional strain. For clinicians working with younger populations, gamers, or clients who use VR for therapy or exercise, this study underscores that immersive VR is not a neutral stimulus. Depending on the stereoscopic technology used, VR can substantially increase physiological load, which can be either therapeutic or counterproductive depending on client goals. Understanding how different forms of VR affect the autonomic nervous system can guide safer and more effective implementation of VR based interventions. Our fourth study takes us into the realm of data science and mental health prediction. This paper examines adaptive long window pre processing as a method to reduce artifacts in HRV data for personalized psychosis prediction. While technical, the study speaks directly to one of the central challenges in HRV ensuring the accuracy and reliability of HRV metrics. Psychosis prediction models often rely on continuous physiological monitoring, but real world data is noisy motion artifacts, environmental interference, and sensor inconsistencies can significantly distort intervene interval data. The authors evaluated an adaptive pre processing technique that uses longer time windows to stabilize HRV calculations, particularly in the presence of artifacts. Their findings showed that adaptive pre processing significantly reduced distortions in HRV metrics, allowing for more reliable predictions of psychosis risk. Longer windows help smooth short term irregularities without obscuring meaningful physiological changes. This has broad implications beyond psychosis research. Any clinician or researcher using wearable HRV sensors could benefit from more stable pre processing methods, especially when working with clients who move frequently during monitoring. I want to thank this week's podcast sponsor. This Week in HRV is brought to you by Optimal hrv. Optimal HRV is offering digital gift cards and discounts to make it easier for clinicians, coaches, and organizations to access tools for tracking and improving heart rate variability These gift cards can be a great way to offer clients continued support or to incorporate new team members into your HRV monitoring ecosystem. This is an excellent opportunity to expand the reach of HRV informed care within your practice or program. With that, we'll shift gears and explore our fifth study, a comprehensive review published in the Lancet titled which Antidepressants Shift Physiology? By Pillenger and colleagues. This study offers a sweeping analysis of how different antidepressants influence weight, blood pressure, heart rate and other metabolic markers. Drawing on over 150 randomized controlled trials and 17 FDA reports, the authors compared the physiological effects of 30 antidepressants. Heart rate responses varied Nortriptyline increased heart rate by nearly 14 beats per minute, while fluvoxamine lowered it by more than eight beats per minute. Systolic blood pressure increased with several medications, including amitriptyline and venlafaxine, with mean increases ranging from about 2 to almost 5 millimeters of mercury. Meanwhile, nortriptyline reduced systolic pressure. This study is a crucial reminder that antidepressant medications can influence autonomic and metabolic function in varied ways. For clinicians using HRV to understand client physiology, these drug effects matter. A decrease in HRV or an increase in heart rate might reflect a medication side effect rather than a change in psychological state. Integrating medication awareness into HRV interpretation is essential for accurate clinical decision making. Our sixth study brings us back to more controlled experimental physiology. Published in Scientific Reports. The study, titled A Controlled Comparative Study on the Effect of Arterial Occlusion and Pressure on Immediate Sympathetic and Hyperemic Responses by Trzerbolski, Kristof, Meraki, Minkowski, Olanishin, and Wilk examines how different levels of arterial occlusion pressure influence autonomic and microcirculatory responses. The author studied 30 healthy adults exposed to four levels of arterial occlusion 40%, 80%, 100%, and 130%. They measured resting flow biological zero peak hyperemia, time to peak average NN interval, the ratio of low frequency to high frequency power and heart rate. The findings revealed that while resting flow did not differ significantly across pressure levels, nearly every other measure did. Higher arterial occlusion levels led to more pronounced sympathetic activation and stronger hyperemic responses, but responses tended to plateau between 100% and 130% pressure. Similarly, SDNN and average NN interval shifted with pressure levels, but beyond a certain threshold the responses stabilized. This study is valuable for both sports science and clinical rehabilitation.
[00:09:44] Blood flow restriction training has gained popularity and understanding how autonomic and microcirculatory responses change with varying occlusion levels can help make these interventions safer for clinicians monitoring HRV during exercise or rehabilitation. Understanding how occlusion pressures influence autonomic balance can help accurately interpret in session HRV fluctuations. Our seventh study comes from the journal General Psychiatry. It is titled Heart Rate Variability as a Predictor of Mental Health. A cross sectional analysis by Chen, Li, Jang, Wang, and Zhou. The authors recruited individuals across a broad spectrum of psychological distress ranging from mild symptoms to clinically significant presentations. They collected high resolution HRV data using ECG based interbeat interval recordings. They paired these measures with validated mental health scales assessing depression, anxiety, emotional regulation, cognitive burden, and perceived stress. The authors examine RMSSD, SD HF Power, LF Power, and the LF HF ratio as indicators of autonomic balance. Lower RMSSD and HF power emerged as the strongest predictors of elevated psychological distress, indicating diminished parasympathetic activity among individuals exhibiting mood and anxiety symptoms. Participants who reported rumination, intrusive thoughts, difficulty downshifting after stress, or chronic worry consistently demonstrated lower parasympathetic modulation.
[00:10:56] One notable finding was the strong association between SDNN and overall quality of life scores. Individuals with lower autonomic flexibility tended to report reduced well being and greater emotional volatility. The study argues that HRV may serve as both a biomarker of current distress and a marker of resilience capacity for clinicians. These results reinforce the importance of using HRV not simply as a physiological metric but as a window into emotional functioning. Our eighth study, titled Heart Rate Variability Monitoring in Clinical System Level, Benefits and Challenges, was published in the journal Healthcare and authored by Rossi, Fernandez, Kumar, Patel, and Anderson. This study provides a comprehensive overview of how HRV is used across medical systems to enhance clinical care. The authors drew from observational data sets, case reviews, inpatient telemetry, and outpatient wearable monitoring programs to map the role of HRV in predicting physiological decline. They identified several patterns. First, postoperative HRV monitoring often revealed decreases in parasympathetic activity hours before clinical deterioration became visible, particularly in cardiac and pulmonary patients. Second, chronic disease management programs benefited from tracking HRV trends over time. Patients with heart failure, diabetes, and chronic lung disease demonstrated characteristic HRV shifts that informed medication changes, behavioral recommendations, and risk assessments. Third, in emergency settings, HRV markers supported triage decisions by helping clinicians differentiate between autonomic instability and benign presentations. The authors also highlighted challenges including the need for reliable sensors, consistent measurement protocols, and adequate clinician training for practitioners. This research reinforces that HRV is becoming a meaningful clinical signal across disciplines and that thoughtful implementation can improve early detection and patient outcomes. Our ninth and final study returns us to scientific reports. The article titled Distinct Autonomic Recovery Profiles following Physical and Cognitive Stressors by Novak, Steiner, Mueller, and Hartmann used validated laboratory stress protocols to map autonomic activation and recovery patterns across different stress conditions. Participants completed both a physical stress task and a cognitive stress task, while ECG sensors captured beat to beat intervals. The authors analyzed rmssd, hf, power time, varying heart rate patterns, and recovery curves to compare differences between the two stressors. Physical stress generated rapid sympathetic activation with sharp increases in heart rate and decreases in hrv, followed by a delayed but strong parasympathetic rebound during recovery. Cognitive stress, on the other hand, produced a slower buildup of autonomic arousal and a flatter, more prolonged recovery trajectory, indicating sustained cognitive load. The study also examined individual differences in autonomic responsiveness. Participants with higher baseline HRV recovered more efficiently from both stressors, suggesting stronger autonomic resilience. Those with lower baseline HRV showed slower recovery and prolonged sympathetic activation. These results emphasize that not all stressors are physiologically equivalent and that HRV provides a sensitive metric for differentiating stressor types and tailoring recovery strategies. It was published in the journal Healthcare and is titled Heart Rate Variability Monitoring in Clinical System Level Benefits and Challenges by Rossi, Fernandez, Kumar, Patel, and Anderson. This study offers a broad view of how HRV is being used across medical settings, from critical care units to outpatient monitoring programs. The authors review cases and data from multiple clinical environments to understand how HRV can serve as an early warning biomarker for physiological instability.
[00:14:08] Their analysis highlighted several key areas where HRV improves clinical decision making. First, post operative monitoring declines in HRV often preceded observable clinical deterioration, offering a window for early intervention. Second, chronic disease management patients with heart failure, diabetes, and pulmonary disorders exhibited predictable HRV patterns that helped guide individualized treatment plans. Third, acute care HRV tracking supported risk stratification in emergency settings, especially among patients presenting with non specific symptoms such as dizziness or chest discomfort. The study also acknowledged real world challenges, including the need for reliable artifact resistant sensors, consistent measurement protocols across departments, and clinician training in HRV interpretation. Together, these insights reinforce HRV as a powerful adjunctive tool that strengthens clinical awareness, improves early detection, and supports better patient outcomes. This study ties together many of the themes we've discussed across today's episode. Stress recovery is not uniform, and HRV's sensitivity to context makes it one of the most powerful tools available for understanding stress resilience as we close today's episode, let's turn to our actionable insights. First, for individuals, the studies this week highlight how accessible practices such as resonant breathing, paced respiration, and guided relaxation can create meaningful shifts in autonomic balance. These practices not only influence heart rhythm, they shape how the body recovers from daily challenges, responds to immersive environments, and prepares for anticipated stress. Engaging in steady, intentional breathing remains one of the most effective tools for restoring balance after cognitive load, physical strain, or emotional activation. Second, for clinicians, the diversity of findings across these studies reinforces that context matters. Stress recovery, anticipatory stress, immersive technology exposure, and physiological interventions like arterial occlusion each influence HRV differently. Understanding these nuances can help clinicians make informed decisions about when to introduce biofeedback, how to interpret HRV data in the presence of medications or physiological strain, and how to consider individual differences such as personality traits or sensitivity to immersive environments. Third, for researchers, this collection of studies demonstrates the rapid growth of HRV science across psychological, technological, and clinical domains. Advances in artifact reduction, nonlinear HRV modeling, and multimodal sensor approaches are expanding what can be measured and understood. There are growing opportunities to refine stress paradigms, examine individual autonomic profiles, and explore how technology mediated experiences influence physiological load. Thank you for joining us on the Heart Rate Variability Podcast. Each week, HRV helps us better understand the nervous system's remarkable capacity for adaptability, sensitivity, and healing. We look forward to seeing you next time.
