Heart Rate Variability Podcast: Understanding Frequency Domains

Heart rate variability reveals insights into health, emphasizing the importance of understanding its frequency components for wellness.

### Understanding Heart Rate Variability Frequency Domains
* ❤ Dr. Fred Schaefer explains the concept of frequency in heart rate variability (HRV) as the **number of times an event occurs in a period of time**, such as the **time between successive heartbeats**.
* 🕰 Ultra-low frequency, the slowest HRV component, is slower than **5 of a Hertz**, with cycles that can be as long as **8 hours**, making it **impractical for real-time biofeedback** but potentially **useful in long-term assessments**.
* 🔍 Very low frequency (0.33-0.4 Hz) may reflect a balance between sympathetic and parasympathetic activity, influenced by **stress perception** rather than **severe stress responses**.
* 📊 Low frequency (LF) power is predominantly parasympathetic, reflecting **baroreceptor activity** and **slow-paced breathing or muscle contractions** during intentional practice.
* 📉 LF/HF ratio is often not useful in consumer-grade HRV measurements, as **LF power is primarily parasympathetic even at rest**, and **LF and HF components may not align perfectly**.
* 📈 The goal of LF power training is to increase **high frequency (HF) power** during resting baselines over time, indicating **improved vagal tone**.
* 📱 Consumer-grade HRV measurements may be affected by movement artifacts, requiring a **grain of salt** when interpreting **uncorrected values**.
* 🧠 Dr. Schaefer emphasizes the importance of **consistency in HRV measurements**, looking for **general trends** rather than obsessing over **specific values**.

welcome to the heart rate variability podcast. Each week we talk about heart rate variability and how it can be used to improve your overall health and wellness. Please consider the information in this podcast for your informational use and not medical advice. Please see your medical provider to apply any of the strategies outlined in this episode. Heart rate variability podcast is a production of Optimal LLC and Optimal HRV. Check us out at optimalhrv.com. Please enjoy the show. Welcome friends to the heart rate variability podcast. I am so excited for this episode. Our good friend, and I say ours because he dropped a great episode with us on time domain, frequency, or time domain. I'm jumping ahead here. HRV readings about a month ago and got some really great feedback on that. So I want to welcome Dr. Fred Schaefer back to the show. At this point, if you don't know Fred, you got to go back to the time domain episode. It'll set up this one on frequency domains really well. So Fred, welcome back to

the show my friend. It is great to see you happy 2024. I was pleased to make it to 2024. It's starting out well. That's good. Hopefully, it ends well too. I'm a little nervous about, you know, maybe some things that happen this year, but uh, let's just all wish for the best. So uh, I try yes uh, speaking of stress uh, frequency domains uh. I'll be honest with our audience. These have been a something that I have studied um. I have tried to work into my thinking. I think I got low frequency pretty good, but we hit a level of complexity here that I'm am so so glad. If I were to pick one person in the world to help me work through this complexity, Fred, it would be you. So I'm going to just throw you throw it out there. What the heck is a frequency oh what what are we looking at here when it uh relates to heart rate variability. Actually, if there was one person I would choose to tell this story, it would be Dr. Richard GT et al.

University, uh, he is, uh, probably my favorite explainer of all things HRV. Uh, now having said that, let's talk about what a frequency is. Yes, it's just the number of times an event occurs, uh, in a period of time like a minute. Uh, so frequencies are when we take a look at, uh, the HRV just like the EEG. It's driven by different sources and therefore they occur different numbers of times per minute. Are you with me so far? And so with you so far, we can use a term like cycles per second. So imagine a sine wave and so, uh, the number of waves per unit of time, uh, would be its frequency. Okay, and the height of the wave from peak to trough would be the strength or amplitude. Okay, of that frequency. So we, anyone who has an experience with the EEG knows that it is divided into different frequency bands and that we can measure how much energy is in alpha and, uh, theta and beta and so forth. Uh, in the same way, the uh, HRV signal because

it's generated by different processes, some very glacially slow, others more rapid like breathing. It contains different frequencies too. The slowest frequencies are called ultra-low, the fastest frequencies are high frequency. Okay, you with me so far? I'm with you so far. Hey, well, let me ask you a question. I might be wrong with, well, maybe an A. Let me just throw something out because I think I'm wrong, but I think the correction might help a lot. So, when we say frequency, I don't think we're saying the frequency of the heartbeat, right? Am I correct with, yeah, no, we are actually talking instead about the component. We look at the basis of HRV measurement, whether we're looking at the average amount of variability, yeah, or the frequency components, is the time period between a series of successive heartbeats. So, we're not looking at heart rate, we're rather looking at the different amounts of time in milliseconds and milliseconds, thousands of a second, yeah, between successive heartbeats.

now frequent one way of defining frequency is the number of cycles a second. Okay, uh, and we're looking at things that are really slow. So, another term for this, by the way, abbreviation is HZ or Hertz. But what we're looking at in terms of frequencies are far, uh, different than the ranges that we typically see in the EEG. For example, uh, the very slowest ones, uh, which we typically record over 24-48 hours, is ultra-low. Yeah, now ultra-low is slower than, and listen to this, 5, of a Hertz. So, 5,000 of a cycle per second. So, that's really, uh, that's really slow. Yeah, uh, in performance work in, uh, HRV by feedback, uh, you're not going to measure this in, uh, real-time because it's going to take many hours, uh, to be able to, uh, record enough data for this to be useful. Okay, is that making sense so far? So, so, it's not that you, again, may, maybe, may, I think I'll, I'll be our audience who may be a

little uninformed on this in the podcast, asking some of these questions, but are we so the ultra long, the ultra low frequency. Is it that to get a cycle takes so long with this? We just need to gather enough information to make it useful. Yes, exactly. The cycles that make up ultra low could easily be as long as eight hours. Yeah, and so this is not a practical kind of bi-a feedback because we want people to have fairly immediate knowledge of results in bi-a feedback. And so we so ultra low may be useful in assessment. If I were if I had a heart patient, and I'm not a clinician, I want to make that clear. I'm an academic and a researcher. But if I were if I were assessing a if I did have a license and under my license would assess a heart patient. This may be an important metric because of the relationship between total variability and ultra low frequency variability in coronary outcomes. Okay, and would that

person be lying in a hospital bed because I mean everything basis good no so you can use uh just as cardiologists can monitor the body for like uh month uh using you uh a portable uh monitor uh we can for 24 48 Hours uh monitor uh heart rate variability including Ultra L okay okay and that I can get up I can go to the gym I can go absolutely we want you to get all that that's that's okay with this this method because this captures all of the sources of variability okay and sleep is one of the most important right uh sources of variability yeah uh so now we don't entirely understand there isn't a consensus about the sources of ultra low and what I mean is there undoubtedly are are many slow acting uh glacially slow biological processes uh like core body temperature uh metabolism renin and ensin uh and so forth uh but we know that when it is blower uh that this and or when uh total heart rate variability is lower uh this is a very poor uh prognostic.

sign okay so that's all ultra low, and it really isn't part of most HRV by feedback practice. Yeah, did you think when we think about HRV tracking, where people have Apple watches on or Fitbits or other, like, is it useful? I don't see this very often in the results, these 247 no wearables and 24/7 is used very loosely in my term because I know they all do it a little different, but it doesn't seem like there's a whole lot of commercial-grade products right now focused on this unless I'm missing something. No, okay. For example, Firstbeat Technologies has a tracker that is designed for this kind of ambulatory recording, and my dear friends at The Institute of Heart Math are able to take 24 hours of data from this device and then both manually and automatically. It's a combination of both, clean it up and then analyze it, and so the Institute of Heart Math does.

reports based on say 24 hours of data that have been cleaned up. Fascinating, fascinating, and but again for most of your listeners, uh, this is really important for research. It's not important for uh either Optimal Performance training or uh clinical interventions. Uh, excellent. So mostly in the cardio space, uh, heart health. Are we talking about any mental health or other? Is it giving us, I mean, is higher, is probably better, I would imagine, for everything. Heart rate variability, higher the better, is as long as it's coming from a healthy source as opposed to a abnormal heart rhythm. Yes, gotcha, gotcha. Excellent. So I know another one we could probably knock off the list, uh, but I, I want, I want to give it its due and its place in the Sun as well, is very low frequency. Uh, so I, I will shut up and allow you to explain this to our audience. Okay, the frequency range for very low frequency is between, and you're going to have to listen to decimals very carefully. I'm looking at it as well, three, so

0.33 to 0.4 Hertz. So again, we're talking about an extremely slow rhythm. The periods of time we're looking at. So the rhythms that make up very low frequency are between 25 and 300 seconds. Okay, where for ultra-low, the periods were from 5 minutes to about 24 hours. For very low frequency, it's between 25 and 300 seconds. You probably want a minimum of you of five minutes, which, but it's better monitored over 24 hours. Okay, so you can get a measurement in five minutes, but it's largely going to be poop. So the more data, the better. The better now we are not entirely sure of what contributes to this rhythm. There is the possibility that the heart's own intrinsic nervous system may contribute to the very low frequency rhythm. It may be influenced by physical activity. It may. There may be over a long period of time some sympathetic contribution, but probably there also will be a parasympathetic contribution, and and

this is where I want to make a distinction. P. Steven Porges has described two components of the parasympathetic branch. What he calls a phylogenetically older component is called the unmyelinated vagus. Vagus is the 10th cranial nerve, as well as what he calls a phylogenetically newer component called the myelinated vagus. Within this explanatory model, the polyvagal theory, when stressors cause us to feel unsafe and distressed, we may suppress the newer myelinated vagus. This may in turn increase very low frequency activity. So, we're not talking about the severity of stressors like traumatic stressors that might produce immobilization, freezing, fighting death, passing out, dissociating. We're not talking about that type of severity. Yeah, instead, we're just talking about the perception that we're being challenged. And so, to make this practical, it is possible that when clients try too hard during HRV training, we may see a spike.

in very low frequency band power that reflects what we'd call vagal withdrawal, the suppression of the newer myelinated vagus. So, it's important not to, and my dear colleague Dr. GTS makes a distinction that we should not automatically assume that when we see that increase, that it is sympathetic; that it may very well be unmyelinated parasympathetic. So, are we talking dorsal vagus nerve? Yeah, we're talking about the, okay, we're talking about the two branches. Yeah, okay, so I know that's a term listeners will be maybe a little bit more familiar. So, are we might be seeing slight dorsal vagal activation? We may see, we may actually see a rather pronounced activation of the unmyelinated vagus. Okay, so let me, this has been a topic for the show, so I'd love to jump in here and get your opinion on, because that there's in

my world of the trauma. Sometimes people use dorsal vagal to say, I'm a little tired today. I must be in dorsal vagal. My kind of understanding of it was more like an emergency brake during trauma to shut you down, but there's not kind of like, it's not like a normal brake on a car where you can gradually put it on and take it off, but it's more of an emergency and trauma. But I'm kind of hearing from you that it might maybe looking at this as maybe more contin, it's on a continuum. In other words, everyday stressors can activate the, can basically suppress the myelinated vagus without producing a full-blown freeze response, right? So often what we call a stress response and misl as sympathetic is simply a suppression of the myelinated vagus of the nucleus ambiguous. So if I use the term, This is good stuff here, removing. So a lot of times we'll talk about on

the show. The ventral vagal break of the sympathetic activation. So, are we talking, I mean, when I hear suppression, it seems like different, it seems different or inhibit. We inhibit the myelinated vagus. Okay, now think about what the myelinated vagus, the newer vagus does. It allows us to engage in social interaction. It allows us to self-regulate. It allows us to emotionally bond with others. And this can be disrupted by everyday stressors. Yeah, and so one of the takeaways is that when we do any kind of self-regulation, it's important to not try too hard. And that's consistent with Eric Pepper's wonderful term, effortless breathing. Yeah, that you don't force your breathing, you get out of its way. In Dr. Enah Kazan's perspective, you rediscover your breathing rhythm. Yeah, you don't force it, you don't order it, you rediscover it. Then you trust your body to breathe for you. Yeah, so it's important in HRV training to use the

autogenic concept of passive volition of allowing rather than ordering or forcing. Yeah, and so when you see elevation in very low frequency activity, it may signal that the person is trying too hard. In some cases, you may see other changes. You may see increased sweat gland activity. You may see a reduction in hand temperature. And these also may be signs of vagal withdrawal. And so we're not talking about fight or flight. We're not talking about freezing. Yeah, and fighting. We're talking about more modest changes. Okay, so and are we getting some of that dorsal vagal activation as the ventral vagal? Is that, you know, because one of the things I think polyvagal, I struggle with a little bit, is I get, hey, you a carcer over to your lane. The ventral vagal brake releases. You got all that sympathetic energy to react immediately and activate the flight response. That seems pretty intuitive. It's where like, okay, I get the freeze response kind of the

emergency aspect of this but like okay I'm just tired like I I've had a hard day at work so I'm I don't I'd love a little sympathetic energy to be honest with you but you know that there's not that there are we getting is that a is that a vagal withdrawal a vental vagal with can be something as simple as uh you have burn through available ATP okay let me point this way uh attention uh and executive control are a very represent very finite resources yeah uh and the brain is powered by stored glycogen which is then used as glucose to provide the ATP with me so far yep if during the day you have uh exhausted yourself uh your brain may have less of a reserve uh of Bogen uh and therefore you are not going to be as sharp yeah uh and you may feel more fatigued so I don't think we need to use uh and I'm I'm generally not comfortable uh explaining things uh in terms of components of uh

of the parasympathetic nervous system when there are simpler explanations. Yeah, so all right, you know, it's like trying to explain things from the quantum level. Yeah, as soon as you see a, uh, by a feedback, and I'm using this in quotes, uh, vendor explaining why their product works at a quantum level, you should run for the exit, uh, because you're, uh, you're going to hear, uh, what one TED speaker calls neuro flap doodle. I love that, just, uh, you know, silliness. So, I think it's important to keep things simple and grounded, and so the takeaway is that what we call a stress response, uh, may very well be just, uh, reducing our normal, uh, parasympathetic activity. It isn't so much that we freeze, it isn't so much that we engage in fight or flight, it's not P. The nervous system isn't perceiving it as that magnitude of threat. Excellent, but it is enough to increase very low frequency, it is enough to cool the hands and to make them sweatier. Yeah, and just

to appreciate that our simple answer took us up into the complexity of the brain, which may or may not be more complex than quantum physics, depending on how much ATP you have to go with it on a given day. Yes, so I thank you for going on that tangent because it's an ongoing theme of the show trying to kind of figure some of these stuff out. So, it seems like if I were to summarize very low frequency and ultra-low frequency, we're measuring Sarcan Rhythm comes to mind, but I don't want to use, I don't want to put those words, but rhythms like that where we're getting there, and there seems to be some question marks still to what we're looking at and the value of the application of what we're looking at. Am I close? Yes, when Christopher Zur and McCrady and I finished our literature review somewhere around 2013, there remained a great deal of uncertainty about the sources.

of both ultra-low uh than very low uh. There is more agreement about low and high, and those are the ones that uh your audience will be most interested. Let's let's go there, my yeah low frequency activity uh is uh large, is exclusively under most conditions in which we measure it, parasympathetic. Okay, so one of the most important takeaways is we're looking at uh parasympathetic activity. Another contributor can be the Barrow receptors, and these are the blood pressure uh reflexes. Yeah uh, but collectively uh, these are uh, we can consider this to be largely parasympathetic. Now the reason we care about low frequency power is that low frequency power tells us if the activity we are using to stimulate uh the uh nervous system uh is working. So, and what I mean by that is uh, it could be uh slow-paced breathing, mhm. It could be slow-paced muscle contraction. Now when I talk about slow-paced uh, we could be talking at six times a minute. We could be talking at

some slightly different rate if we find fortunate to the individual, so maybe 4 and A2 to maybe six and a half times a minute for an adult, but that's a slow pace, whether it's breathing or muscle contraction. This will stimulate the baroreflexes, and in turn, can teach the cardiovascular system to increase heart rate variability. So when my breathing exercise or my muscle contraction exercise is working, I will see during that time, but only during that time, an increase in low-frequency power. Okay, and importantly, the only, you know, that it's a manifestation, maybe I correct my L, but I think it's really important for our audience, is that it is happening during an intentional practice. You know, it's it, you're taking, you're going to the gym, so to speak, and this is the way to kind of measure the impact of that practice on overall, probably going back to the time domains. You know, you should see increases in that eventually if you're practicing at rates that

increase your low frequency. Yes, I love your example, and this is one of those very important takeaways for your audience. We are not doing slow-paced breathing or muscle contraction practice to increase low frequency power. Low frequency power is just a way we keep scoring, and we absolutely do not expect people to either breathe at this rate or contract their muscles at this rate throughout the day. You only go to the gym if we're lucky, like once a day. Yeah, yeah, and it would really be inconvenient to have to do bench presses throughout the day. Yeah, curls or those other activities. Yeah, so you're doing it for a brief period of time. As I've listened to the always brilliant Ena Kazan, we're talking about a maximum amount of time training time of about 20 minutes. Initially, it might be 5 minutes, and then you might, you know, week by week, you increase it to a maximum of 20, and that's just 20 minutes, perhaps once a day. And it's not to increase low

frequency power again low frequency power just tells us that we're getting results initially as we're doing it. Yeah, uh, the closest analogy I can make, it's a really lame analogy, is when I'm doing uh weights in the gym. I might during the exercise or in between sets feel my muscles get swo so briefly. I might sense a bulging hypertrophy of the muscle. Yeah, but the point of it isn't to get swall all Ely. The what you're looking for is going to what we call the high frequency band when the person is just breathing normally. Now, what I mean by normally is maybe 12 to 18 BRS per minute. And the high frequency bend, the amount of power in that bend tells us if we move the needle on vagal tone, parasympathetic tone. Yeah, over a matter of weeks, we may see that number get bigger. Now, I'm not talking about percentage, I'm talking about absolute power. Uh, but uh, and uh, the optimal HRV app uh, gives you a measurement that you can

take under resting conditions. Uh, and so if you take what we call a resting baseline, and what I mean by that is you're sitting quietly, breathing at normal rate, ates no feedback. Uh, and if you see that the high-frequency power is greater, you are moving in a direction of increasing vagal tone. So, we do we increase low-frequency power during practice so that we can increase high-frequency power during baseline. I love that. So, let me let me just ask maybe I I'll give you permission to say Matt it doesn't really matter because that that is a totally appropriate. But I'm I'm looking at you. You mentioned like total power or absolute power, I think it was, and we're back into the the herses, and now that we kind of care more about now that we don't care about ultra very low, but now we're like really care about low-frequency, high-frequency for the average user. Yeah, when we talk about power and we talk about Hertz, it's always been kind of a mystery to me. Let's put it this way. Hertz is the

number of cycles per second, and do we know what we're measuring with low or high frequency? Low is going to be parasympathetic, low maybe Barrow receptor, but largely parasympathetic. Hi is parasympathetic. Okay, and are we talking about, again, I listeners will be somewhat familiar with these terms, you know, re, you know, when the exhale throw puts on, you know, the break, the term is escaping me, right? You're talking about respiratory sinus. There, there we go, thank you. So, are we talk, is that like a cycle, like what we're talking about here, or a cycle would be a breathing, you know, a cycle is just the number of waves per second. Okay, that's all we're talking about, and based on this, again, we're talking about very slow processes, and again, to remind you, when we talk about, say, Alpha, that's eight to 13 or 12 waves or cycles per second. With me so far? Well, low frequency is not even one cycle. It's

like 0.005, so 500s of a cycle to .15 Hertz, so not even one cycle, so that's really slow, and that is parasympathetic, and probably the bar receptors, gotcha. High frequency is defined by .15 to about .04, so again, not even one cycle per second, and it is due to breathing, and it's entirely parasympathetic. So one of the important takeaways for your audience is some of them will have read or seen reference to a ratio between low frequency and high frequency power, and power just is a way of measuring how much energy there is depending on how this is obtained, what the person is doing. This is largely going to be poop, and let me tell you why. It assumes that low frequency has a robust sympathetic component, but in many cases, what we're asking the person to do doesn't involve exercise, right? The person may be sitting quietly, and so it will be parasympathetic divided by

parasympathetic. Okay, so that index is very least under resting conditions. Uh, pretty sketchy in the sense of not, not very informative. And that's, is that am I right to say that's a relatively recent kind of change in how we look at things? Certainly in the last decade. Okay, but again, it many questions are extremely nuanced. Uh, so it matters a great deal how you are measuring heart rate variability. Uh, for example, in our life lab, people are sitting quietly. We're not putting people on a tilt table. Yeah, a tilt table has your head pointing down. It is a, uh, cardiovascular stressor. Yeah, uh, and yes, you'd expect it to AIC at sympathetic uh, activation. But under our uh, and, and honestly, most of your uh, audience is going to sit upright or lay down or stand, and they are going to measure their uh, heart rate variability under very uh, non-demanding circumstances. And therefore, uh, we wouldn't expect uh, to have a significant sympathetic component to low frequency.

power. So, it's just parasympathetic divided by parasympathetic. So, my takeaway is to use low-frequency power while you're engaged in the activity designed to increase your HRV. Use high-frequency power during your resting baselines so that over a period of weeks to months, you can see whether it increases. Excellent. So, with that again, I may be wrong, so please correct me if I am. High frequency, so if we take a three to five-minute reading, you know, which is kind of in the arena of the time domains that we talked about in the last episode. High frequency could come in there in a way that gives us some valuable information like RMSSD or SDNN. Would it fit well within that? Would it tell us something different than though the time domain measures? I think of the apocryphal story of blind sages in India, each holding on to a different portion of an elephant, getting a different aspect of

heart rate variability, uh, in, uh, they're not going to align perfectly even among what we call time domain measures. And for your audience who haven't listened to our, uh, podcast from a month ago, uh, time domain measures give us an average value of how much heart rate variability did I have, uh, in a recording period like five minutes or three minutes, uh, it, uh, for my students, the average value that's relevant to them, uh, might be, uh, their, uh, GPA in this case. So time domain and the time domain values don't all line up right because they measure, they assess different parts of the elephant, okay, uh, but there is some agreement. So for example, I would expect that, uh, the short-term measure of HRV, which is the RMSSD, uh, will, uh, move in concert, uh, with increased high-frequency power when both are measured at rest after. So as, uh, high-frequency power slowly increases over time, uh, during resting baselines, so should the RMSSD. Excellent, hey there, there's an elephant there after all, yeah, there.

is you know one of the real challenging aspects of HRV is that all the metrics, even time domain or frequency, do not line up exactly. Yeah, and that's okay because they are measuring some, are measuring total variability, some are doing brief variability, and there are other differences as well. Yeah, and it's okay, but as high-frequency power increases, and in a research setting, we would convert the number to what we call the natural log or log to the base e. As that goes up, the RMSSD may very well go up in the same direction. Excellent boy. Anything that I am not smart enough to ask because I really appreciate this. I really think we and like that think about and nerd out about HRV a lot, can throw these terms around, and even like I said with the Herz thing, like, okay, I think I guess so. I really can't tell you how much I appreciated just personally, and I

know the audience were, but is there any questions I should ask you or anything else. It's not because you're not smart enough; it's just that you are so smart that you're pulled in quite a few different directions. Thank you. So, let me raise the question that again your audience may be interested in, right. How do I assess my change in my numbers? And it's important [Music] to where you can be consistent. You're more likely to compare apples with apples and not bananas or kumquats, okay. So, consistent could be the same time of day, the same preceding activity, and so forth. But you don't have to be obsessive about it, but it's important consistency. And then what you look for are General Trends, yeah, in your numbers. What I would like to see over time as a function of exercise, Stress Management, HRV practice is an increase in resting high-frequency power, as well as increased time domain activity such

as the RMSSD, yeah, and you're looking at just trends. You don't worry about a fractional; you just ask, Is it going up or down? Yeah, uh, and some authors have suggested that if we're pretty good at keeping it constant, and by constant, I mean recording at the same time in the same conditions, it may give us useful information about whether we have exhausted ourselves due to our workouts, whether we have just caught a viral infection, because HRV may reflect that. Awesome. Well, uh, my friend, uh, this has been a spectacular journey, uh, to take with you because, like I said, I really unpacking the complexity, and I think exploring, like, well, you know, our audience might hear very low frequency and to say, Hey, there's limitations there; it's telling us something, uh, but we're kind of still trying to figure it out in some ways, and this is what we have figured out. U I just think really helps people like myself to say, I don't have any clue.

what ultra-low frequency is. I don't think I have to worry about it, but you don't have to worry about that. You don't have to worry about very low, yeah, and you also need to take the measurements you obtain from consumer-grade year with quite a few grains of Morton salt. And let me just remind your audience why the apps on our smartphones, the apps on our smartwatches and trackers, do either no or minimal error correction. Yeah, so much of the variability we may see from recording to recording may reflect movement artifact and not a change in your physiology. That's, I mean, the more sophisticated members of your audience may upload, you know, may basically upload their inner beat intervals, the time period between heartbeats, and clean it up to get rid of that source of false variability. The others, including myself, because I'm way too lazy and I really don't care, I just look for general changes, realizing that the measurements, I mean, it's like tracking.

calories burnt. Uh, that is so, uh, imprecise. Yeah, uh, no, I do trust the steps a little bit more, uh, but even there, uh, I don't, I allow for variability. So, I, I do know, you know, the steps, uh, are not, uh, exactly accurate, but they don't need to be, right, right? Well, as, as, uh, a fan of history, the word artifact has been something that brings me joy to something that haunts my dreams, uh, trying to, to figure out because I mean how, how concise you, where, where you put the Lim, like all that stuff is a whole another level of complexity of, of how do you do this while, how, what's for a commercial grade app, how much of that artifacting can you do, do you want to do, uh, because you got to get enough to give feedback at the same time. So, it, it's very, like I said, the word artifact, it's for something that brought me joy in a museum to something that now, uh, you know, just, I, I could never hear the word again and be

Okay, no, and you shouldn't be. I mean, I look at the measurements from my Fitbit and from my Apple Watch. Sometimes it will tell me that my RMSSD is over 150. The late Fritz Perls would call that elephant. He was good at coining very able phrases. Yeah, but far more extreme than just the bull variety, right? Uh, 150? No way. Heck no. Uh, 35? I believe it. Yeah, 150? I don't believe it. But it doesn't do error correcting, so one has to be nuanced about our measurements and to realize the imprecision. And that's where consumer-grade gear is now. Uh, and fortunately, in our lab, uh, we can do our own data cleanup. But so I want you readers to take their measurements if they are just looking at uncorrected values with several grains of Morton salt. I love that. I think that that's a great way to wrap up. Uh, Dr. Fred Scharer, thank you so much. Uh, I, uh, I just appreciate you.

appreciate your patience. Really, I think walking through this at a pace that is still good in my learning curve. Like I said, obsessing about this stuff, I could have like given you probably maybe something you give me a B on for low and high frequency. Now I think I got the A answer for the class. Maybe I could even write a paper on it. I don't know, but I really do appreciate that because, you know, as HRV gets more and more, I think paying attention to what it is and where these metrics come from and how confident are we that we know what we're looking at. I think are all just things to keep on people's radar. Here's where we're at maybe a year or two for now as technology gets even better. We'll have another conversation about, yeah, now we can measure very low frequency in a different way and we know what it's telling us in that way. So I just appreciate you, my friend, and being

able to go into this level of detail with us. This has been a joy for me. I am so glad to hear that too. So um, as always listeners, optimal rv.com. You can find show notes, uh, the Youtube videos, and I will promise to do my best to find a good topic to temp uh Dr. Schaer to come back on the show soon because I know we always get great feedbacks. Uh, my friend for win on so I thank you and I thank our listeners. Thank you. Take care.

Dr. Fred Shaffer talks HRV Frequency Domains

Matthew Bennett

Understanding Frequency Domains in Heart Rate Variability

Frequency refers to the number of times an event occurs in a given time period, and in heart rate variability (HRV), it relates to the different sources driving the heart's rhythm.

HRV signals contain various frequencies, with ultra-low frequencies being the slowest and high frequencies being the fastest.

The measurement of frequency in HRV is based on the time intervals between successive heartbeats, rather than the heart rate itself, and ultra-low frequencies can take hours to record, making real-time measurement challenging.

Understanding Ultra Low and Very Low Frequency in Heart Rate Variability

Ultra low frequency cycles can last up to eight hours, making them less practical for immediate biofeedback.

These metrics may be important for assessing heart patients and monitoring variability over 24-48 hours.

Very low frequency rhythms range from 25 to 300 seconds and are influenced by the heart's nervous system, physical activity, and both sympathetic and parasympathetic contributions.

The Distinction of Vagus Nerve Components

Steven Porges describes two components of the parasympathetic branch: the unmyelinated vagus (older) and the myelinated vagus (newer).

Stressors can suppress the myelinated vagus, leading to low-frequency activity and vagal withdrawal, without necessarily causing a severe stress response.

Everyday stressors can disrupt social engagement and self-regulation by inhibiting the myelinated vagus, highlighting the importance of effortless self-regulation in HRV training.

The Impact of Fatigue on Brain Function and Stress Response

Fatigue from a long workday can lead to reduced brain reserves of glycogen, resulting in decreased sharpness and increased tiredness.

The stress response may simply be a reduction in normal parasympathetic activity, rather than a severe threat response.

Low-frequency power activity is primarily parasympathetic and can indicate the effectiveness of activities like slow-paced breathing or muscle contraction in stimulating the nervous system and increasing heart rate variability.

Understanding Low and High Frequency Power

Low frequency power is used as a scoring mechanism and is not meant to be sustained throughout the day.

Brief training sessions, gradually increasing to 20 minutes, are effective for achieving results.

High frequency power during normal breathing (12-18 breaths per minute) indicates an increase in vagal tone over time.

Heart rate variability (HRV) is influenced by low and high-frequency power, both of which are parasympathetic and can be misinterpreted as having a sympathetic component.

The measurement of HRV is nuanced and can vary depending on the individual's activity and position.

Using low-frequency power during activities to increase HRV and high-frequency power during resting baselines can provide valuable insights over time.

Understanding HRV Metrics and Their Variability

HRV metrics, such as time domain and frequency, do not align perfectly as they measure different aspects of variability.

Consistency in measuring conditions is important for tracking changes in HRV numbers.

General trends, rather than fractional changes, are key to assessing the impact of exercise and stress management on HRV.

The Challenges of Measuring Health Metrics

Measuring calories burnt and steps taken can be imprecise, but they provide valuable feedback.

The complexity of data artifacting poses challenges for commercial-grade apps.

Consumer-grade gear often lacks error correction, making it important to approach measurements with nuance and skepticism.