[00:00:00] Speaker A: 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
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[00:00:32] Speaker B: 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've 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.
[00:01:15] Speaker C: I was pleased to make it to 2024.
It's starting out well.
[00:01:21] Speaker B: That's good. Hopefully it ends well, too. I'm a little nervous about maybe some things that happen this year, but let's just all wish for the best.
I try. Yes, speaking of stress frequency domains, I'll be honest with our audience. These have been something that I have studied.
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 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 it out there. What the heck is a frequency? What are we looking at here when it relates to heart rate variability?
[00:02:18] Speaker C: Actually, if there was one person I would choose to tell this story, it would be Dr. Richard Gevert at Alliant University.
He is probably my favorite explainer of all things HRV.
Now, having said that, let's talk about what a frequency is. Yes, it's just the number of times an event occurs in a period of time, like a minute.
So frequencies are when we take a look at 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?
We can use a term like cycles per second. So imagine a sine wave. And so the number of waves per unit of time would be its frequency.
And the height of the wave from peak to trough would be the strength or amplitude, okay, of that frequency. So anyone who has any 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 theta and beta and so forth.
In the same way. The 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, with me so far.
[00:04:45] Speaker B: I'm with you so far. Well, let me ask you a question I might be wrong with. Well, maybe 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.
Am I correct with.
[00:05:09] Speaker C: Yeah, we are actually talking instead about the component.
The basis of HRV measurement, whether we're looking at the average amount of variability 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. In milliseconds, there's thousands of a second between successive heartbeats.
Now, one way of defining frequency is number of cycles a second, 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 different than the ranges that we typically see in the EEG. For example, the very slowest ones, which we typically record over 24, 48 hours, is ultra low.
Now, ultra low is slower than, and listen to this, 5000th of a hertz. So 5000 of a cycle per second.
So that's really slow.
[00:06:56] Speaker D: Yeah.
[00:06:57] Speaker C: In performance work in HRV biofeedback, you're not going to measure this in real time because it's going to take many hours to be able to record enough data for this to be useful. Okay, is that making sense so far?
[00:07:25] Speaker B: Again, I think I'll be our audience, who may be a little uninformed on this at the podcast asking some of these questions.
The ultra low frequency, is it that to get a cycle takes so long with the cycles to gather enough information to make it useful?
[00:07:53] Speaker D: Yes, exactly.
[00:07:54] Speaker C: The cycles that make up ultra low could easily be as long as 8 hours. Wow.
[00:08:02] Speaker D: Yeah.
[00:08:03] Speaker C: And so this is not a practical kind of biofeedback because we want people to have fairly immediate knowledge of results in biofeedback.
And so we so ultra low is maybe useful in assessment.
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 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.
[00:09:09] Speaker D: Okay.
[00:09:10] Speaker B: Would that person be lying in a hospital bed? Because.
[00:09:20] Speaker C: You can use, just as cardiologists can monitor the body for like, a month using a portable monitor, we can, for 24, 48 hours, monitor heart rate variability, including ultra low.
[00:09:45] Speaker D: Okay.
[00:09:46] Speaker B: And I can get up. I can go to the gym? I can go. Absolutely. We want you to get all that's okay with this method.
[00:09:56] Speaker C: This captures all of the sources of variability.
[00:10:02] Speaker D: Okay.
[00:10:02] Speaker C: And sleep is one of the most important sources of variability.
[00:10:08] Speaker D: Yeah.
[00:10:12] Speaker C: Now, we don't entirely understand. There isn't a consensus about the sources of ultralow. And what I mean is there undoubtedly are many slow acting, glacially slow biological processes like core body temperature, metabolism, renin, angiotensin, and so forth.
But we know that when it is lower or when total heart rate variability is lower, this is a very poor prognostic sign.
[00:10:57] Speaker D: Okay.
[00:10:58] Speaker C: That's ultra low. And it really isn't part of most hrv bifeedback practice.
[00:11:06] Speaker D: Yeah.
[00:11:07] Speaker B: Do you think, when we think about hrv tracking where people have apple watches on Fitbits or other, is it useful?
I don't see this very often in the results. These 24/7 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.
[00:11:45] Speaker C: No.
For example, first beat 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 Art Math does reports based on, say, 24 hours of data that have been cleaned up.
[00:12:39] Speaker D: Fascinating.
[00:12:42] Speaker C: But again, for most of your listeners, this is really important for research. It's not important for either optimal performance training or clinical interventions.
[00:12:58] Speaker D: Excellent.
[00:12:59] Speaker B: So mostly in the cardio space, heart health, are we talking about any mental health or other?
Is it giving us. I mean, higher is probably better, I would imagine, for everything. Heart rate variability, higher the better, as.
[00:13:18] Speaker C: Long as it's coming from a healthy source as opposed to an abnormal heart rhythm. Yes.
[00:13:25] Speaker D: Got you.
[00:13:27] Speaker B: Excellent. So I know another one we could probably knock off the list but I want to give it its doing its place in the sun as well is very low frequency. So I will shut up and allow you to explain this to our audience.
[00:13:45] Speaker C: Okay. The frequency range for very low frequency is between.
And you're going to have to listen to the decimals very carefully.
[00:13:56] Speaker B: I'm looking at it as well.
[00:13:59] Speaker C: So zero 00:33 to zero 4 hz.
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 five minutes to about 24 hours. For very low frequency it's between 25 and 300 seconds. You probably want a minimum of five minutes but it's better monitored over 24 hours. So you can get a measurement in five minutes.
But it's largely going to be poop. So the more data the better.
[00:15:02] Speaker D: The better.
[00:15:03] Speaker C: Got you. 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.
There may be over a long period of time some sympathetic contribution but probably there also will be a parasympathetic contribution. And this is where I want to make a distinction.
Stephen Porgis has described two components of the parasympathetic branch.
What he calls a phylogenetically older component is called the unmyelinated vagus. Vagus is a 10th cranial nerve as well as what he calls a phylogenetically newer component called the myelinated vagus.
Within Corgius's explanatory model, the polyvagal theory when stressors cause us to feel unsafe and distressed we may suppress the newer myelinated vagus and 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, feigning death, passing out, dissociating. We're not talking about that type of severity. 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. Gerbertz 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.
[00:18:35] Speaker B: So are we talking dorsal vagus nerve?
[00:18:40] Speaker C: Yeah, we're talking about the two branches.
[00:18:46] Speaker D: Yeah.
[00:18:46] Speaker B: Okay. So I know that's a term. Listeners will be maybe a little bit more familiar. So we might be seeing slight dorsal vagal activation.
[00:19:00] Speaker C: We may actually see rather pronounced activation of the unmyelinated vagus.
[00:19:09] Speaker B: Okay, this has been a topic for the show, so I'd love to jump in here and get your opinion on, because 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. And my kind of understanding of it, it was more like an emergency break during trauma to shut you down. But it's not like a normal break 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 continuum.
[00:19:57] Speaker C: 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 mislabel as sympathetic is simply a suppression of the myelinated vagus, of the nucleus. Ambiguous.
[00:20:40] Speaker B: 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.
When I hear suppression, it seems different.
[00:21:05] Speaker C: We inhibit the myelinated Vegas. Okay, now think about what the myelinated Vegas, the newer Vegas 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.
[00:21:37] Speaker D: Yeah.
[00:21:39] Speaker C: 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 is consistent with Eric Pepper's wonderful term, effortless breathing, that you don't force your breathing, you get out of its way.
In Dr. Ina Khazan's perspective, you rediscover your breathing rhythm. You don't force it. You don't order it. You rediscover it, then you trust your body to breathe for you.
So it's important HRV training to use the autogenic concept of passive volition, of allowing rather than ordering or forcing.
[00:22:42] Speaker D: Yeah.
[00:22:43] Speaker C: 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 and feigning. We're talking about more modest changes.
[00:23:26] Speaker B: Okay, are we getting some of that dorsal vagal activation as the ventral vagal?
Because one of the things I think polyvagal, I struggle with a little bit is I get, hey, a car sewer is over near 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, okay, I get the freeze response, kind of the emergency aspect of this, but okay, I'm just tired, I've had a hard day at work, so I'd love a little sympathetic energy, to be honest with you. But there's not that. There is that a vagal withdraw ventral vagal.
[00:24:18] Speaker C: It can be something as simple as you have burned through available atp. Okay, let me explain it this way.
Attention and executive control represent very finite resources and the brain is powered by stored glycogen, which is then used as glucose to provide the atp. With me so far, if during the day you have exhausted yourself, your brain may have less of a reserve of glycogen and therefore you are not going to be as sharp and you may feel more fatigued. So I don't think we need to use, and I'm generally not comfortable explaining things in terms of components of the parasympathetic nervous system when there are simpler explanations.
It's like trying to explain things from the quantum level. As soon as you see biofeedback. And I'm using this in quotes vendor explaining why their product works at a quantum level. You should run for the exit because you're going to hear what one Ted speaker calls neuroflap doodle. I love that, just 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 may very well be just reducing our normal parasympathetic activity.
It isn't so much that we freeze, it isn't so much that we engage in fight or flight.
The nervous system isn't perceiving it as that magnitude of threat.
[00:26:55] Speaker D: Excellent.
[00:26:55] Speaker C: But it is enough to increase very low frequency. It is enough to cool the hands and to make them sweatier.
[00:27:05] Speaker D: Yeah.
[00:27:05] Speaker B: 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.
So 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, circadian rhythm comes to mind, but 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?
[00:28:03] Speaker C: Yes.
Christopher, Zurr and McCready and I finished our literature review somewhere around 2013.
There remained a great deal of uncertainty about the sources of both ultra low than very low.
There is more agreement about low and high, and those are the ones that your audience will be most interested in.
[00:28:44] Speaker B: Let's go there, my friend.
[00:28:46] Speaker D: Yeah.
[00:28:49] Speaker C: Low frequency activity is exclusively under most conditions in which we measure it, parasympathetic. So one of the most important takeaways is we're looking at parasympathetic activity. Another contributor can be the barrow receptors, and these are the blood pressure reflexes.
But collectively, we 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 the nervous system is working.
What I mean by that is it could be slow paced breathing.
It could be slow paced muscle contraction. Now, when I talk about slow paced, we could be talking at six times a minute.
We could be talking at some slightly different rate if we fine tune it to the individual. So maybe four and a half to maybe six and a half times a minute for an adult. But that's slow paced. Whether it's breathing or muscle contraction, this will stimulate the barrow reflexes 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.
[00:31:09] Speaker D: Okay.
[00:31:10] Speaker B: And important, it's a manifestation, maybe I correct my lane, but I think that's really important for our audience, is that it is happening during an intentional practice.
You're going to the gym, so to speak. And this is a way to kind of measure the impact of that practice on overall, probably going back to the time domains, you should see increases in that eventually if you're practicing at rates that increase your low frequency.
[00:31:49] Speaker C: 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 score. 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.
[00:32:30] Speaker D: Yeah.
[00:32:31] Speaker C: And it would really be inconvenient to have to do bench presses throughout the day, curls or those other activities.
So you're doing it for a brief period of time.
As I've listened to the always brilliant Enoch Azan, we're talking about a maximum amount of time, training time of about 20 minutes.
Initially it might be five minutes, and then you might, 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.
The closest analogy I can make, it's a really lame analogy, is when I'm doing weights in the gym, I might, during the exercise or in between sets, feel my muscles get swollen. So briefly, I might sense a bulging hypertrophy of the muscle. But the point of it isn't to get swollen. Ultimately, 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 twelve to 18 breaths per minute. And the high frequency band, the amount of power in that band tells us if we move the needle on vagal tone, parasympathetic tone, 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.
The optimal HRV app gives you a measurement that you can take under resting conditions. 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 rates, no feedback.
And if you see that the high frequency power is greater, you are moving in a direction of increasing vagal tone. So we increase low frequency power during practice so that we can increase high frequency power during baseline.
[00:35:25] Speaker B: I love, let me, let me just ask, maybe I'll give you permission to say, matt, it doesn't really matter because that is a totally appropriate. But I'm looking at you mentioned, like, total power or absolute power. I think it was. And we're back into the hertzes. 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, when we talk about power and we talk about Hertz, it's always been kind of a mystery to me.
[00:36:05] Speaker C: Let's put it this way. Hertz is the number of cycles per second.
[00:36:10] Speaker B: And do we know what we're measuring with low or high frequencies?
[00:36:15] Speaker C: Low is going to be parasympathetic.
Low, maybe barrel receptor, but largely parasympathetic. High is parasympathetic.
[00:36:31] Speaker B: Okay, and are we talking about. Again, listeners will be somewhat familiar with these terms when the exhale puts on.
The term is escaping me.
[00:36:46] Speaker D: Right.
[00:36:46] Speaker C: We're talking about respiratory sinus.
[00:36:49] Speaker B: There we go. Thank you.
Is that like a cycle, like what we're talking about here, or am I.
[00:36:58] Speaker C: Cycle would be a breathing. A cycle is just the number of waves per second.
[00:37:05] Speaker D: Okay?
[00:37:06] Speaker C: 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 twelve waves or cycles per second.
With me so far, well, low frequency is not even one cycle. It's like zero five.
So 500 of a cycle to 00:15 hertz. So not even one cycle. So that's really slow. And that is parasympathetic. And probably the barrel receptors got you. High frequency is defined by 00:15 to about zero four. 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 isn't 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.
The person may be sitting quietly, and so it will be parasympathetic divided by parasympathetic.
[00:39:17] Speaker D: Okay?
[00:39:18] Speaker C: So that index is, at very least under resting conditions, pretty sketchy in the sense of not very informative.
[00:39:30] Speaker B: Am I right to say that's a relatively recent kind of change in how we look at things?
[00:39:38] Speaker C: Certainly in the last decade? Okay, but again, many questions are extremely nuanced.
So it matters a great deal how you are measuring heart rate variability.
For example, in our lab, people are sitting quietly. We're not putting people on a tilt table. A tilt table has your head pointing down. It is a cardiovascular stressor.
And yes, you'd expect it to elicit sympathetic activation.
Honestly, most of your audience is going to sit upright or lay down or stand, and they are going to measure their heart rate variability under very nondemanding circumstances. And therefore, we wouldn't expect to have a significant sympathetic component to low frequency power. So it's just parasympathetic divided by parasympathetic. So my takeaway is 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.
[00:41:19] Speaker B: Excellent.
Again, I may be wrong, so please correct me if I am high frequency. So if we take a three to five minute reading, 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 RMSD or SDN. Would it fit well within that?
Would it tell us something different than the time domain measures?
[00:41:57] Speaker C: Do what the time domain measures.
I think of the apocryphal story of blind sages, say, in India, each holding on to a different portion of an elephant.
[00:42:16] Speaker D: Yeah.
[00:42:19] Speaker C: We'Re getting a different aspect of heart rate variability, and 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 podcast from a month ago, time domain measures give us an average value of, how much heart rate variability did I have in a recording period? Like five minutes or three minutes?
For my students, the average value that's relevant to them might be their GPA. In this case, the time domain values don't all line up because they assess different parts of the elephant.
Okay.
But there is some agreement. So, for example, I would expect that the short term measure of HRV, which is the RMSD, will move in concert with increased high frequency power when both are measured at rest.
So as high frequency power slowly increases over time during resting baselines, so should the RMSD.
[00:44:06] Speaker B: Excellent. Hey, there's an elephant there after all.
[00:44:10] Speaker C: There is.
One of the real challenging aspects of HRV is that all the metrics, even time domain or frequency, do not line up. Exactly.
[00:44:26] Speaker D: Yeah.
[00:44:27] Speaker C: And that's okay, because some are measuring total variability, some are doing brief variability and there are other differences as well.
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 RMSD may very well go up in the same direction.
[00:45:08] Speaker D: Excellent.
[00:45:11] Speaker B: Boy.
Anything that I am not smart enough to ask, because I really appreciate this. I really think we think about and nerd out about HRV a lot can throw these terms around, even like I said with the Hertz thing.
Okay, I think I get. So I 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?
[00:45:43] Speaker C: 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.
[00:45:52] Speaker B: Thank you.
[00:45:55] Speaker C: So let me raise the question that again your audience may be interested in. Great.
How do I assess my change in my numbers?
And it's important to where you can be consistent.
You're more likely to compare apples with apples and not bananas or cumquats. Okay, so consistent could be same time of day, 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 are for general trends 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 RMSD.
And you're looking at just trends. You don't worry about a fractional difference, you just ask, is it going up or down?
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 and same conditions, it may give us useful information about whether we have exhausted ourself due to our workouts, whether we have just caught a viral infection, because HRV may reflect that.
[00:48:10] Speaker B: Awesome. Well, my friend, this has been a spectacular journey to take with you because like I said, I really unpacking the complexity and I think exploring things like, well, our audience might hear very low frequency and to say, hey, there's limitations there. It's telling us something, but we're kind of still trying to figure it out in some ways. And this is what we have figured out, 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 worry about that you don't have.
[00:48:52] Speaker C: To worry about very low. And you also need to take the measurements you obtain from consumer grade gear 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.
So much of the variability we may see from recording to recording may reflect movement artifact and not a change in your physiology.
The more sophisticated members of your audience 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 burned.
That is so imprecise.
Now, I do trust the steps a little bit more, but even there, I allow for variability. So I. I do know, you know, the steps are not exactly accurate, but they don't need to be, right?
[00:50:53] Speaker B: Well, as a fan of history, the word artifact has been something that brings me joy to something that haunts my dreams, trying to figure out, because how concise, where do you put the limit? Like, all that stuff is a whole nother level of complexity, of, how do you do this for a commercial grade app? How much of that artifacting can you do? Do you want to do.
Because you got to get enough to give feedback at the same time.
Like, I said, the word artifact for something that brought me joy in a museum, to something that just. I could never hear the word again and be okay, no, and you shouldn't be.
[00:51:43] Speaker C: I look at the measurements from my fitbit and from my apple Watch.
Sometimes it will tell me that my RMSD is over 150.
The late Fritz pearls would call that elephant shit.
He was good at coining very memorable phrases, but far more extreme than just the bull variety, right?
150. No way in heck, no. 35. I believe it. 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.
And fortunately, in our lab, we can do our own data cleanup.
But so I want your readers to take their measurements if they are just looking at uncorrected values with several grains of Morton salt.
[00:53:02] Speaker B: I love that. I think that that's a great way to wrap up.
Dr. Fred Schaefer. Thank you so much.
I just appreciate you. I 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 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 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 from 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.
[00:54:19] Speaker C: This has been a joy for me.
[00:54:22] Speaker B: I am so glad to hear that. So as always, listeners, optimal hrv.com. You can find show notes, the YouTube videos, and I will promise to do my best to find a good topic to tempt Dr. Schaefer to come back on the show soon because I know we always get great feedbacks, my friend, for Winyon. So I thank you and I thank our listeners.
[00:54:47] Speaker C: Thank you.
[00:54:48] Speaker B: Take care.
