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The Melanie Avalon Biohacking Podcast Episode #86 - Harpreet Rai (Oura)

Harpreet Singh Rai is the Chief Executive Officer of Oura and a member of its board. His purpose is to be part of a team that is committed to improving population level health and wellbeing. He is responsible for Oura’s vision and strategy and guides decisions that ensure the organization's financial health. Before Oura, Harpreet was a portfolio manager who led the technology, media and telecom portfolio at Eminence Capital for 9 years. He began his career working in Morgan Stanley’s merger and acquisitions group. Harpreet studied electrical engineering at the University of Michigan.




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The Melanie Avalon Podcast Episode #76 - Harpreet Rai (Oura Ring)

7:55 - what is Oura ring?

10:20 - replacing the Oura; Is there a data transfer?

12:30 - if you change fingers will it change the data?

14:00 - Updating Baseline data

17:00 - the accuracy vs precision

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21:10 - calculating sleep stages

22:50 - algorithms and BMR Calculation

26:10 - collecting Data from Oura for the cOVID Study

The Pulse Blog

29:00 - Can Oura tell if you're getting sick?

30:55 - how to use the tags

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34:55 - making notes inside the app

35:35 - tracking women's fertility

37:30 - will there be a cycle tracker?

40:05 - Heart Rate Variability (HRV)

41:25 - optimizing hRV Data

43:05 - resting heart rate (RHR)

46:45 - The Oura Ring is Waterproof

47:10 - keeping it clean

47:25 - EMF

49:35 - adding workouts from previous day

52:30 - will there be an incorporation of CGM?

53:45 - imagining new capabilities


Melanie Avalon: Hi friends, welcome back to the show. I am so incredibly excited about the conversation that I am about to have. It is with a repeat guest. That's how you know you've got a good one. It is about a product that I personally use, adore, love, has changed my life. I literally mean that, especially after I released the first episode with this guest about the biohacking device. You guys, in the audience, love it as well. I decided it was so important that we bring him back for Part Two, for all of your questions, because I get so many questions about this, which is the Oura ring, which I am obsessed with. I'm so happy that I'm back here today with Harpreet Rai, the CEO of Oura and he's going to answer as many listener questions that we can get to, because I got a lot from you guys. Harpreet, thank you so much for being here.

Harpreet Rai: Melanie, thanks for having me back, and then also thanks for all the engagement and good questions from the audience. Hopefully I can answer some of them, might not be able to answer all of them, but we'll try.

Melanie Avalon: We'll see what we can do. In the interest of time for listeners, I will put in the show notes the link to the first interview that we did, because in that episode, we went deep into the science of Oura and heart rate variability. There's just so much information there. If you're not familiar with Oura at all, or want to learn more about heart rate variability, or just more foundational things about the ring, definitely listen to that episode, probably first, so you can have a foundation, and then this episode, we could just go all over the place with questions. To start things off, so I'm not going to ask you about your personal story, even though it was really wonderful for our listeners. It'll be in the first episode that I'll link to, in case you're wondering Oura ring what it is. Harpreet, what is the Oura ring? I'll start with that.

Harpreet Rai: The Oura ring is a wearable ring, we actually let users track their sleep, and other things like activity, but we holistically package it up to the user in something we called Readiness. That's the main score that you'll get in the app every day. What Readiness allows you to do is actually look at not just your sleep and activity patterns over the prior night and prior few weeks, but frankly, also physiological signals from your body that we get clues from every night. What time did your resting heart rate occur? What was your heart rate variability? How is that changing? What was your respiratory rate or changes in temperature? These signals, these physiological signals give us little sort of blueprints about your health and we try to present that all in an easy-to-use manner to the user, so they can start to understand what health decisions they made and how's that impacting their health and their performance.

Melanie Avalon: Okay, that was such a wonderful answer. Listeners, there's so many things Harpreet says that it tracks and you learn so much about you about how you're sleeping about if you actually are ready, like to what extent you should tackle the day as far as activity goes and things like that. I was nervous to get one because I thought that it would be a little bit overwhelming. If I didn't sleep well, then I would probably feel bad about myself based on the data that I received. But what I love about Oura ring and why just want everybody to get it is it is so approachable. It really makes me feel empowered. Never do you feel you're falling off the wagon, or the things are going bad. Even if you didn't sleep well, even if you aren't, don't have an optimal readiness score, it really speaks to you gently and nudges you back to a better place. I actually got feedback about that. Catherine, for example, she says, “I love mine. It's really so awesome. I love the meditation options, and the app is so much more than I thought it would be. I agree with you, Melanie Avalon, when you said it's not discouraging. The sad story is, I was wearing it all the time and I never travel, and I travelled this past weekend, and I never take it off. I don't know if I took it off, I don't know if it fell off. I lost it. Here I am without it for the first time in quite a while, which has made me realize even more how much I love it.” That's a question from me and a question from the listeners. If for whatever reason you need to get a new Oura ring, does your data just transfer over? For example, Rose says, she saw that there's a new ring, how does that impact the ring she just bought a month ago? And for me, when I get a new one.

Harpreet Rai: No, it's the same ring that was shipping a month ago that we've been shipping for over the last year and a half. They might have just seen a news article saying the new Oura ring, but it's the same ring. We haven't launched a new product. It's the same as it was in terms of your data, actually everything does transfer over. You actually set up the ring for the first time, you create an account, and if you've lost your ring and you buy a new ring when you set up the ring again, it'll ask you, “Hey, do you already have a login?” All you have to do is enter your login, which is just your email that you used to register, so all your data will transfer over. It'll be like you didn't even lose the ring. It’ll be a new ring that you just bought, but our same Gen 2 Oura ring, and all the data will just transfer over.

Melanie Avalon: Okay. Gen 2, so do you know, in the future when Gen 3 will be coming out?

Harpreet Rai: I don't know when a Gen 3 will be coming out. Nothing imminent that we know about or can talk about. I think we were constantly always investing in new hardware, and new sensing technology and new form factors. It's something that we're going to continue to do, but no, I don't think there's any media plans coming for in new Oura ring anytime soon.

Melanie Avalon: This is a question for me. Do you guys not make the diamond one anymore?

Harpreet Rai: Woo, I honestly don't know. I feel it's still there, but it may have been either-- because we do have that we work with a jeweler to actually inlay the diamonds on top. I know we don't sell that many, it's obviously not our best-selling model, given the price of the diamonds. But I believe we still sell them, I'm not entirely sure.

Melanie Avalon: I was looking for it and couldn't find it. I couldn’t try to track it down. Some other questions while we're talking about the actual ring itself. This is something I was wondering, Stephanie says, “If you change fingers, will the data change?”

Harpreet Rai: That's good question. The way the Oura ring works is we always come back to your personal baseline. The short answer is no, the data won't change. But even if it were to for some reason, let's say your temperature is 0.1 degrees different baseline on one finger versus the other. For example, if you use your thumb or your pinkie, because they're at the edge of your hand, not the core of your hand, not the middle three fingers, you may actually see a slight temperature change from one finger to the next. But the way that Oura ring’s algorithms work is we actually relearn your baseline, that's how we personalize all of your data and all of your scores. The short answer is no, it won't change. Even if it were to change slightly, you'd be back to a new baseline in two weeks. You don't have anything to worry about. Sorry, if that answer was too technical, but I'd rather explain that given your audience I know want to understand how that some of this stuff work.

One thing you may see change is actually your battery life. In general, you shouldn't, but some people have certain fingers that might have a little bit worse of a pulse signal or weaker or stronger, but the most you'd see the battery life affected is 10% difference or something like that. If we see someone who has a weaker pulse, we will increase the power that we use to make sure that we still see good robust data.

Melanie Avalon: I actually have a question about that baseline. Does Oura reevaluate your baseline to make sure your baseline is still your baseline? Or, does it determine it in the beginning and then pretty much sticks to it unless you are doing things that you just mentioned?

Harpreet Rai: No, great question. We actually use a rolling baseline. Your baseline is always reevaluating for different metrics on a rolling basis. For example, if you lower your heart rate, because you're starting to really exercise again, do a lot of cardio, and if you lose a lot of weight, you'll see your resting heart rate decrease. One of the, for example, things we look at is Recovery Index, and your resting heart rate and absolute value in the Readiness score, and that will readjust to getting to know your new birth baseline as you keep improving it. I think the saying maybe like the only person you're competing against is your own self. The cool thing is, we're always changing and hence, the baseline is always re-averaging constantly.

Melanie Avalon: I love that so much. I was really thinking about it in particular, because I've noticed when I changed my macros, so if I'm doing high carb, low fat or low carb, high fat, it seems to have a very pronounced effect on my body temperature. I was just thinking about if I were committing to one of those diets for any amount of time, I feel my baseline temperature might change.

Harpreet Rai: Yeah. Honestly, we've even seen cases where people are frankly learning how to-- because thyroid medication. Anyone who has had severe thyroid issues knows that there's a while where you and your doctor will have to get your thyroid medication, redo a blood test, make sure that your TSH, FSH levels are all good and there's a lot of tweaking that needs to be done and calibrating the right dosage amount. We've seen other people also realize that and see some of those changes, for example, in their temperature when they're changing their thyroid medication dosage. But the good thing is we've taken those things into account and we're always constantly reevaluating and reupdating your baseline.

Melanie Avalon: I love hearing that. I was also wondering because it says when you wear it to have the sensors, I believe, on the bottom part of your finger, if it's moving around on your finger is that making a huge difference?

Harpreet Rai: Not really. Again, the only thing is sort of battery life. The sensors do work optimally if they're on the palm side of your finger. If there's too much rotating or spinning, there may be too much noise in the data for us to feel like it's robust enough to be accurate. You may see at certain points what we call sort of holes in your data, if you looked at your HRV curve, or your HR curve. But frankly, some people just may start to realize that they just orient the ring, the top as the top and the sensors are at the bottom when they sleep, that should be fine. Most of the time, there's no impact to the data quality, what ends up happening is it just takes a little bit more battery power to sensitive the ring is turned all the way 90 degrees to the side. Most of the time, it's fine.

Melanie Avalon: Have you guys seen data on accuracy versus precision with the ring?

Harpreet Rai: Ooh, on which metric?

Melanie Avalon: I guess, any of them in general?

Harpreet Rai: Yeah. I would say heart rate variability and even things like respiratory rate, something that's like a physiological signal, that is both accurate and precise. Now, sleep data, for example, sleep staging is based on brainwaves. In your REM sleep, your brain frequency waves are higher than for example, if you're in deep sleep. So, what we do, and other wearables do, is we train lots and lots of all the raw data and sensors and physiological signals coming off against polysomnography or brainwave data from a sleep study. If you do that enough, you can start to see really cool patterns and use old types of machine learning models, and you can create an awesome algorithm. Because you're interpreting now many different physiological signals, and you're correlating them to a brainwave signal, when you do that, there's lots of different ways of the algorithm you can make.

We specifically have chosen our algorithm while to be as accurate as we can, even favor more precision. The reason is that's the use case on how you use the product. You, let's say for example, have 45 minutes of deep sleep, or if it's 40 minutes, or even 35 minutes, that may be your deep sleep, that matters on an absolute level basis. What actually really matters and how you use the product is seeing the changes, “Oh, if you drink a lot of alcohol one night, your deep sleep may go down a lot,” and you want to be able to see that relative change very precisely. We've focused our algorithm on that, because that ends up teaching people, actually, “Hey, here are lifestyle decisions that are actually improving my data or hurting my data.” I think it's that mentality that we found and how users actually use the product that really matters. We favored our algorithms for sleep staging more towards precision.

Melanie Avalon: Awesome. For listeners, just briefly, accuracy is basically how accurate the actual measure is, of whatever it's measuring. Then precision shows how accurate are the different measurements in relation to each other. Just some clarification. You actually addressed two questions that we have with that answer that you just gave. Lindsey said, “How can the Oura ring identify the different stages of sleep?” It sounds like you're using an algorithm, is it looking at heart rate variability as to how it related to brainwaves?

Harpreet Rai: We look at every single sensor and every single thing we measure. Anytime we're forming an algorithm. Some of the direct measures we have our movement. It's on your finger and we have an accelerometer and a gyroscope, and you can see movement in many different axes but the main axes for accelerometers are X, Y and Z, so we use that data. We use heart rate variability data, we use respiratory rate data, we use temperature data, and we use all those different data streams. We actually compare that against brainwaves from a polysomnography device. We take all the raw Oura ring data that you can get off at the highest frequency that you can get it and store it in and we compare that against all the polysomnography data that comes off those machines. Some of those are 16-lead polysomnography machine, some are even north of 32. I think that's a little bit on how algorithm processes made.

For example, that's just for sleep staging, but you'd go through the same process frankly, if you're trying to do activity detection. You'd get someone wearing an EKG, think of them go, I don't know, go do a certain type of-- rowing versus Stairmaster or snowboarding or skiing. Same thing, you'd compare that sort of reference data against all the raw data coming off an Oura ring, and you'd create your algorithm that way. That's how all these wearables basically do algorithm creation.

Melanie Avalon: Awesome. You actually just answered, because Stephanie's question was, “What formula do you use to estimate your BMR for the activity calories?” It just sounds it's very complicated.

Harpreet Rai: We actually look at METs. We measure METs, and then we also look at things like, “Oh, yeah, all the raw acceleration data that's coming off of the accelerometer" to figure that out.” I think, yeah, it ultimately you can tune, frankly, this data, you can create algorithms almost against any reference data point. For example, COVID, we all talk about another one, woman's health. During COVID, we're still ongoing in a study with UCSF and UCSD and over 70,000 Oura ring users who enrolled in this study. As part of that study, there's a reference dataset. If you're in that study, and you opt in, and it looks like you may have gotten sick, UCSF will email you and say, “Hey, can we send you a COVID test?” They send you that COVID test to get definitive gold standard reference data. Then, you can compare that against-- we have symptoms surveys that people were taking every day in the app, and we have all the Oura ring data. The researchers will look at that and say, “Here's a gold standard. Here's all the different data streams we saw off an Oura ring.” Boom, we can use all that data and create an algorithm that actually looks pretty good.

I think there was a good research study showing this for women's health. Actually, I think it's an open medical journal and scientific reports researcher named Azure Grant at Berkeley, who's fantastic. She actually took, I want to say, maybe getting some of the specifics wrong, but it's like over 35 women, and looked at them for three different cycles each, they looked at luteinizing hormone, I believe it was saliva, or urine or blood, or I don't know I forget which one, it might have been two of the three. They also looked at basal body temperature every single morning using oral thermometer and also looked at temperature iButton sensors, which lots of research studies use. They were able to use that and compare it against, again, all the raw data coming off an Oura ring, the minute-by-minute temperature data we have along with actually the heart rate, heart rate variability, respiratory rate sleep, etc. What she showed in that paper-- actually not many people have seen this yet, just because the paper came out the same time during a lot of our wearables work with COVID, I felt unfortunately got overshadowed. What that paper showed was actually using this data and an algorithm, a researcher was able to show that with over 90% of women they could see luteinizing hormone one or two days in advance of the saliva test, which is huge, has huge implications for managing women's health, whether you're trying to get pregnant or not, or even relative things and the strength of how much luteinizing hormone any person may have. It was fascinating. You can train these algorithms against any reference data, whether that's a COVID test, LH, luteinizing hormone test, polysomnography test, brainwaves. Hopefully, that helps explain a little bit the process on how algorithms can get created.

Melanie Avalon: This is so incredible. I had a lot of questions about that. Denise, she actually did participate in the COVID study that you just talked about. She wanted to know if they had any interesting data yet that they were able to report on what they found?

Harpreet Rai: Yeah, I think we share this on our blog, and also UCSF put it out on their website, and it was published in a medical journal and scientific reports, which is the medical journal, Nature, they're open access version online. For the COVID study, what they showed was that, actually, for a majority of people, the data from Oura ring could see, there were significant changes in the data three days in advance before users reporting any symptoms.

Melanie Avalon: Oh, wow.

Harpreet Rai: Yeah. that was for, I think, over 75% of the participants so far. They, I think, took the first 50 cases and analyzed them quickly, because they want to get the paper out. I know they're analyzing now the several 100 cases of positive COVID data, that's in that data set. So, they'll have a follow up with even more data. But the early results were so impressive, I know they wanted to get it out. Something like 38 of the first 50 subjects saw a significant change in the data three days in advance before reporting symptoms. I think another 14% of subjects saw significant changes one to two days before reporting symptoms, they saw changes, again, in the data before the symptom onset. Then, it was 10% of people that they saw symptom onset at the same time their data was significantly changing. I think frankly that was remarkable. I argue that because of the rich HR, HRV data, but frankly, also the minute-by-minute temperature data we have that other wearables don't have on the wrist. Also, respiratory rate was helpful. But it's all four of those that were extremely helpful and identifying these changes well in advance.

We've had two other research studies come out, and actually share similar-type findings. There's another study during COVID that was funded by Defense Innovation Unit, and they worked with Texas A&M and Philips, and this is out there on a website as well, that DIU, Defense Innovation put out, and they were using Oura rings and they were able to spot an outbreak among soldiers more than two days in advance of people reporting any symptoms. Then, even the Rockefeller Neuroscience Institute at West Virginia, it was actually pretty-- there were the first ones in their study to come out and put an early press release out, just saying, “Hey, we're seeing changes up to three days in advance to people reporting symptoms." It's been really cool to see three different independent research groups arrive at pretty similar conclusions.

Melanie Avalon: That is so cool. For listeners, I'll put links in the show notes to all the studies that are available on the blog post from your website. The show notes for this show, again, are at melanieavalon.com/ouraring2. I have not become sick while using the ring at present. Does it tell you if it thinks you're getting sick?

Harpreet Rai: Yeah. We have something called Rest Mode, that's new, and that we launched during COVID. Rather than call it Sick Mode, we felt it's more appropriate. “Oh, what should you do if it looks date looks like you're getting sick?” “Well, we'll rest.” I think now you'll see a trigger in the app or, I shouldn’t say trigger, but like an option to enable Rest Mode. The insight messages you get are the same, that, “Hey, it looks like your body temperature is elevated,” or “Your heart rate's up quite a bit. It looks like you may be getting sick, you may want to take it easy.” We'll get that message in the Readiness card, like you always would, but then you have an option actually in the app to turn on Rest Mode.

What that does is, some of the things like your activity targets, or even different scores in the app will actually adjust or turn off. We actually turn off the activity score, and don't set the activity guidance for days that Rest Mode is enabled. It's not just COVID. If you're getting any type of cold or illness, you may see Rest Mode get triggered. Frankly, even if you had like a really, really bad hangover, you may see a trigger for that too. We asked users to tag because we say, “Hey, does it look like you're getting sick? Does it even look like you got a vaccine?” That's an interesting tag we're starting to get. "Does it look like you had a lot of alcohol?" That lets us help and learn more about how we can keep specifying all the different use cases, that may present themselves somewhat similarly, but all slightly different, and the data. Once Rest Mode’s turned on, we encourage users to give us a little bit more feedback so we can help keep improving the algorithm and keep getting better for the sake of all of the users on the platform.

Melanie Avalon: I'm so glad you just mentioned tags, that was a question I had and Allison had. I hadn't actually used the tags before. Allison said, “Tags, how do we use them?” Does it give you options or do you write it in yourself? I hadn't used them.

Harpreet Rai: We actually allow you to do both. If you open the app, and you actually hit the plus sign, you'll see an option to enter a tag. You can actually make what we call a manual tag. We have a timestamp, date, and time. There's also now a long list that you can choose from. What's really interesting is now if you go into the Trends section of the app, and one of the areas you'll be able to see like-- for example, for me, I've been using the sauna a lot, I’ll actually have in my tags. The days I'm using the sauna, if I looked at my HRV, it's pretty cool to be able to see a pretty interesting correlation. Oh, well, for me, I can see that on the days that I have tagged, I see that in my trend data over a week over a month over several months or several days, a clear improvement for me in my data when I'm using the sauna. I think that's pretty one of the reasons we made it. We're going to keep improving and working on that. The more tags we see from other users, the more we can learn and start to suggest tags to other users. It's definitely every Oura ring user who tags is helping us learn so we can help other Oura ring tag easier in the future.

Melanie Avalon: Pamela, she said, “I would like a place to enter notes on each of the screens for my purposes only, that would give what was going on for the results achieved.” Could she use the tags or do you think there'll be an update in the future where people can add in more detailed notes?

Harpreet Rai: You can actually in that manual tag area and when you go to new tag entry, you can actually write a pretty in depth note. Yeah, it's actually pretty cool. It's worth exploring. That may not seem obvious, but yeah, we've allowed for that capability.

Melanie Avalon: Then, I did want to come back. You were talking about the fertility and everything with women, I got so many questions about that people were really excited. I'll just go through some of these, and you've sort of already addressed it. Casey said, “Are you planning on tracking basal temp changes to track fertility windows?” I guess, with the software, will we be able to actually see fertility windows at some point in the ring?

Harpreet Rai: Yeah, I think actually if you go already, we've done a blog post on this pretty in depth. That's definitely one we can share with you, Melanie, to share with the users in the audience and the community that you have. If you go to the temperature trends, you can actually see some of that already, just in the way that the temperature, it almost looks like a sinusoidal pattern, like a sine wave. You can actually see some of that already. We're working to improve that to make it even more obvious. Now, there are unfortunately, I think, as a wearable what you can and can't say in an app to a user, that triggers an FDA review, is a pretty narrow line.

Melanie Avalon: Probably intense.

Harpreet Rai: Yeah, so I think saying, “Hey, this is your fertile window.” The FDA, one of the things they always look at is, “Are you diagnosing or treating? If so, then it's a medical device." We don't want to intend to diagnose anyone that this is your actual fertile window. What we can show is, “Hey, here's data. By the way, here's a research study that was done that suggests when this is happening, the data, this may be happening.” I think that's the approach we've taken, but we're treading that line carefully, we get their input, we want to make sure we're not crossing the line, yet still providing actionable information to the user.

Melanie Avalon: I can only imagine the headache of navigating that line. To that point also, is the Oura ring at present taking into account those cycles when it's giving scores? What I mean by that further is, Sophia says, “When my temperature goes up right before menstruation, it gives me a lowered score. Would it be possible to put a cycle tracker in it so that it takes fluctuations in temperature into account?” Or, is it already doing that? I'm wondering.

Harpreet Rai: It's a great question. Frankly, I think this is a really interesting area in technology design, in general. Not enough companies, including ourselves, have done enough to honestly personalize the user experience for both genders. Especially in the wearable space, I think too many companies, and we're working to improve and I'll describe what we've done in a minute, have just taken, “Oh, most of this audience is male. Here's how we've designed this technology for them.” For example, what we've done is when we recognize a woman is cycling, we actually change the way the Readiness messages are written. Instead, we've now fixed it, so you won't get a penalizing message that it looks like you're sick or you have a fever. We've specifically done that and gotten rid of majority of the time we think when that may happen and triggering the incorrect user.

Over time, we're actually trying to do more research on this now, what would be the appropriate alterations in a score given that's happening. We're doing some good research on that, and also user design and getting feedback for what people actually really want, what women want when that's happening. Some may want to know that, “Hey, no, look, your heart rate is up. Your heart rate variability may be down. Your temperatures up a bit. Your respiratory rate may be changing.” There's certain women who use that data actually specifically for trying to figure out the best days and hardest days to train for them. There are certain women who are saying, “No, to me, regardless of that happening, I want the algorithm to adjust for me, and I'll figure that out myself.” We're trying to do more user feedback now. We're doing more research in this area. I think you'll see a couple more women's health related studies coming out that users are able to opt into in the future coming in the next few months.

Melanie Avalon: I love hearing that so much. I think that's not a complete blackhole, but it is a problem with modern research and science, the general lack of attention to the difference in the gender. I remember when I read David Sinclair's book, Lifespan, I'm trying to remember exactly what it said but it talked about how in rodent trials, I'm probably misquoting, but I think male rodents respond better to, I think, pharmaceutical interventions, whereas female rodents responded better to, I think, diet and lifestyle. It just has so much implications for so much, like the information that we're learning about different things. Heart rate variability, we've been using that word a lot. Again, listeners, if you listen to the first episode, Harpreet goes deep, deep into the science. Can you say briefly what heart rate variability is?

Harpreet Rai: Yeah. We did definitely talk about it in depth last time, which was fun. Thanks for all the great questions, Melanie. Heart rate variability is really being used more and more as a sign for stress, whether it's physical stress or mental stress. I would say it's precise, maybe not specific to the type of stress. Most of our users are using heart rate variability as a way to figure out how hard they should train, how well they're recovered, or even how in general they may be stressed out and if they should alter either their training or even their schedules to match for that. I can tell you when I have really heavy intense period of meetings or board meetings, or certain meetings with potential customers or partnerships, it reflects in my data. I use heart rate variability that way to really figure out, “Man, I've got too many meetings going on right now, I need to slow it down a bit and focus.” There's lots of different ways to use heart rate variability, but the best way I think about it is as a measure for stress.

Melanie Avalon: Amy had a good question about it, she said, “Is HRV something to strive to continually improve or is it more of a thing where if you're in a certain range, you're good?”

Harpreet Rai: That's a good question. I think people can optimize their HRV, I think it's good to actually learn about what lifestyle decisions you make that impact it, and how your body handles with stress. I've had certain people tell me that-- let's say they work in the finance world, and they work in trading stocks. If a certain stock is down a lot and their portfolio performance is doing really bad, they'll see their HRV tank. I've seen other people telling me that, “I got in a fight with my loved one. I was really upset and really emotional and I saw my HRV really go down.” I found other users who say, “Man, I use HRV as the sole metric on how hard I should train that day.” Marco Altini, actually, he's an advisor at Oura, and started the app called HRV4Training, getting HRV measurements, even just from your camera phone, and he pulls in data from other wearables like Oura. I think he uses HRV primarily for training and tries to figure out how hard his training load should be just based on his HRV response. To that question, I'd say, it's actually more about the changes in your own HRV and how you use that to make different health decisions and in your lifestyle.

Melanie Avalon: Again, going back to the individual person. This is a question I really had about resting heart rate versus HRV and showing the averages versus the lowest. Then, Diane asked that. She said, “Resting heart rate is one of the daily metrics reported in the dashboard area towards both of the Sleep and Readiness pages in the app. The number that is displayed here seems to be the lowest that our heart rate ever drops all night. Why is that? Versus displaying the overall average for the entire duration of the sleep. And/or why should I care about that lowest moment, which may account for just a tiny percent of the whole night versus the overall average?”

Harpreet Rai: Yeah. It's a great question. if you're in the Sleep or Readiness section, and you look at the heart rate graphs, we actually show both, the lowest heart rate and the average. You can see that dotted blue line that shows the average. Actually, in the Trends view, which you can get to in the top left menu, just go into Trends, you can actually also track both your average, your resting heart rate, I think-- actually, we may have taken the average out, I'm actually trying to remember if we did or not. I guess we did, it's your lowest resting heart rate. The reason we look at lowest resting heart rate is that it's another sign of stress, and how well recovered you are that's relative to you. The timing of your resting heart rate actually matters quite a bit, whether that your lowest resting heart rate happens at the beginning, middle or end of the night, and we have a good blog post sort of explaining that, and how hormonally actually looking at the middle of the night is really probably the best. If it happens earlier, it may mean you're not getting enough stimulation or even physical stress in your life. If it happens very late, that can be a sign of late meals, having too much alcohol or frankly, even too much physical stress.

But I think Literature has shown that your lowest resting heart rate can actually be really interesting to look at night to night to be able to get some of those clues in the data. Your average is actually less likely to change because it's your average. As a result, you may not be able to actually see enough feedback in your data to recognize that you did something that was something that actually helped or hurt in your own data. That's the reason we focus on resting. I'm just taking a look at my own data here to perhaps prove that point. I'm pulling up my app. If I looked at my data between my last few days, my lowest resting heart rate may change as much as 5% but my average is changing 2%. There may not be enough of like a change in the data, just by looking at average for the user to gain a benefit from, versus looking at the lowest.

Melanie Avalon: So, it's a more definitive warning sign. It's like you have to know somebody really well to look for little signs that something might be off. It's like the Oura ring knows you really well.

Harpreet Rai: That's the hard thing about health. You have to look for and figure out the signs and clues for you by focusing on certain metrics, you think about them as almost these biometrics, or physiological blueprints, these signals that we try to pull out that we think users can start to learn from. If I look at my resting heart rate, I can tell you, this week, my lowest resting heart rate has been 100% correlated to it being lower on the nights that I use the sauna. My average night, my average HR, heart rate, didn't actually change that much during those nights. Maybe one or two beats, but not three or four beats where I actually noticed a difference from my baseline.

Melanie Avalon: It's also perfect, because Rose wanted to know if you can wear it in an infrared sauna.

Harpreet Rai: Yes.

Melanie Avalon: That's a yes.

Harpreet Rai: Yeah, you can. You can go diving with an Oura ring. It's basically waterproof to 150 meters. You can go and really, really cold weather. I don't know how cold, and really, really hot. I know I have an infrared sauna at 150 degrees. I know so many of our users, especially in Finland where our company has started, use way hotter saunas, and it's fine.

Melanie Avalon: Veronica was wondering about when you get soap on it, is that a problem?

Harpreet Rai: Not a problem. We do encourage users, if you've buildup on your ring, just to rinse it off to make sure that, there's not dried soap sitting on the LEDs or anything.

Melanie Avalon: Okay. You answered this last time, it's one of the biggest questions that I get all the time and that is about the EMF exposure. Stacy says, “The only thing holding me back from getting one is the EMF. How much is it? Has it been measured?" My guess is that it's not enough to maybe make a negative impact?

Harpreet Rai: We specifically have focused on infrared light, and not green light for measuring your heart rate and heart rate variability at night, partially because the user doesn't see it and doesn't bother them. Actually, we also know from medical research that everything that infrared wavelength is actually beneficial for your health. Obviously, you don't see it, so you don't wake up to it like you would to the green lights from a Fitbit or Whoop at night. That's one of the reasons we use infrared for that EMF reason. The other thing that we've done that other wearables have in is, we actually have an airplane mode. You can actually turn off the Bluetooth, and the ring will still store all your data for actually several days, and the way you turn the airplane mode off is, you pop the ring back on the charger and you open the app, and then we recognize it and turn the airplane mode off. So, you can actually stop any of the Bluetooth transmission from happening. We don't honestly ping the Bluetooth to your phone that often to upload data, and there's always sort of design trade-off. Some people want to be able to look at that and seeing instantaneously when you open the app, for tracking your steps, but frankly, I think if you just wait a couple seconds with the app open, it'll ping the Bluetooth anyway. That's not that big of a burden. We think that transmission is not doing it so frequently is better for EMF. I know we transmit way less than most other wearables.

Melanie Avalon: I'm very EMF concerned, and I felt very comfortable with Oura. I put it in airplane mode when I sleep and it's just really fantastic.

Harpreet Rai: It's also a reason why we don't have any other screens. Your Fitbit, your Garmin, your Apple Watch, they all have screens and so we know those screens are emitting EMF, and so we didn't want a screen. We felt like there's enough distractions in our life, let alone the EMF exposure from all the constant pings. Why not have something that seamlessly, blends in, you can yet still go look at super granular data when you want to.

Melanie Avalon: I love it. It makes me so happy. Some very last quick questions about the future of at all. Well, this is an update I actually would love to see and Betty also asked about it. She said, “Will we be able to make it so that we can add workouts for the previous day, not only the day of. Sometimes I work a night shift and it hits 12, and I haven't put in my workouts and then I can't add them the next day.” I realized this as well because I go to bed late and sometimes, I try to retroactively add and workouts, but you can only add it for that day. Do you know that'll be an update in the future?

Harpreet Rai: It will, but we actually have recently made a new update too. Now, you'll actually get a prompt if you've done a workout or activity and you haven't tagged it. We actually launched something called Automatic Activity Detection. What we were able to do is we took all the health kit data, Google Fit data, and manual workouts that people have entered and we looked at that data against our sensor data, our accelerometer, gyro, etc. We've now actually made it so that if you do a workout and you open the app, you should get a suggestion, depending on the type of workout on what it might have been. I know we just had a couple of users reach out recently, because it's ski season and they're like, “I just went snowboarding. My Oura ring asked me afterwards, was I just snowboarding?”

Melanie Avalon: Oh, and it said snowboarding?

Harpreet Rai: Yeah, it said snowboarding.

Melanie Avalon: That's so cool.

Harpreet Rai: Yeah. It's actually one of those things where we personalize that activity detection to you. Now, if you actually enter a workout a few times manually, or if we suggest something and you confirm it or reject it and correct it, we start to learn and actually get more personalized, so we'll automatically add that activity. We still give you the prompt, just to confirm. For example, I went for a walk this morning for 25 minutes and you could actually see that when I open my app the next time, it said, “Hey, did you just go for a walk?” I said, “Yes,” and it guessed my intensity, and my how long, and it keeps getting better and better tuned to you. If you don't see that, after you perform an activity, we do ask that we learn from you, so if you tag it a few times, we should learn it, and start recognizing it. Then we actually again use the data from all of our users. It's almost like for us, by us. Becoming a platform that the more you tag, it's not just for you, we'll actually use that for other users. We then start to suggest, “Hey, did you tag?”

But, Melanie, getting specifically to your question, so now when you open the app in the morning, if you didn't tag an activity, the day before, we’ll actually ask you, we will be like, “Hey, did you not tag this today before?” We will start to prompt you the morning. Yeah, so you'll actually get that reminder and they'll be added to your activity score from the day before once you confirm it.

Melanie Avalon: Perfect. Then also looking to the future, a lot of my listeners use continuous glucose monitors. Carol wanted to know if there's any chance of that being incorporated in the future.

Harpreet Rai: Ooh, I can't wait. I think it's so cool to see so many companies starting to do this., I know there's Levels. I forget some. Supersapiens, I want to say, and I want to say January.

Melanie Avalon: Nutrisense.

Harpreet Rai: Yeah, and obviously Dexcom and Abbott being the two medical device versions or two of the main medical device versions and others more now. Medtronic, I think has one too, I forget what it's called. Yeah, we're looking to integrate more and more with those. We do pull in data from Apple HealthKit and Google Fit, if our users consent to us doing that and want to see that integrated. We hope that there can be more continuous glucose streams there. We hope that more and more APIs from those partners are developed, so we can start to integrate and pull in that data, because the link is fascinating. We know that research suggests if you get less sleep, your insulin response gets way worse. Your resting glucose levels, your fasting glucose levels unfortunately increase. So, we know there's a huge, huge correlation between your insulin response, your fasting glucose levels, and your lack of sleep.

Melanie Avalon: Then I have a million more questions from listeners, but the lucky last winner question is from Deb. She says, “If they could magically give the ring extra capabilities beyond what it has now, what would they be understanding that sometimes technology trails behind our imaginations?”

Harpreet Rai: Wow. There's so many. Every person in our team has their own wish list. Look, there's great work being done with wearables and blood pressure and hypertension. I think there's a lot more work we can do in pioneering this space for wearables and women's health. Even sleep apnea is super fascinating to us. I think even early onset of dementia we know now in Alzheimer's is caused by poor deep sleep. So, I would love to be able to learn more how we can do that for users that are starting to age, get sort of above 40, 50, 60, 70. I feel there's so many different use cases. It's honestly what makes doing this so fun. There's so many ways to potentially help people.

I was talking to someone recently who runs a large company that has a lot of acute care patients. One of the biggest problems in acute care can be ventilations, and getting off the ventilator. It turns out that it's a really manual process today where you're in an ICU-like setting, you want to wean, you don't want them to be on the vent too long, because your body honestly gets weaker. It gets too reliant on the vent, and you need to slowly wean it off because if you wean it off too fast, you may have some type of COPD event. I think there's so many cool use cases for the future wearables that there's no shortage of things that can potentially help people.

Melanie Avalon: This is absolutely incredible. That makes me even more grateful for the Oura ring, for the work that you're doing. Listeners, if you don't have one already, get one right now. The second I lost mine, I was like, it's not even a question, I'm getting another one right now. It's absolutely amazing. The last question I always ask every guest on this show, and it's something you might remember from last time, but it's just because I think mindset is so important. What is something that you're grateful for?

Harpreet Rai: I just started journaling this one, but actually recently, I'm writing it down at night. Then, I glanced at it first thing in the morning, before I start working. Let's see, where was I last night?

Melanie Avalon: Oh, yay, I love this. [laughs]

Harpreet Rai: I wrote, “I'm grateful for all the challenges I have in front of me that I can learn from.” That was just the one from last night. Luckily, that was not too personal. [laughs]

Melanie Avalon: You're in the clear. Well, thank you, Harpreet. This has been amazing. I am so grateful for everything that you're doing. Again, I cannot recommend listeners enough. Check out the show notes, read more about it, get an Oura ring. You will not regret it. Hopefully, we can do a part three in the future.

Harpreet Rai: Yeah, definitely. Actually, Melanie, I want to say another thing I'm grateful for. It's not just me, there's no one person that can do this stuff. It's our team at Oura, so grateful for the team that we have and that we're building. It doesn't just take a village, it's taken an army, that's frankly all aligned in helping people. And I'm honestly grateful for you and your audience. I think you've been pulling together such passionate people and teaching them about health, and then seeing the community engage the way that you have. Thanks for doing that as well. Really, really appreciate it.

Melanie Avalon: Well, thank you. I'm just smiling. This has been absolutely wonderful. Thank you for your time. We'll talk again in the near future. Thank you. Bye.

Harpreet Rai: Bye.

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