BoneChat #131 - Lessons learned building wearables for orthopedics

So this is BoneChat Discussion 131. Today we're diving into the world of wearables and remote monitoring with returning guest Lisa Voronkova. She's a medtech hardware entrepreneur. I think that's the best way to say it. She's the CEO of Ossia. Ova Solutions. Many of you may remember her from Comeback Mobility, where she led the development of smart crutch sensors that provided real-time feedback for post-op orthopedics. Today, Lisa's going to share lessons learned in developing wearables. So turn over the mic to Lisa. Don't be shy, raise your hand. Welcome aboard. Thank you.

So thank you, Tiger, and thanks everyone for being here. Yes, I got— I started working with Comeback Mobility a couple of years ago.

Couple years ago.

Was in parallel with my main activity. So basically I'm running an R&D shop for medical devices, but sometimes we're getting too involved with the startups we are working with. So, uh, in this specific case, I got, um, CTO position in Comeback Mobility. And so I know this, this room is a mix, so I saw the list of participants and I know there are founders, surgeons, and people who invest in the space. So I try to make this pitch useful for all of you and gonna keep it plain. So the title of this talk is Wearable Electronics in Orthopedics and Why We Think It's All Moving to Patches, What It Gives to Doctor. So that's, that's a long title. So let me try to explain it in one line.

Okay.

The most useful data about your patient is not collected in your clinic, it's collected at home. And the device that collects it is getting so small that it's about to disappear into the body. So that's the whole talk. Let me show— Show you what I mean. Um, quick context on why I'm the one talking today. So my team and I built medical devices for a living, and we're a bit over 60 engineers. We shipped more than 200 devices. We designed over 200 devices and more than 60% of them either passed clinical trials or on the market already. We're mostly focusing on Class 2 and 3 devices, but sometimes we work with wellness devices, sometimes we do Class 1 devices. We've been working together for over 10 years for now. Wow. And I also wrote a book that is called Hardware Bible. It's on Amazon on how to build a medical device from idea to the production line, to actually to the market, I would basically say. So I'm telling you that for one reason only, so that everything after this lands as things we have actually built, not just slides or resources that you can make yourself and Google, right? So I just want to give a clear map of where this field is going in our opinion.

Mm-hmm.

And, um, the engineering that decides who wins it. So here is the thing that— Here, uh, that started this for me. So this— there are like 168 hours in a week, and if your patient is doing well, you might see them for one of those hours, maybe less. So think about what that means. In the clinic, you get a snapshot, like a single frame. The patient walks in, they're nervous, they're on their best behavior, and you measure them for a couple of minutes, but the real recovery doesn't happen in this frame. So it happens in the other 167 hours at home when no one is watching. And that is where the swelling goes up or down. And that is where the muscle either wakes up or stays asleep. And that's where good recovery and bad recovery can be separated. Right. And here's the uncomfortable part about this process. This few minutes you do get might be the least honest minutes of the week. Right. So the patient rested before the visit, they pushed through the pain to walk straight to you. The clinic is one place where they're not living their normal life. So, for a long time, that real life that happens outside wasn't visible. And the whole point of wearable electronics is to make it visible. Let me show you how fast the hardware is shrinking right now. So, 3 weeks ago, like end of May, Oura released the Ring 5, and all the press releases were naming it the smallest smart ring in the world. So it's about 40—

Yes.

This one. It's about 40% smaller than the ring before it, and it's about like a third lighter. The battery still runs up to 9 days. Amazing. And just let's think about it. You have full computer with motion sensors, temperature sensors, heart sensor, radio, battery, sits inside the ring so light that you forget that you're wearing it. Right. And what we observed over the last 5 years, that the electronics did not just get better. They got small enough to vanish on the body. And once that happens, The ring and the watch are not the final shape. We think that the next shape is a patch. So think of something like a Band-Aid, like thin sticker you put right on the spot you care about. And after the patch, maybe as a next step, the sensor goes one step further. It goes inside, like into the implant, into the bone itself. So that move from the wrist to the patch to the bone is the line of what we see, like, the market is moving towards. Um, so yeah, I'm going to do 3 things quickly. First, like, the map where the money, the products actually are right now. Second, what this does for you in your real day for 2 real problems for the doctor, right? And third is an engineering perspective— why adding a sensor is the easy part, and what actually decides whether one of these devices ships or dies. So let's start with the map. Wearables in orthopedics split into two simple groups. So the first group is the diagnosing screen. This watch how a person moves, their walk, their motion, load on the foot, uh, like a Gait Lab analysis or a pressure mat, but shrunk down so the patient can wear it at home. So you use it to find a problem or to follow a condition over time. And the second group is treat and control. So this is the one around the procedure, before surgery, during surgery, after the surgery, and through the rehabilitation process. So this is the group tied to the operating room and the recovery ward. And most of the noise you hear is about the first group because consumer fitness lives here. So like rings, watches, step counters, but the real value for the— you, like, as a person involved in medicine, for the clinical value, sits in the second group. So the one is tied to the operation and the recovery. And that's the part, uh, that is still pretty wide open if you look into the market. And that's where I'm going to spend most of my time today. So the market itself, the market for electronic skin patches, the stick-on kind, is already around $18 to $19 billion this year. It's not a big number, but it's growing really fast. And it's growing, as you can see, every year. In fact, keeps compounding. And here's the part that matters for this room. One of the biggest drivers of what grows is not fitness. It's telemedicine and remote monitoring. So sending the patient home, but still watching them over time. And the big slice of that is offshore.

Mm-hmm.

Surgery and during the rehabilitation. And it's not a someday idea because remote monitoring after an operation is already a real product category. I know that some of you in this room build it. So, one simple piece already on the market is a temperature patch. So, used to catch infection and follow healing after a procedure. And there is a business reason for the hospitals to purchase that, not just for doctors, because remote monitoring takes a lot of the stuff. It lets the nurse to keep an eye on many patients at once. It saves the, the resource in the whole building, which is their time. So fewer beds tied up, fewer visits for things that turn out fine, right? So the direction of the money is clear. It's just— pointing straight at post-operation and recovery. So, here is the one trend that ties the whole field together: miniaturization. So, something that is pushing the sensor closer and closer to the thing you actually want to measure. So, it's again, as I said, it started on the wrist, then it moved to the patch in the skin, and the next step is inside, um, like the implant or in the bone. And there is a simple reason for that. The closer the sensor sits to the source of the signal, the cleaner you get the data. So on the wrist, you're guessing about the knee, right? On the knee, you're measuring the knee, and inside of the knee, you're measuring the joint itself. And let's keep this idea, uh, that closer to the source, cleaner the signal. Uh, I'm gonna come back to this. later. Now, uh, let's, let's get like more practical, talk about the day of the doctor. Because when I talk to orthopedic surgeons, the interest is not really in diagnosis. Uh, by the time someone is your patient, the diagnosis like is already clear. The interest is in two things: one, doing a procedure well and keeping inflammation under control, And second, controlling the recovery after. So two problems: inflammation and recovery. And good news is that wearable maps almost perfectly onto those two. So, uh, let's talk about them one at a time. So problem one: the quality of healing and catching inflammation early. So the simplest useful thing we can do today is It's small and it works. So you finish the operation and you place a patch right on the area. That patch will watch the local temperature continuously with the patient being elsewhere, like at home. Why temperature? Well, because we all know that post-op window, you know it better than I do. So rise in local temperature, uh, how high it goes and how long it stays is one of the easiest signs that something is off, like infection, inflammation, something is not right. So instead of waiting for the patient to feel bad and come in, you get early signal days before visit. So you see the problem while it's still small. So let's imagine, I don't know, day 4, the patient is at home and he feels fine, but the patch— Sorry. Sees the temperature goes up and stays up. So then you see the flag on your dashboard, you bring them in early and you catch the infection while it's still small and cheap to treat instead of like 3 days later when they already notice that it's off and come to the emergency room. So that single catch can pay for the whole device here. And this is the minimum version. So the next version is to add more sensor into the same patch, not just temperature, but markers of inflammation, like proteins, antibodies. I also seen similar projects on the market already in the idea stage, I would say, or prototype stage. So the chemistry of the healing that is read from the surface. So you go from a simple temperature sticker to a smart patch that actually reads the biology of the recovery. They typically designed with a microneedle. So it's not as invasive as, let's say, sugar monitoring. Yeah. Right. So you have same spot, same idea, more in-depth analysis here. Now, problem number 2, rehabilitation, right? And real load on the body. So here's a number that should bother all of us. After a knee replacement, by many estimates, as many as 1 in 5 patients is still not happy a year after. Wow. 1 out of 5. So there's a pain, there's stiffness, there is like function that never comes back. And the hard part is not just that it happens. Okay. Is it's that we catch the bad path too late. So today the first real check is often weeks after the patient goes home. Weeks is a long time to walk through the wrong way. So Yeah. by the time it shows up clearly in clinic, the patient is already far down the bad road. And this is where wearables change the game because the motion data from a simple sensor, the way the person actually walks, lines up well with the standard clinical scores that you already trust and you already implement. And it can show a bad recovery starting earlier than the next scheduled visit you have with the patient. So you can see the problem sooner, and when you see it sooner, you can step in sooner. And that's the whole difference between a patient who recovers and the patient who joins this, like, 1 in 5 statistic. So what does the measuring— um, let's make it concrete because this, I think, is a useful piece of information. So Two simple pieces, um, soft sleeve with muscle sensor, one on the leg and thin insole under the foot that reads pressure at the main load points, the heel and the ball of the foot. And together, these two reads, um, how the muscle fire when the person walks and how the weight lands. So from that, you get symmetry, left versus right. Mm-hmm. Where the load goes, which muscle group is doing too much and which one is asleep. And this is not only for big surgery, just, uh, strong in everyday orthopedics as well. So small patches on a child's leg and watch how the foot and arc work during the work. During the person walking, put a patch on the muscle and second one in a matching muscle on their side. And you can see like all along the statistic, whether the body is working evenly or not. And the same muscle sensor that athletes use to train can be pointed straight at recovery. So like same hardware, just a new job. The sports— In the general, like fitness world, sports world already proved the patch works. We just aim it at the patient instead of the runner that moves you from judging by AI, which is something that is typically done now still in most places, to recommend a specific exercise for a specific muscle backed by real data washed across the whole day instead of guessed at in 10-minute visits, right? So, um, this is the part that does not exist yet at scale, and I think it's very doable. Now the frontier, and I want to show you this is not like science fiction, it's already on the market. There's a smart knee implant called Persona IQ from Zimmer Biomet and Canary Medical. So it's the first and so far the only, basically smart knee to get cleared by the FDA through the novel path, which is the path like used for a brand new category. And here's what it does. Inside the stem of the implants, the part that sits in the bone, there's a tiny motion sensor, like a tiny accelerometer, tiny gyroscope, and it measures the real movement of the knee, like range of motion, step count, walking speed, and so on. And then on its own, it sends data to a small base station in the patient's home and up to cloud every day. And it is built to keep doing that for up to 10 years. So the key point here, it works. In validation tests and the range of motion, the implant reports matches the real motion of the joint within a fraction of degree. I saw this report because it's like, it's all open. The signal goes right through the bone and cement and out to receiver and then holds up. So it's already FDA-cleared device that lives inside the knee, measures the joint directly, and reports for decades. So the data from inside the body is now clinically trustworthy. And what it means to us, the regulator has already accepted that a sensor inside an implant can produce data you act on. So this door is already open. No, the hard part is not the permission. The hard part is probably engineering and go-to-market. So here's the takeaway from this.

Any questions so far, guys? She's gone over a lot. Raise your hand or just blurt out a question if you have one.

Hey Lisa, can you hear me?

Yes.

Yes.

So, and if you're gonna get to this later, feel free to address it. One thing that's always kind of caught my attention in the idea of wearables and at-home monitoring and postoperative stuff related to the patient is some of that information that doctors do not want because they run the risk of having some liability around it looking like they didn't do their job. Or making something look bad when maybe the patient is doing okay. It just, it feels like there is a whole minefield of post-market surveillance complaint generation that can come from this. What have you seen in that realm? And is that something that good or bad lessons are being learned by Canary Medical and that device, or what do you thought about that?

So there's like just some gossip saying about this is that in fact there is a huge resistance in adoption of this type of devices specifically by the reason that you mentioned now. But typically, doctors being pressured by an insurance and by business people in the hospital, because positive outcomes of using this device are, I would say, more economically valuable to the hospital. So there's a certain— Yeah. Pushback from doctors, which is true, but, um, this is how this industry works.

Probably a bigger deal in the US than other places, obviously. And then it depends on what you're measuring. So we've had Pletthy on BoneChat, we've had TrackPatch, we've had Canary Medical, And we've had MYO-1, I believe. MYO-1 measures compartment syndrome after traumatic surgery, after trauma, and it can save a leg. And there's a valuable few days where if pressure builds up near a wound, you can lose your entire arm or leg. And little sensor goes in and alarm goes off. And that's an acute thing. But I guess it depends on what you're picking. If you're picking gait analysis, I can't see a lot of pushback on that. But anyway, just comments. Anybody else? Yeah, Copeland, Mark and Mark, why don't you take off?

Maloney, you go first.

So I think that when I, when I helped to bring in SQ-Lab surgical navigation system into the United States, I was operating under the premise that all information has value, all information is good, and the more information you have, the better decisions you can make and the outcomes will improve. What I learned and what I lost money on was that the American surgeon didn't wanna know what they didn't wanna know. And they would rather do more surgery with less information than less surgery with more information. Did I say that right? Yeah. They'd rather do 6 cases in, in a day with less information and maybe a lesser outcome than they would 4 cases in a day with more information and a better outcome. Just the opposite of what I observed, for example, in Germany. Mm-hmm. Yeah, that's, that's my go. I think, I think Kyle's comment has validity, but I think in the end of the day, you know, if you follow the money, you know, as Lisa is inferring, that will win.

Yeah, doctors are, surgeons are making less and less product choice in the US. It's more insurance companies and big healthcare. And I think, I think that trend's gonna change. That's really interesting.

Copeland.

Yeah, can I throw, I'm gonna give you a couple of statistics on my own personal situation. According to Lisa's quick math, which she's probably right 'cause I'm terrible at, I'm 510 hours post-op from my total hip. I'm wearing a wearable that tells me I did 301 steps so far today. I have no idea how that compares where I am. Should I be back to 10,000? Should I be at 1,000? I have no clue. I spent $350 for EnRoute pre and post-op nutrition. I spent $400 for cold compression because I wanted to give myself the best chance to recover quickly. And had there been a patch that I could have put on that told me, here's how you're doing relative to your peers, I would have bought it in a nanosecond, right? And I have— Uh. I am very fortunate. My orthopedic surgeon is a very close friend of mine. I could text him anytime and say, "Hey, this is weird," or, "What's this?" I didn't do it necessarily, but I am extremely fortunate that I could do that and have other surgeons tell me what's going on, right? Who cares what doctors think? I would sometimes, honestly, I would say like, I don't know what Tiger paid for his Oura 5. It's probably, it may have a comma in it. I have no idea. People pay over $1,000 a year for wearables though. Who cares? Like if you gave me something that said, "Cope, you're doing well," or, "You need to pick it up," or, "You're cooking too much," whatever it is, I would've been interested because I'm the consumer in 2026. I wanna know how I'm doing And I don't wanna bug my doctor if I don't have to. And should I? And by the way, I love my doctor. He's awesome. I'm not even sure he would know, right? Like, so today's consumer spends, oh, by the way, I owe $7,500 still for my deductible. I'm paying money for this, right? Why would I not be interested in buying a sensor I can slap on my leg or something that Lisa comes up with? Right. For $500? I might. Let's not underestimate the capabilities of the consumer in 2026. I'd love to know this stuff. I have no idea how I compare. So that's my comment is doctors will figure it out. Consumers are already looking for it. Are you looking at that and targeting that market?

Yeah.

So it's a tricky part about the consumer electronics. And by the way, I think Whoop is the first company who figured out that consumers doesn't want to know their heart rate or amount of steps, and they don't care about the number, they care about the insights regarding their well-being. And now that's this year and following years, the market is moving towards edge AI. I think it's a huge opportunity for wearables as well, because they can take the data that is relevant to you personally and give you personal insights. And it's something that we might see more on the market. By the way, on a previous topic about doctors not wanting to see the data, I was thinking that without data, the mistake of the doctor, if there is a mistake, it wouldn't disappear, right? So we would just find out about it later when it's already like some severe complication. And that's exactly those late complications that create this question. So, um, and part of what looks like a bad recovery is not the surgeon, it's usually the patient. So they skip rehabilitation, they behave horribly. Like the moment that doesn't, doesn't hurt anymore. Like they, they just don't care. They don't follow the procedure. They skip rehabilitation, they overload the joint. And, uh, for a first time, the data inserted to the body can show that objectively. So it takes the blame of the doctor also. Mm-hmm. And that might be an interesting way to communicate this to the doctors. I'm not sure how Zimmer is doing this right now. I think they're still using the force to, to, to, to convince hospitals.

Yeah, we, we, we've had Bill, we had Bill Hunter on and the main thing that he solved with the PersonaIQ was compliance. Because patients aren't going to wear a, they're not going to wear something for 10 years. But if the device is secretly hidden in the implant, they don't have a choice. And the second thing I learned was the device is so sensitive. It can look, it can find early Parkinson's. It can find out if you had a, just had a stroke. I mean, it can, it can just find out incredible information even beyond, you know, your need. So anyway, keep going, Lisa. This is, this is good.

Okay. So yeah, like we, we already agree to the fact that we can trust the data from the body. This question is already answered since the implanted device is cleared already. So about the engineering side, I would say that adding a sensor is easy. So anyone can basically glue a chip to a thing, right? Making that thing actually work in real body for years, cheap enough, and getting it cleared, that's the hard part. And that's the whole game. So I have— Yeah. 6 things that actually decided. That's what we've seen in the space here. So, first one, like signal, not sensor. So, the sensor is a cheap part. The hard part is getting a clean signal from the body. So, you have like sweat, different types of skin, you have different medication person is using. The motion, whether the patch even stays stuck to the body. So the sensor with not clean signal is worthless. And clean signal is the real product. And in one of our devices, we spend more time killing the noise. The company was called Xtrode, by the way. They're on the market. They're not in the orthopedic space, but they use a number of different applications to measure muscle activity. Heart rates, brain activity, and so on. So on this device, we spent more time cleaning the signal than on everything else about this device combined. So on the bench, it looked perfect. But once we put it on a real person, we figured out, okay, different people sweating differently, they have different skin color. Some people are hairy, some they're not. They have different age, you have different skin properties. So fixing that is the actual job. Now, second part is like energy. For something that runs all the time, especially sometimes inside the body, power is a bottleneck and you cannot charge a battery inside of the bone. So I'll come back to this one because there are some good news. Okay. Number 3, how to get data out of it? So the sensor that cannot talk is just like useless, right? So you need a radio that fits in a millimeter or 2. And something that body tissue would accept and also housing that behaves like a bone. So, this is a real engineering. This technology is also on the market, but that's a complex engineering, something that would differentiate a demo from the product. Another thing, like, of course, everyone is using AI, right? So, it's— Yeah. It's only as good as the data you feed it. So raw signal that you're seeing is not an insight for AI. You need clean data, calibration, and some real clinical link to build the product. So you like have to collect the data, compare it with the clinically validated data, And then AI would be useful because it would have a good dataset and it would actually define how the device is working afterwards. Now, number 5, the regulation should shape the design from early on. So, new category like this goes through the NOOA part, the same one that the Smart Knee used. And we have to build it from the first sketch, not just you know, like think about it later on and realize there's a bunch of steps missing to use the de novo path because it's the most complex one. And also like a last one, but not least is miniaturization. So, two hungriest things for space and for power are antenna and the battery.

Mm-hmm.

So, to send the signal and to consume the energy. And sometimes the smart move is to store the data on the device and sync it later, like in the charger, instead of broadcasting all the time. So, we've seen different options here. So, let me come back to the energy part here. I think it's most exciting here. So, we know the joint is never still, like even like every step basically puts pressure and motion through it. And I've seen a technology in the market that's, uh, turns that pressure straight into electricity with no battery, no wire. So they use the piezoelectric and triboelectric sensors, and then they make power from motion, from movement of the leg. And recent work shows that walking loads in the knee can produce a few microwatts of power. Wow. Power? Well, it's small, but it's enough because modern low-power electronics are built to run on exactly that, just a few microwatts. So the picture is this: the joint moves, the movement makes the power, the power runs the sensor, and the sensor measures the joint. So this entire construction feeds itself from the very thing it's measuring. Um, So, this like another direction that we see here.

Lisa, quick question. How big is that piezoelectric sensor? I mean, we talking a couple millimeters thick?

I mean— Yes, it's really tiny. So, we've seen in experimental sensors, they're This technology haven't been cleared yet. At least I'm not aware of. Maybe it's already on the market, but I have— sorry, not in past clinical trials, but I haven't seen it yet. But I've seen recent articles showing that it's possible. And sensors that they were using, they were like really tiny. Again, a couple of millimeters, like probably 2 to 3 millimeters only. So it's doable in my opinion. So another honest objection that I heard a lot is that people think that it sounds expensive and too far away from today, and that patients and surgeons are slow to adopt anything new. It's fair, but Every piece that I showed you already, it exists in the market. So this tiny patch exists, the energy harvester exists, it's just early stage, but still, in-bone sensor cleared by FDA exists. Nobody have put them together into one clean, affordable system yet. And this gap is not science problem, it's engineering and timing problem, in my opinion. And those get solved by whoever decides to go first. So, here, let me show you the idea that we got in the company. We haven't moved this project from a pet project. But we have like a couple of pet projects running at the same time. And one we might turn into startup later. Patch for seniors. But another concept we got here is like two layers that talk to each other. So in the outside is a patch on the surgical area, temperature today, biomarkers tomorrow, as I say, that would handle the inflammation problem. And on the inside, sensor about the size of couple of millimeters that goes into the bone like a— Like a small screw. So something biocompatible in the bone-like housing with a soft head, has a motion sensor, so treats the real movement of the joint and real load on it. And ideally, like, we haven't built this concept, but we made a simulation and know that it's physically possible, that it's powered by the load the way I just described, and it talks to the patch on the outside. So, here in this concept, we didn't invent monitoring rehabilitation. People have tried to read recovery from the outside, even from the crash for years, right? We have built lots of sensors into crashes in the startup of Comeback Mobility. But the cleanest signal is at the source in the bone. So that's where we think is the best place to put in the sensor. And this startup would not be something that started from zero because a number of companies are already doing real work in the bone. So like screws, bone models, the equipment for reconstruction, base is here today. And I believe that in 2027, we see other companies doing that. Okay. So, if you make implants, sensors like this can ride inside what you already built. And the team that solves clean signal energy and data out of it, like all three in a millimeter, is a team that would own this category, probably. So, what we see right now Is that the body is becoming something that you can read all the time, not just this one frame, one visit in the clinic, but the full picture. You can see it now and collect about the person at home where recovery actually happens. And here's the honest truth about who would win. This is not the team that adds like extra sensors. Sensors are easy. It's the team that solves all this three things at the same time. And well, probably we would move towards a new standard of care. So that's the prize. And I feel that now it's the right time and it's close.

Yeah, it seems like a convergence of technology and regulatory pathways and things are getting cheaper. It's just The perfect time. So I wanna ask the panel that knows orthopedics inside out, what, where do you go? Where would you go for the next sensor? You know, where, what would you measure? Go ahead, Todd. You're on mute.

Here you go. In my fracture fixation world that I've lived in for 20 years, I think we wanna measure when we're healed. So you could probably have a sensor on both sides of the bone. You would know when healing has occurred by measuring loads. You know that you can, I think people are working on this, like, inside the hardware, like a trauma plate, but they're not, you know, I like this, I like this discussion because I think that gives a more accurate answer, right? You have, you're in the bone where the body, and we're putting screws in all over the place anyway, but you're in the bone where you might have a better answer than on a plate or a nail or even an external fixator.

That's a, that's a good one. So fracture, 'cause we don't really even know when a fracture heals. We're just looking at x-rays and, and motion. That's a good one. Kyle.

So what jumps out to me here is the most motivated patients on planet Earth, which are sports medicine patients, athletes that are told they can't perform and can't compete and they want back in the action as soon as possible. So a sensor that helps track that recovery and also potentially provides evidence that they are ready to go in spite of what their doctor or their parents or their coach or their trainer might tell them, I think that would be a hot, hot spot to go.

So you're mainly talking muscle, soft tissue, I would think, not fractures with athletes?

Probably not fractures, but I think Todd's onto something there too.

But I just— Yeah.

What I think is interesting is Like Copeland was talking about things related to his hip replacement. That's all like he's motivated to get better, which is some patients. I got a father-in-law that just got a second knee replacement. Both of them have been terrible. He also is a total pain in the butt in every way. He's not super motivated to do it right. But you know, I got a 19-year-old daughter just about to turn 19. She fought her way through every injury imaginable to be on the track field. No one's more motivated than a high school or a college-level athlete. Just, they'll do anything to get back. And I think a sensor that helps them with that would be— and then parents aren't going to be price sensitive about that either. So the cost becomes less of an issue.

Great, great point.

That's a great idea. Sorry for chiming in again. You think about these, these little micro fractures that runners always— I used to be a runner, but now I'm soon to be a knee implant patient, so I only ride my bike. But I'm trying to stretch that out, but runners microfractures all the time and they're, they're not fractures that are getting, they're not fractures that are getting implants. You know, these are, and these keep any, any runner that I know, they're gonna run prematurely before it's healed and just cause that to be worse and worse and worse.

Okay. Maloney and, and yeah. Maloney, and then Alyssa's in the wing somewhere with a comment or question.

So having attended hundreds of probably first-year orthopedic residency lectures as well as fracture conferences, all I've ever— the first lesson I ever learned was stability, stability, stability, stupid. That's everything from pain reduction to healing. I think the data that comes from this will teach us new things that we don't even know yet, which is fascinating. 'Cause everything in orthopedics is about fixation and stability, whether it's an ACL, and if it slips 5 to 7 millimeters, you're screwed. But yet it, those slip every day. And spine and trauma, all of these things speak to this. Again, I think what we're gonna learn is from this measurement how to modulate like Wolff's law, you know, how to modulate that micromotion that speeds healing versus that micromotion that eventually breaks the plate or the pedicle screw or whatever. Now this is fascinating. Mm-hmm.

Interesting. Alyssa, you there?

Yeah, can you hear me?

Yes.

All right. Well, we actually touched upon this subject over at the NASA Innovation Summit, and the surgeons had a great option, like an observation. So here's the thing. We have a patient and they're not healing, and they have a sensor, and the sensor fundamentally has to tell them they're not healing. You know, that's part of their rights as a patient. But they don't have any complications or not having problems. Nothing's loosening. Everything's just staying stable. So how does that translate into medicine and placebo effect? Will it hurt the patient in the long run? Because we know mentally we can influence change. Just, you know, in our, in our physical psyche with cortisol and adrenal fatigue and, and. And the— there's— I think the true opportunity for sensors is presurgical and postsurgical optimization. Understanding what the patient's disease state is without having to do genetic testing and all of that stuff, but optimizing them, saying that they are nutrient deficient in things that CBC doesn't qualify for. Mm-hmm. Understanding the hormone balances. So then custom scripts can be created using AI to influence optimization, pre-surgical and post-surgical for the patient.

Wow, I love it. And what would you measure post-surgical, Alyssa?

So, pH balance, infection, um, If the drug that they put in is working, for example, you can use CRISPR technology through— now I'm going to self-promote here, I apologize, but our goal is to use CRISPR technology through our devices to treat cancers, because you can mix the bone marrow that we draw with the CRISPR technology and re-inject. Understanding if the cancer is actually being treated without radiation because radiation kills bones surrounding the implant. Um, there's, there's so much opportunity for influence on implantables that are far beyond, um, just tracking. Also pelvic tilt. I think in spine surgery, pelvic tilt is underutilized or underconsidered, um, in spine surgery and how it affects— because once you, as you guys know, anybody that's been in hips, once you start dislocating, you usually don't stop dislocating until they— until a constrained liner sometimes is effective, but sometimes you have to take everything out. So I really think that, that we need to focus on universally the pre-surgical patient and the revision patient.

Boy, that's great comments.

Wow.

So Lisa, what kind of, I know you're working with lots of startups. What kind of things are you working on? Probably mostly outside ortho.

I would say that we have 3 main areas of expertise, which are orthopedics and everything related to orthopedics. Bone drilling equipment, implants itself, at-home rehabilitation sensors, and so on. So second biggest category would be any type of wearable devices. So we have— We have 16 ongoing projects in our company right now, and I would say 30% of them are wearable devices. In different form factors. And third category would be whatever equipment that goes inside of the operation room, like medical ventilators. We have one very big project, which is a robotic surgeon that we're working on right now, or another equipment goes inside of the operation room. But in general, we've built, as I said in the beginning, over 200 different medical devices.

Wow.

Another trend that I see in general in the industry is using edge AI to give better feedback to the person using the device. Like when I was a kid, I had a thermometer when I need to look at this and guess what number I'm looking at, you know, and now my kids have a thermometer where It shows the number of digital thermometers. So I feel this technology moves to other areas. For example, this ovulation microscopes where you lick the lens and then you try to understand, do you see a pattern or not? This fern pattern, because sometimes during the ovulation saliva forms fern pattern. On the lens. So, you as a person should look at it and make a decision. And I believe that's a huge opportunity for AGI in this. And a pet project that we have in our team is we've— I think I post article in our newsletter about that. So, we've built the AGI— Hmm. For semen analysis. Because first of all, the entire procedure is accumulating. You need to give the material, you need someone to look at it. And the device that we've built actually just takes the material and allows to understand the properties of the cells without someone looking at it and without someone coming up with a conclusion what is happening to the cells. So I think it would be a next big step in the industry moving towards, um, like easier understanding of the results, not depending on someone with an expertise looking at them.

Wow, you're a busy person. So I'm gonna— Lisa writes a really, really good newsletter that comes out every couple weeks, 2 or 3 weeks. I'm just going to put a link here. Everybody should subscribe to this newsletter. It's very well written.

Tiger, I agree. Lisa's like you. That's why I had to come on here even if I was late. It's like you— she has your voice where she gives critical feedback to the ecosystem and it's And there are far too many people that are doing that.

Yeah, she's— if I were developing a wearable next week, I would just call Lisa. I mean, I would give her some requirements and turn her loose. And she has a pretty good team too. How many people are on your team?

We have 62 engineers right now.

Yeah, I mean, that is incredible. Oh, Art Maloney is sending Russian that I don't understand.

He said great job, actually, or very good.

Excellent.

Thank you.

Any— so we got a couple of minutes left. Any comments, questions? I mean, yeah, go ahead. Wrap it up.

Yeah.

Thank you for having me here today. It was a great topic and thank you so much.

Yes, I can't— I think patches, I mean, the, the visual of going from bulky things to patches to things in the bone is just so natural. It's gonna happen and there's gonna be a first mover advantage for somebody, for some startup and Yeah, if I were a younger man, I might take a product concept and run with it, but this is a— I love this space.

There are lots of opportunities here as well. Like, we saw a number of applications, and the one we choose for ourselves, like, for Pasha, is seniors care, because the statistic is huge. For example, 80% of people who are prescribed with this smart alert buttons, they're not using them. And out of people who are using them, another 80% are not pressing the button when they need help. So, uh— There should be a patch that can understand if you're unwell. And also if you ever experienced that, because we experience it all the time, we have to test our patches, right? So it's unique experience in terms of you can stick it on and you forget it's there for like in 15 minutes after you place it on your body. I see there is a question about the reimbursement here. Um, It's in Q&A.

Uh, reimbursement. I don't see the question. I don't see the question.

Okay, let me read it. So what is the reimbursement landscape for remote therapeutic monitoring, and are physicians incentivized to adopt it, or is it too burdensome, not enough clinical value in post-op applications? So, uh, I researched it recently, conveniently for our startup that we're working on. And this is something that is changing all the time. I think good news is that the payment procedure, like the payment pathway, already exists and just got better quite recently for exactly the post-op case. So There are codes for remote therapeutic monitoring, and there are a number of codes. There's a code for setting up the device, for treatment management. Approximately, I cannot answer confidently here, but I think approximately it's around 100 to 150 $1,000 per patient per month. Uh, it's like an average. Uh, of course it might vary from like, uh, depending on the place and the payer. And, uh, this year there is a huge change because, um, they just finalized the largest, uh, RTM expansion since 2022 and explicitly aimed, um, the, the, the entire procedure at the post-surgical recovery. So old rules, they needed like around 2 weeks of data and around like 20 minutes per month, uh, which didn't fit a short front-loaded post-op window. So there was an adoption issue, and now the change of the codes is following. So they have short window codes for 2 to 15 days of data, and, uh, the goal is to cut this administration burden and make it like finally viable for more applications. So this thing is like too, too burdensome. I think it's been slowly eliminated. It's basically just fixed.

Yeah, we, we had Raja from Pletthy on a couple weeks ago and he, he shared the reimbursement codes. There's, there's plenty of reimbursement codes for post-op for sure. Yeah, I want to ask an M&A question. I'd love to hear Colleen on this too. So if you're a startup wearable, what specific metric or milestones would make you, would turn you into like a must-acquire company? There's how many patients, treatments, cogs? I don't know, what would be the numbers that make you really attractive?

You know, I've given a lot of thought to that. Is there an echo?

I know.

No, you're good. Okay. So, you know, I think you gotta get the adoption and you've gotta get not just a few surgeons or a few hospitals or it really has to be a widespread adoption. And the challenge to that is how is that data flow and the use of the sensors integrated into the patient's care plan. And that's always, that was a challenge for us at TrackPatch. So I would say if you can get the adoption and consistent loyal users, I think that's what it takes. I mean, so how much revenue? I think revenue and, Margins need to make sense, but you probably have to be approaching over $10 million in revenue and lots of adoption.

With a nice, a nice curve.

Yeah.

Yeah.

And it'd be great if it, you had multi types of products, right? You know, not just monitoring a post-op knee, but you know, whether it's spine or ACL or I think it has to be a broader product.

Got it. And it kind of goes back to that whole throughput question. It's gotta reduce the burden on the healthcare staff.

Absolutely.

That, yeah, that's, that's a must have. Well, we're gone over this. We could talk for another hour with Lisa. This is great. Thanks for your time, Lisa, and come back anytime. This is terrific. I've learned a lot.

Thanks, Lisa.

I really enjoyed it.

Yeah, awesome job. Thank you.

Great work out there, Lisa.