Healthcare based on tech-gathered data, not opinion

"It's not a matter of our opinion whether we think that you should eat this or that," says Fullpower Technologies' Philippe Kahn. "Let's look at the data."


IoT and AI can help us make health decisions based on data not opinion, Philippe Kahn, CEO of Fullpower Technologies tells TechRepublic's Tonya Hall.

"Opinions are great, for politics and related fields," and there's a lot of that going on, especially in this country right now, but I'm a scientist," Kahn says. "We wanted to have tools that allow us to apply science to important things for Mrs. and Mr. Everyone, like wellness, health, etc, and say 'You know what? It's not a matter of our opinion whether we think that you should eat this or that. Let's look at the data.'"

Watch the video interview above or read the full transcript below.


Tonya Hall: What keeps you up at night, and is it a problem? Hi, I'm Tonya Hall with ZDNet, and we're going to discuss that and more with our guest, Philippe Kahn, who is the CEO of Fullpower Technologies. He's an inventor, and among other things invented the first phone camera. Welcome, Philippe.

Philippe Kahn: Thank you. It's a pleasure to be here.

Tonya Hall: Talk about what you're doing at Fullpower Technologies.

Philippe Kahn: Well, at Fullpower Technologies, we're an AI-powered company. We build a platform, and there's a lot of ways to talk about what we do. But on a program like this, I like to say that we build the tools that are going to make science the answer, as opposed to opinion. And let me try to qualify that. For example, take the problem of sleep. There's lots of opinions of what sleep should be. Should you sleep eight hours? Should we sleep six and a half hours, et cetera? There's lots of opinions that people say if you wake up twice a night it's horrible, you need to get on medication or something. It has been until now, a matter of opinion. Now that we have hundreds of millions of nights of digital sleep, I mean basically sensing base-sleep recorded and we can use AI tools, machine-learning, and deep-learning, et cetera, to analyze that.

Then we can get data and let the data speak and see without a matter of opinion what's normal for a female between say 35-years-old and 47-years-old? What's a normal night's of sleep? What's the 95% percentile, what's the 50%, where do people rank, and what's the difference between where they are and where the people who have a 95% percentiles on a sleep score? Then we can understand who sleeps well, and who doesn't, and whether using something called cognitive behavioral science, we can through little changes, help people do a better job. But not as a matter of opinion, but as a matter of science. That's really what we're proud of doing. Now all the rest that we build, there's a lot of technology, serves that purpose.

Tonya Hall: So you basically went from discovering the camera phone, to working with machine-learning and artificial intelligence and healthcare. What made you decide that a health focus, or being in the health space was important to you?

Philippe Kahn: Well, you know I've always been involved with AI in prior companies, too, because building development tools, et cetera, you look at and everything you do is what we call AI today, expert systems et cetera, in the '80s, we shipped even a tool called Prolog, which was a language for artificial intelligence, which was a dedicated one, just like Lisp was at the time. So I was always involved with that. What really became important when every object became connected and when sensors became much more advanced and where we had the prospect of having AI powered processors in devices, what people call Edge devices now. What became really interesting is, we had the tools to not only monitor an oil-rig offshore, et cetera, which is what a lot of the industrial IOT does, which is pretty simple to do but still has to be done or your wash machine or your coffee machine, whatever it is, but we have now the tools to understand human health and wellness much better from a scientific, from a data standpoint.

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Diet is a perfect example of it. If you go back 20-30 years ago, people would have told you that to be healthy you have to eat three servings of spaghetti a day and avoid protein and stuff like that. Now, there's half of the people that says, "Oh no, it's the opposite. Don't touch that pasta, don't touch that bread. Eat a protein and fat centric meal and you'll do better." So all these things change all the time, but they're really a matter of opinion because there's very little science. Now, with the tools we're developing we can actually look at what it means from a science perspective.

Opinions are really great, maybe for politics and stuff like that, and there's a lot of that going on, especially in this country right now, but I'm a scientist. So what we wanted is to have the tools that allow us to apply science to important things for Mrs. and Mr. Everyone, like wellness, health, et cetera and say "You know what? It's not a matter of our opinion whether we think that you should eat this or that. Let's look at the data."

Tonya Hall: You talked about sleep, specifically, but considering we have learned so much and we have come so far, and now we're really looking at data, how is the healthcare industry looking at the technology today, the data, the machine learning. How are they looking at it differently than they looked at it, maybe, when we first started using data?

Philippe Kahn: They're not yet. And a lot of it is in denial. And I'll tell you why. It's because there are very powerful economic motors powering different sides of this. Big pharma wants to sell more drugs, so I'll give you an example. Recently, you may have read that in the New York Times had a story like that a couple days ago, there's been the American Heart Association or one of those organizations decided that to lower the guidelines for hypertension for people, saying if you're over 120/80, then you're in hypertension mode. Officially, the reason they've done that is they tell you that it's because they want people to be more cautious and change their diet and exercise. That's a lot of bull. The real reason is that the big pharma companies want to put people on all these high-blood pressure medicines, and by doing that, they hit 30 million more people. And that 30 million more people who will, for the rest of their life, take three pills a day, which is a lot of money, billions of dollars.

So that kind of ... there's a lot of denial. What we hope is the kind of work we do and some other people do is going to change some of that behavior in a positive way in looking, wait a minute, it's okay. Everybody wakes up once a night. You don't need to take Ambien because you wake up once a night. It's perfectly healthy. It's actually good for you. In fact, when you start looking at it and thinking about it from an evolutionary standpoint, people did not sleep in a perfectly quiet, perfectly dark, perfectly temperatured room. We used to sleep communally, there was a lot of people in a room, there was noise, et cetera but we were really good at tuning these things out, filtering it, and be able to get our sleep. Now, people are like, "Oh my God, I just heard something. I just woke up. What's going to happen?" And that's really the key.

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And of course, some people take advantage of that. They say, "Oh, I can sell you a pill." Or "Oh, you have a breathing problem at night. I'm going to put you on a CPAP machine, and therefore the guy who prescribes the CPAP machine gets a 20% cut on the sale of the CPAP machine, the CPAP machine comes with a subscription. Every day they make money, and that pays his or her mortgage, whatever it is, and the people who make the CPAP machines are delighted. It doesn't mean that you don't need CPAP machines, but they get overprescribed, because it's good business. So the question is, can we actually look at the data, and see what actually is necessary, and what benefit Mrs. and Mr. Everyone every day, as opposed to benefit the coffers of big pharma companies.

Tonya Hall: Okay, and my dad uses one of those, and I have friends that use them, so what is it that we need to do differently moving forward? What does the healthcare industry need to do? It sounds like it's complicated.

Philippe Kahn: Well, what's complicated is really the following, it's that wellness and health has typically been proxied to a medical doctor who is competent, but people have forgotten that through the digital revolution, we can get a quantified self, and we can get to understand what's happening to ourselves, and compliment that specialist's opinion and advice with actually things that you learn all the time. I'll give you an example with hypertension. Most people get diagnosed with hypertension in a medical doctor's office, and okay, you've got hypertension. What's really important is not to know whether you had high blood pressure when you were in that office, which you know, you might be stressed because of something called the white-coat syndrome where you basically stress out because they're going to measure your thing. You go, "Oh my God, I might have [high-] blood pressure." And that raises it, because it's a lot of psychology in that.

So what happens during the night? What happens during the day? Do we have more data, and what does the data say? I think that you'll find that that's changes completely the kind of diagnosis, because now we have a pretty good idea of, "Oh, I get high blood pressure when I eat that kind of food for three hours after the meal," as opposed to, "Oh, I have high blood pressure. I've got to go on a pill."

The same thing is true for CPAP machines. Everybody is going to have some respiratory event at one point when they sleep. Especially if you go to a sleep specialist, and they put you in the back room over there and say, "Sleep now" in an environment that's not yours. They wire you like you look like Frankenstein or Mrs. and Mr. Frankenstein. You look like a monster with wires coming, and now you have to sleep, and they say, "Oh well you only sleep one hour, but I can tell that you have all these wake up events." Well they didn't measure your sleep. They measured your disrupted sleep in the back room of a bad hotel room, which is basically what that sleep lab was.

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It's not that it's not useful. It's a data point. But it's not everything. What's really important is that I think that's part of the quantified self-revolution that people don't proxy everything about wellness, especially when they're educated. It's people who just they want to go somewhere and they want someone to tell them what to do. That's one thing. Or take a pill. But most people I believe with a college education should be able to use some critical thinking, which is rare sometimes these days, and say, "Okay, why is it that I'm going? How does it work? Is that correct? Do I feel this way every day?" Whatever it is. I think that's really what we're talking about is empowering Mrs. and Mr. Everyone, as opposed to empowering all these outside forces, which have useful opinions, et cetera. But we need to take charge of our own health. That's how we're going to make the most difference. It's true for any of the, especially the chronic conditions.

Tonya Hall: Well, I'm excited to see the future of data being introduced into healthcare, as well as understanding the human component as well. You did a really good job of articulating that, Phillippe, and thank you for talking to us. So, if somebody wants to follow what you're doing as it relates to sleep or anything else, how can they do that?

Philippe Kahn: Well, you can go to fullpower.com, our thing. We actually build the sleep-monitoring solution for the company that is the leading mattress company in North America, called Simmons-Serta. They have a product called Beautyrest, and they sell it on Amazon. It's called Beautyrest Sleeptracker. It's a very advanced system, and basically it's not well-known because they sell their products through mattress distribution channels, so they're not a consumer electronic company, but it's the most advanced sleep monitoring solution, and it's completely non-invasive. You put a sensor under your mattress, and it does everything else for you, and it gives you a complete analysis, and it tells you how you sleep versus millions of others. I think that's a useful data point, because now suddenly you say, "Oh, my sleep's not so bad." Or, "Well, I have disrupted sleep. What can I do about it?" And the system will help you through small little incremental modifications using cognitive behavioral science to little modifications to actually gradually improve your sleep a little bit at a time.

Tonya Hall: That's good to know. And it's good to know that me waking up throughout the night is actually not a bad thing.

Philippe Kahn: No, it's a good thing. It's a good thing.

Tonya Hall: Again, I'm Tonya Hall. You can follow me and find more of my interviews here at TechRepublic and ZDNet, and to follow me on Twitter at @tonyahallradio or find me on Facebook at The Tonya Hall Show.

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