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  • When I was a kid,

  • I was, like many of you in this room, very much fascinated by Star Wars,

  • and what fascinated me the most is this notion of the Force,

  • this energy that connects all people and all objects

  • and allows you to feel people that you can't even see.

  • And I remember many nights, I would be sitting at home,

  • just, like, concentrating and focusing, trying to feel the Force,

  • and I didn't feel anything, don't worry.

  • (Laughter)

  • And later in life, I became a scientist.

  • I joined the MIT faculty and started working on wireless signals.

  • These are things like Wi-Fi or cellular systems,

  • and I did a lot of work in that domain.

  • But then, again, this Force thing kept nagging me,

  • and at some point, I was just like,

  • "Wait a minute, these wireless signals -- they are like the Force."

  • So if you think about it,

  • wireless signals, they travel through space,

  • they go through obstacles and walls and occlusions,

  • and some of them,

  • they reflect off our bodies, because our bodies are full of water,

  • and some of these minute reflections,

  • they come back.

  • And if, just if, I had a device that can just sense these minute reflections,

  • then I would be able to feel people that I cannot see.

  • So I started working with my students on building such a device,

  • and I want to show you some of our early results.

  • So here, you see my student standing,

  • and here is our device.

  • And we are going to put the device in the other office, behind the wall,

  • and we are going to monitor him as he moves.

  • This red dot is tracking him using wireless signals.

  • And as you can see, the red dot is tracking his movements very accurately,

  • purely based on how his body interacts with the surrounding wireless signals.

  • Pretty accurate, isn't it?

  • He has no wearables, nothing.

  • (Applause)

  • Now you might be wondering,

  • how is it possible that we can sense people

  • and track them, without any wearables, through walls,

  • and the easiest analogy to think about is radar.

  • I'm sure many of you have seen this picture.

  • You transmit a wireless signal to the sky,

  • it reflects off some airplane, comes back to you,

  • and you start detecting these airplanes.

  • But if it were just radar,

  • then we would have this 50 years ago.

  • So it's not just radar.

  • There are two key differences.

  • So the first difference, of course --

  • you can't, like radar, just blast wireless power at somebody.

  • You're going to fry them like if they were in a microwave.

  • Don't do that.

  • So it means that you have to be able to deal with very weak signals,

  • and that means that your device has to be very sensitive.

  • The second difference is that, unlike the sky, where it's empty --

  • if you are lucky, there is one airplane that you can catch there.

  • Like, look at the room

  • and look how many objects and people there are.

  • So in indoor environments, the signal not only reflects off the person,

  • if reflects off the person, off the floor, the ceiling,

  • off other people around,

  • and you get very complex reflections

  • where the same signal reflects off me and then off you,

  • and then off the ceiling, then off the floor.

  • And you have to make sense of that mess.

  • But we were lucky.

  • We were coming at the right time.

  • So two things helped us.

  • The first thing is radiotechnologies have evolved a lot,

  • and over the last decade,

  • radio technology became much more powerful,

  • so we were able to build very sensitive radios

  • that can sense weak and minute RF signals.

  • The second thing: machine learning.

  • So you keep hearing about machine learning

  • and there was a revolution of machine learning recently,

  • in deep learning,

  • and that allowed us to build machine-learning models

  • that can understand wireless signals and interpret them

  • so they would know what happened in the environment.

  • So if you think of it, the radio is like the ear of our device

  • and the machine learning is like the brain,

  • and together, they have a very powerful device.

  • So what else can we sense about people using wireless signals?

  • Sleep.

  • Sleep, actually, is something very dear to my heart,

  • because my sleep is a disaster.

  • (Laughter)

  • So one thing is when you start working on some physiological signal

  • and you discover that yours sucks.

  • (Laughter)

  • So you can see why we can capture sleep,

  • because the person walks and the device sees him as he walks to bed,

  • when he stops tossing around in bed,

  • when he steps out of bed,

  • and that measure of sleep is what people call actigraphy.

  • It's based on motion.

  • But it turned out that we can actually get sleep

  • at a much more important level.

  • We can understand the change in the brain waves

  • that occur during sleep.

  • So, many of you probably know that as we go to sleep,

  • our brainwaves change and we enter different stages:

  • awake, light sleep, deep sleep and REM, or rapid eye movement.

  • These stages are of course related to sleep disorders,

  • but they are also related to various diseases.

  • So for example, disturbances in REM are associated with depression.

  • Disturbances in deep sleep are associated with Alzheimer's.

  • So if you want to get sleep staging,

  • today, you will send the person to the hospital,

  • they put all of these electrodes on their head,

  • and they ask them to sleep like that.

  • (Laughter)

  • It's not really a happy experience.

  • So what if I tell you that I can do the same thing

  • but without any of these electrodes on the person's body?

  • So here is our device,

  • transmitting very low power wireless signal,

  • analyzes the reflections using AI

  • and spits out the sleep stages throughout the night.

  • So we know, for example, when this person is dreaming.

  • Not just that ...

  • we can even get your breathing while you are sitting like that,

  • and without touching you.

  • So he is sitting and reading

  • and this is his inhales, exhales.

  • We asked him to hold his breath,

  • and you see the signal staying at a steady level

  • because he exhaled.

  • He did not inhale.

  • And I want to zoom in on the signal.

  • And this is the same signal as before.

  • These are the inhales,

  • these are the exhales.

  • And you see these blips on the signal?

  • These are not noise.

  • They are his heartbeats.

  • And you can see them beat by beat.

  • So I want to stop here for a moment and show you a live demo.

  • Zach is going to help me with the demo,

  • and we're going to use the device to monitor Zach's breathing.

  • So this white box that you see here is the device,

  • and Zach is turning it on ...

  • and I see that he breathes well.

  • So we're going to do exactly what we did in the video with the other guy,

  • so the wireless signal is going through,

  • it's touching Zach's body,

  • and it's reflecting back to the device,

  • and we want to monitor his breathing, his inhale-exhale motion.

  • So we see the inhales, exhales --

  • so see, these ups and downs are Zach breathing.

  • Inhaling, exhaling.

  • (Applause)

  • So, he can breathe.

  • (Laughter)

  • Zach, can you hold your breath, please?

  • OK, so now he's holding his breath,

  • so you see the signal stays at a steady level,

  • and these are his heartbeats.

  • Beat, beat, beat, beat, beat.

  • (Applause)

  • OK, Zach, you can breathe again.

  • (Laughter)

  • We don't want accidents here.

  • (Laughter)

  • OK, thank you.

  • (Applause)

  • So as you can see, we have this device

  • that can monitor so many physiological signals for you,

  • and what is really interesting about this device

  • is that it does all this without any wearables,

  • without asking the person to change his behavior

  • or to wear anything or charge anything special.

  • And that got doctors very excited,

  • because doctors,

  • they always want to know more information about their patients,

  • particularly at home,

  • and this is particularly true in chronic diseases,

  • like pulmonary diseases, like COPD,

  • or heart failure or Alzheimer's and even depression.

  • All of these chronic diseases are very important.

  • In fact -- perhaps you know --

  • two-thirds of the cost of health care in the US

  • is due to chronic diseases.

  • But what is really interesting about chronic diseases

  • is that when the person, for example,

  • has a problem that leads to the hospital and the emergency room,

  • this problem doesn't happen overnight.

  • Actually, things happen gradually.

  • So if we can monitor chronic disease patients in their home,

  • we can detect changes in their breathing, heartbeat, mobility, sleep --

  • and we can detect emergencies before they occur

  • and have the doctor intervene earlier

  • so that we can avoid hospitalization.

  • And indeed, today we are working with multiple doctors

  • in different disease categories.

  • So I'm really excited

  • because we have deployed the device with many patients.

  • We have deployed the device with patients that have COPD,

  • which is a pulmonary disease,

  • patients that have Alzheimer's,

  • patients that have depression and anxiety

  • and people that have Parkinson's.

  • And we are working with the doctors on improving their life,

  • understanding the disease better.

  • So when I started, I told you

  • that I'm really fascinated with Star Wars and the Force in Star Wars,

  • and indeed, I'm still very much fascinated,

  • even now, as a grown-up, with Star Wars,

  • waiting for the next movie.

  • But I'm very fascinated now and excited

  • about this new Force of wireless signals,

  • and the potential of changing health care with this new force.

  • One of the patients with whom we deployed is actually my aunt.

  • She has heart failure,

  • and I'm sure many of you guys in the audience

  • have parents, grandparents, loved ones who have chronic diseases.

  • So I want you to imagine with me a future

  • where in every home that has a chronic disease patient,

  • there is a device like this device sitting in the background

  • and just monitoring passively

  • sleep, breathing, the health of this chronic disease patient,

  • and before an emergency occurs,

  • it would detect the degradation in the physiological signal

  • and alert the doctor

  • so that we can avoid hospitalization.

  • This can change health care as we know it today,

  • improve how we understand chronic diseases

  • and also save many lives.

  • Thank you.

  • (Applause)

  • Helen Walters: Dina, thank you so much.

  • Thank you too, Zach.

  • So glad you're breathing.

  • So Dina, this is amazing.

  • The positive applications are incredible.

  • What is the framework, though, like the ethical framework around this?

  • What are you doing to prevent this technology from being used

  • for other, perhaps less positive types of applications?

  • Dina Katabi: Yeah, this is a very important question, of course,

  • like, what about misuse,

  • or what about, I guess you could say, about the Dark Side of the Force?

  • HW: Right, right.

  • (Laughter)

  • DK: So we actually have technologies

  • that prevent people from trying to use this device

  • to monitor somebody without their consent.

  • Because the device understands space,

  • it will ask you to prove, by doing certain movements,

  • that you have access to the space

  • and you are the person who you are asking the device to monitor.

  • So technology-wise,

  • we have technology that we integrate to prevent misuse,

  • but also, I think there is a role for policy, like everything else,

  • and hopefully, with the two of them, we can control any misuse.

  • HW: Amazing. Thank you so much.

  • DK: Thank you.

  • (Applause)

When I was a kid,

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【TED】Dina Katabi: A new way to monitor vital signs (that can see through walls) (A new way to monitor vital signs (that can see through walls) | Dina Katabi)

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    林宜悉 posted on 2018/08/09
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