A new way to monitor vital signs that can see through walls Dina Katabi

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 let’s see whether 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)

当我还是个孩子

的时候,和这个房间里的许多人一样,我
对《星球大战》非常着迷,

而最让我着迷的
是这种原力的概念,

这种将
所有人和所有物体连接起来

并允许你 感受
你甚至看不到的人。

我记得很多晚上,
我会坐在家里

,就像,集中注意力,
试图感受原力,但

我什么都感觉不到,别担心。

(笑声

) 后来,我成为了一名科学家。

我加入了麻省理工学院
,开始研究无线信号。

这些是 Wi-Fi
或蜂窝系统之类的东西

,我在该领域做了很多工作。

但是,再一次,这个原力的东西
一直在唠叨我

,在某些时候,我就像,

“等一下,这些无线信号——
它们就像原力一样。”

所以如果你想一想,

无线信号
,它们穿过空间,

穿过障碍物
、墙壁和遮挡物,

其中一些,

它们反射到我们的身体上,
因为我们的身体充满了水,

其中一些微小的反射,

他们回来了。

如果,只要我有一个
可以感知这些微小反射的设备,

那么我就能
感觉到我看不见的人。

所以我开始和我的学生
一起制作这样一个设备

,我想向你展示我们的
一些早期成果。

所以在这里,你看到我的学生站着

,这是我们的设备。

我们将把设备
放在另一个办公室的墙后面

,我们将
在他移动时监视他。

这个红点正在
使用无线信号跟踪他。

如您所见,红点
非常准确地跟踪他的动作,

完全基于他的身体
与周围无线信号的交互方式。

相当准确,不是吗?

他没有可穿戴设备,什么都没有。

(掌声)

现在你可能想知道,我们

怎么可能

没有
任何可穿戴设备的情况下,通过墙壁感知和跟踪人

,最
容易想到的类比就是雷达。

相信很多人
都看过这张图。

你向天空发射一个无线信号,

它被一些飞机反射
回来,

然后你开始探测这些飞机。

但如果它只是雷达,

那么我们将在 50 年前拥有它。

所以它不仅仅是雷达。

有两个关键区别。

所以第一个区别,当然——

你不能像雷达一样,只是
向某人发射无线电力。

您将
像在微波炉中一样煎炸它们。

不要那样做。

所以这意味着你必须
能够处理非常微弱的信号

,这意味着你的设备
必须非常敏感。

第二个区别是,与天空不同的是
,天空是空的——

如果你幸运的话
,你可以在那里赶上一架飞机。

比如,看看房间

,看看有多少物体
和人。

所以在室内环境中,信号
不仅从人身上反射,

如果从人身上
、地板、天花板

、周围其他人身上

反射出来,你会得到非常复杂的反射

,同样的信号
从我身上反射出来,然后从你身上反射出来,

然后离开天花板,
然后离开地板。

你必须弄明白那些乱七八糟的东西。

但我们很幸运。

我们来的正是时候。

所以有两件事帮助了我们。

首先是无线电技术
已经发展了很多

,在过去十年中,

无线电技术
变得更加强大,

因此我们能够制造出
非常灵敏的无线电

,可以感知微弱和微小的射频信号。

第二件事:机器学习。

所以你不断听到关于机器学习的消息


最近机器学习

在深度学习方面发生了一场革命

,这使我们能够构建

能够理解无线信号
并解释它们的机器学习模型,

以便他们知道
环境中发生了什么。

所以如果你想一想
,收音机就像我们设备的耳朵

,机器
学习就像大脑

,它们加在一起就是
一个非常强大的设备。

那么对于人们
使用无线信号,我们还能感知到什么?

睡觉。

事实上,睡眠
对我来说是非常珍贵的,

因为我的睡眠是一场灾难。

(笑声)

所以一件事是当你开始
处理一些生理信号时

,你发现你的信号很糟糕。

(笑声)

所以你可以看到为什么我们可以捕捉睡眠,

因为
当他走路时,设备会在他上床睡觉时看到他,

当他停止在床上翻来覆去时,

当他下床时

,睡眠的衡量标准
就是 人们称之为活动。

它基于运动。

但事实证明
,我们实际上可以

在更重要的层面上获得睡眠。

我们可以
了解睡眠期间发生的脑电波变化

所以,你们中的许多人可能知道
,当我们入睡时,

我们的脑电波会发生变化
,我们会进入不同的阶段:

清醒、轻度睡眠、深度睡眠
和快速眼动,或快速眼动。

这些阶段当然
与睡眠障碍有关,

但也
与各种疾病有关。

例如,快速眼动
障碍与抑郁症有关。

深度睡眠
障碍与阿尔茨海默病有关。

所以如果你想进行睡眠分期,

今天,你会把人
送到医院,

他们把所有这些
电极放在他们的头上

,他们让他们像那样睡觉。

(笑声)

这不是一个真正快乐的经历。

那么,如果我告诉
你我可以做同样的事情,


在人的身体上没有任何这些电极呢?

所以这是我们的设备,

传输非常低功率的
无线信号,

使用 AI 分析反射


在整个晚上吐出睡眠阶段。

所以我们知道,例如
,这个人什么时候在做梦。

不仅如此……

我们甚至可以
在您像那样坐着时让您呼吸,

而无需触摸您。

所以他坐着看书

,这是他的吸气,呼气。

我们让他屏住呼吸

,你会看到信号
保持在一个稳定的水平,

因为他在呼气。

他没有吸气。

我想放大信号。

这是和以前一样的信号。

这些是吸气,

这些是呼气。

你看到信号上的这些光点了吗?

这些不是噪音。

它们是他的心跳。

你可以看到他们逐节拍。

所以我想在这里停一下
,给你看一个现场演示。

Zach 将帮助我进行演示

,我们将使用该设备
来监测 Zach 的呼吸。

所以
你在这里看到的这个白盒子就是设备

,扎克正在打开它

……让我们看看他是否呼吸良好。

所以我们要
和另一个人在视频中做的一样,

所以无线信号正在通过,

它接触到 Zach 的身体

,它反射回设备

,我们想要监控他的呼吸,
他的吸气 - 呼气动作。

所以我们看到吸气、呼气——

所以看,这些起伏
是扎克的呼吸。

吸气,呼气。

(掌声)

所以,他可以呼吸了。

(笑声)

Zach,请你屏住呼吸好吗?

好的,所以现在他屏住了呼吸,

所以你看到信号保持
在一个稳定的水平

,这是他的心跳。

打,打,打,打,打。

(掌声)

好的,扎克,你又可以呼吸了。

(笑声)

我们不想在这里发生事故。

(笑声)

好的,谢谢。

(掌声)

所以大家可以看到,我们有这个

设备可以为你监测这么多的
生理信号

,这个设备真正有趣的

是,它不需要任何可穿戴设备就可以完成这一切

不需要
人们改变他的行为

或 穿任何东西
或收取任何特别的东西。

这让医生非常兴奋,

因为医生,

他们总是想知道
更多关于病人的信息,

尤其是在家里

,这
在慢性病中尤其如此,

比如肺部疾病,比如 COPD,

或者心力衰竭或阿尔茨海默氏症
,甚至抑郁症。

所有这些慢性病
都非常重要。

事实上——也许你知道——

美国三分之二的医疗保健费用

是由慢性病引起的。

但是关于慢性病真正有趣的

是,例如,当一个人

有一个
导致医院和急诊室的

问题时,这个问题不会在一夜之间发生。

其实,事情是慢慢发生的。

因此,如果我们可以
在家中监测慢性病患者,

我们就可以检测到他们的呼吸、
心跳、活动能力、睡眠的变化

——我们可以在紧急情况
发生之前发现它们

并让医生更早地进行干预,

这样我们就可以避免住院。

事实上,今天我们正在

不同疾病类别的多位医生合作。

所以我真的很兴奋,

因为我们已经为许多患者部署了该设备

我们已经
为患有慢性阻塞性肺病

(一种肺部疾病)的

患者、患有阿尔茨海默氏症的

患者、患有抑郁症和焦虑症的患者

以及患有帕金森氏症的患者部署了该设备。

我们正在与医生
合作,改善他们的生活,

更好地了解这种疾病。

所以当我开始的时候,我告诉过

你我真的很着迷
于星球大战和星球大战中的原力

,事实上,我仍然
非常着迷,

即使是现在,作为一个成年人,对星球大战,

等待 下一部电影。

但我现在

对这股新的无线信号力量

以及
用这种新力量改变医疗保健的潜力感到非常着迷和兴奋。

我们部署的其中一名患者实际上是我的阿姨。

她有心力衰竭

,我相信
观众中的许多

人都有患有慢性病的父母、祖父母和亲人。

所以我想让你和我一起想象一个未来

,在每个
有慢性病患者的家庭中,

都有一个像这个设备一样的设备
坐在后台

,被动地监测这个慢性病患者的

睡眠、呼吸、健康
状况,

以及之前 发生紧急情况时,

它会检测到生理信号的退化

并提醒医生

,从而避免住院。

这可以改变
我们今天所知道的医疗保健,

改善我们对
慢性病的理解

,并挽救许多生命。

谢谢你。

(掌声)

Helen Walters:Dina,非常感谢。

也谢谢你,扎克。

很高兴你能呼吸。

所以迪娜,这太棒了。

积极的应用令人难以置信。

但是,框架是什么,
例如围绕此的道德框架?

您正在采取什么措施来防止
这项技术被

用于其他可能不太积极
的应用类型?

Dina Katabi:是的,这是
一个非常重要的问题,当然,

例如,滥用怎么办,

或者,我猜你可以说,
关于原力的黑暗面?

HW:对对对。

(笑声)

DK:所以我们实际上有一些技术

可以防止人们

未经他们同意的情况下试图使用这个设备来监控某人。

因为设备了解空间,

它会要求您
通过某些动作来

证明您可以访问该空间,

并且
您是您要求设备监控的人。

所以在技术方面,

我们有
我们整合的技术来防止滥用,

而且,我认为政策也有
作用,就像其他一切一样

,希望通过这两者,
我们可以控制任何滥用。

HW:太棒了。 太感谢了。

DK:谢谢。

(掌声)