An AI smartwatch that detects seizures Rosalind Picard

This is Henry,

a cute boy,

and when Henry was three,

his mom found him having
some febrile seizures.

Febrile seizures are seizures that occur
when you also have a fever,

and the doctor said,

“Don’t worry too much.
Kids usually outgrow these.”

When he was four,
he had a convulsive seizure,

the kind that you lose
consciousness and shake –

a generalized tonic-clonic seizure –

and while the diagnosis of epilepsy
was in the mail,

Henry’s mom went to get him
out of bed one morning,

and as she went in his room,

she found his cold, lifeless body.

Henry died of SUDEP,

sudden unexpected death in epilepsy.

I’m curious how many of you
have heard of SUDEP.

This is a very well-educated audience,
and I see only a few hands.

SUDEP is when an otherwise
healthy person with epilepsy

dies and they can’t attribute it
to anything they can find in an autopsy.

There is a SUDEP
every seven to nine minutes.

That’s on average two per TED Talk.

Now, a normal brain
has electrical activity.

You can see some of the electrical waves

coming out of this picture
of a brain here.

And these should look
like typical electrical activity

that an EEG could read on the surface.

When you have a seizure,
it’s a bit of unusual electrical activity,

and it can be focal.

It can take place
in just a small part of your brain.

When that happens,
you might have a strange sensation.

Several could be happening
here in the audience right now,

and the person next to you
might not even know.

However, if you have a seizure
where that little brush fire spreads

like a forest fire over the brain,

then it generalizes,

and that generalized seizure
takes your consciousness away

and causes you to convulse.

There are more SUDEPs
in the United States every year

than sudden infant death syndrome.

Now, how many of you have heard
of sudden infant death syndrome?

Right? Pretty much every hand goes up.

So what’s going on here?

Why is this so much more common
and yet people haven’t heard of it?

And what can you do to prevent it?

Well, there are two things,
scientifically shown,

that prevent or reduce the risk of SUDEP.

The first is: “Follow
your doctor’s instructions,

take your medications.”

Two-thirds of people who have epilepsy

get it under control
with their medications.

The second thing that reduces
the risk of SUDEP is companionship.

It’s having somebody there
at the time that you have a seizure.

Now, SUDEP, even though
most of you have never heard of it,

is actually the number two cause
of years of potential life lost

of all neurological disorders.

The vertical axis is the number of deaths

times the remaining life span,

so higher is much worse impact.

SUDEP, however, unlike these others,

is something that people right here
could do something to push that down.

Now, what is Roz Picard, an AI researcher,
doing here telling you about SUDEP, right?

I’m not a neurologist.

When I was working at the Media Lab
on measurement of emotion,

trying to make our machines
more intelligent about our emotions,

we started doing a lot of work
measuring stress.

We built lots of sensors

that measured it
in lots of different ways.

But one of them in particular

grew out of some of this very old work
with measuring sweaty palms

with an electrical signal.

This is a signal of skin conductance

that’s known to go up
when you get nervous,

but it turns out it also goes up with
a lot of other interesting conditions.

But measuring it with wires on your hand
is really inconvenient.

So we invented a bunch of other ways
of doing this at the MIT Media Lab.

And with these wearables,

we started to collect the first-ever
clinical quality data 24-7.

Here’s a picture of what that looked like

the first time an MIT student collected
skin conductance on the wrist 24-7.

Let’s zoom in a little bit here.

What you see is 24 hours
from left to right,

and here is two days of data.

And first, what surprised us

was sleep was the biggest
peak of the day.

Now, that sounds broken, right?

You’re calm when you’re asleep,
so what’s going on here?

Well, it turns out
that our physiology during sleep

is very different
than our physiology during wake,

and while there’s still a bit of a mystery

why these peaks are usually
the biggest of the day during sleep,

we now believe they’re related
to memory consolidation

and memory formation during sleep.

We also saw things
that were exactly what we expected.

When an MIT student
is working hard in the lab

or on homeworks,

there is not only emotional stress,
but there’s cognitive load,

and it turns out that cognitive load,
cognitive effort, mental engagement,

excitement about learning something –

those things also make the signal go up.

Unfortunately, to the embarrassment
of we MIT professors,

(Laughter)

the low point every day
is classroom activity.

Now, I am just showing you
one person’s data here,

but this, unfortunately,
is true in general.

This sweatband has inside it
a homebuilt skin-conductance sensor,

and one day, one of our undergrads
knocked on my door

right at the end of the December semester,

and he said, “Professor Picard,

can I please borrow
one of your wristband sensors?

My little brother has autism,
he can’t talk,

and I want to see
what’s stressing him out.”

And I said, “Sure, in fact,
don’t just take one, take two,”

because they broke easily back then.

So he took them home,
he put them on his little brother.

Now, I was back in MIT,
looking at the data on my laptop,

and the first day, I thought,
“Hmm, that’s odd,

he put them on both wrists
instead of waiting for one to break.

OK, fine, don’t follow my instructions.”

I’m glad he didn’t.

Second day – chill.
Looked like classroom activity.

(Laughter)

A few more days ahead.

The next day, one wrist signal was flat

and the other had
the biggest peak I’ve ever seen,

and I thought, “What’s going on?

We’ve stressed people out at MIT
every way imaginable.

I’ve never seen a peak this big.”

And it was only on one side.

How can you be stressed on one side
of your body and not the other?

So I thought one or both sensors
must be broken.

Now, I’m an electroengineer by training,

so I started a whole bunch of stuff
to try to debug this,

and long story short,
I could not reproduce this.

So I resorted to old-fashioned debugging.

I called the student at home on vacation.

“Hi, how’s your little brother?
How’s your Christmas?

Hey, do you have any idea
what happened to him?”

And I gave this particular date and time,

and the data.

And he said, “I don’t know,
I’ll check the diary.”

Diary? An MIT student keeps a diary?

So I waited and he came back.

He had the exact date and time,

and he says, “That was right before
he had a grand mal seizure.”

Now, at the time, I didn’t know
anything about epilepsy,

and did a bunch of research,

realized that another student’s dad
is chief of neurosurgery

at Children’s Hospital Boston,

screwed up my courage
and called Dr. Joe Madsen.

“Hi, Dr. Madsen,
my name’s Rosalind Picard.

Is it possible somebody could have

a huge sympathetic
nervous system surge” –

that’s what drives the skin conductance –

“20 minutes before a seizure?”

And he says, “Probably not.”

He says, “It’s interesting.

We’ve had people whose hair
stands on end on one arm

20 minutes before a seizure.”

And I’m like, “On one arm?”

I didn’t want to tell him that, initially,

because I thought this was too ridiculous.

He explained how this could
happen in the brain,

and he got interested.
I showed him the data.

We made a whole bunch more devices,
got them safety certified.

90 families were being
enrolled in a study,

all with children who were going
to be monitored 24-7

with gold-standard EEG on their scalp

for reading the brain activity,

video to watch the behavior,

electrocardiogram – ECG –
and now EDA, electrodermal activity,

to see if there was
something in this periphery

that we could easily pick up,
related to a seizure.

We found, in 100 percent
of the first batch of grand mal seizures,

this whopper of responses
in the skin conductance.

The blue in the middle, the boy’s sleep,

is usually the biggest peak of the day.

These three seizures you see here
are popping out of the forest

like redwood trees.

Furthermore, when you couple
the skin conductance at the top

with the movement from the wrist

and you get lots of data
and train machine learning and AI on it,

you can build an automated AI
that detects these patterns

much better than just
a shake detector can do.

So we realized that we needed
to get this out,

and with the PhD work of Ming-Zher Poh

and later great improvements by Empatica,

this has made progress and the seizure
detection is much more accurate.

But we also learned some other things
about SUDEP during this.

One thing we learned is that SUDEP,

while it’s rare after
a generalized tonic-clonic seizure,

that’s when it’s most likely
to happen – after that type.

And when it happens,
it doesn’t happen during the seizure,

and it doesn’t usually happen
immediately afterwards,

but immediately afterwards,

when the person just seems
very still and quiet,

they may go into another phase,
where the breathing stops,

and then after the breathing stops,
later the heart stops.

So there’s some time
to get somebody there.

We also learned that there is a region
deep in the brain called the amygdala,

which we had been studying
in our emotion research a lot.

We have two amygdalas,

and if you stimulate the right one,

you get a big right
skin conductance response.

Now, you have to sign up right now
for a craniotomy to get this done,

not exactly something
we’re going to volunteer to do,

but it causes a big right skin
conductance response.

Stimulate the left one, big left
skin conductance response on the palm.

And furthermore, when somebody
stimulates your amygdala

while you’re sitting there
and you might just be working,

you don’t show any signs of distress,

but you stop breathing,

and you don’t start again
until somebody stimulates you.

“Hey, Roz, are you there?”

And you open your mouth to talk.

As you take that breath to speak,

you start breathing again.

So we had started with work on stress,

which had enabled us
to build lots of sensors

that were gathering
high quality enough data

that we could leave the lab
and start to get this in the wild;

accidentally found a whopper
of a response with the seizure,

neurological activation that can cause
a much bigger response

than traditional stressors;

lots of partnership with hospitals
and an epilepsy monitoring unit,

especially Children’s Hospital Boston

and the Brigham;

and machine learning and AI on top of this

to take and collect lots more data

in service of trying
to understand these events

and if we could prevent SUDEP.

This is now commercialized by Empatica,

a start-up that I had
the privilege to cofound,

and the team there has done an amazing job
improving the technology

to make a very beautiful sensor

that not only tells time and does steps
and sleep and all that good stuff,

but this is running real-time
AI and machine learning

to detect generalized
tonic-clonic seizures

and send an alert for help

if I were to have a seizure
and lose consciousness.

This just got FDA-approved

as the first smartwatch
to get approved in neurology.

(Applause)

Now, the next slide is what made
my skin conductance go up.

One morning, I’m checking my email

and I see a story from a mom

who said she was in the shower,

and her phone was
on the counter by the shower,

and it said her daughter
might need her help.

So she interrupts her shower and goes
running to her daughter’s bedroom,

and she finds her daughter
facedown in bed, blue and not breathing.

She flips her over – human stimulation –

and her daughter takes a breath,
and another breath,

and her daughter turns pink and is fine.

I think I turned white reading this email.

My first response is,
“Oh no, it’s not perfect.

The Bluetooth could break,
the battery could die.

All these things could go wrong.
Don’t rely on this.”

And she said, “It’s OK.
I know no technology is perfect.

None of us can always
be there all the time.

But this, this device plus AI

enabled me to get there in time
to save my daughter’s life.”

Now, I’ve been mentioning children,

but SUDEP peaks, actually,
among people in their 20s, 30s and 40s,

and the next line I’m going to put up

is probably going to make
some people uncomfortable,

but it’s less uncomfortable
than we’ll all be

if this list is extended
to somebody you know.

Could this happen to somebody you know?

And the reason I bring up
this uncomfortable question

is because one in 26 of you
will have epilepsy at some point,

and from what I’ve been learning,

people with epilepsy often don’t tell
their friends and their neighbors

that they have it.

So if you’re willing to let them
use an AI or whatever

to summon you in a moment
of possible need,

if you would let them know that,

you could make a difference in their life.

Why do all this hard work to build AIs?

A couple of reasons here:

one is Natasha, the girl who lived,

and her family wanted me
to tell you her name.

Another is her family

and the wonderful people out there

who want to be there to support people
who have conditions

that they’ve felt uncomfortable
in the past mentioning to others.

And the other reason is all of you,

because we have the opportunity
to shape the future of AI.

We can actually change it,

because we are the ones building it.

So let’s build AI

that makes everybody’s lives better.

Thank you.

(Applause)

这是亨利,

一个可爱的男孩

,当亨利三岁时,

他的妈妈发现他有
一些高热惊厥。

热性惊厥是
在发烧时发生的惊厥

,医生说:

“不要太担心。
孩子们通常会长大。”

当他四岁时,
他发生了一次惊厥性癫痫发作

,那种你会失去
意识并颤抖的那种——

一种全身性强直-阵挛性癫痫发作

——当癫痫的诊断
在邮件中时,

亨利的妈妈去把他
从床上拉起来 早上

,当她走进他的房间时,

她发现了他冰冷、毫无生气的身体。

亨利死于 SUDEP,

癫痫突然意外死亡。

我很好奇你们中
有多少人听说过 SUDEP。

这是一个受过良好教育的观众
,我只看到几手牌。

SUDEP 是指一个原本
健康的癫痫患者

死亡,他们无法将其
归因于他们在尸检中发现的任何东西。

每七到九分钟就有一次 SUDEP。

每个 TED 演讲平均有两个。

现在,一个正常的大脑
有电活动。

你可以在这里看到

从这张
大脑图片中发出的一些电波。

这些应该

看起来像脑电图可以在表面上读取的典型电活动。

当您癫痫发作时,
这是一种不寻常的电活动,

并且可能是局灶性的。

它可以发生
在你大脑的一小部分。

发生这种情况时,
您可能会有一种奇怪的感觉。 现在观众中

可能正在发生一些事情

而你旁边的人
可能甚至都不知道。

然而,如果你癫痫发作时
,那小小的灌木丛之火

像森林大火一样蔓延到大脑上,

那么它就会泛化,

而这种泛化的癫痫发作
会带走你的意识

并导致你抽搐。

在美国,每年的 SUDEP

比婴儿猝死综合症还要多。

现在,你们中有多少人听说
过婴儿猝死综合症?

对? 几乎每一只手都举起来。

那么这里发生了什么?

为什么这种情况如此普遍
,而人们却没有听说过?

你能做些什么来防止它呢?

好吧,科学证明有两件事

可以预防或降低 SUDEP 的风险。

第一个是:“
听从医生的指示,

服药。”

三分之二的癫痫

患者通过药物得到控制。

降低 SUDEP 风险的第二件事是陪伴。

你癫痫发作的时候有人在那里。

现在,SUDEP,即使
你们中的大多数人从未听说过它,

它实际上是所有神经系统疾病
中潜在生命损失多年的第二大原因

纵轴是死亡人数

乘以剩余寿命,

因此影响越差。

然而,与其他人不同的是,SUDEP

是这里的人们
可以做些什么来推动它。

现在,人工智能研究员 Roz Picard
在这里告诉你关于 SUDEP 的内容,对吧?

我不是神经科医生。

当我在媒体实验室
从事情绪测量工作时,

试图让我们的机器
对我们的情绪更加智能,

我们开始做很多工作来
测量压力。

我们建造了许多传感器

,以
多种不同的方式对其进行测量。

但其中一个特别

是从这项非常古老的工作中发展
而来的

,即用电信号测量出汗的手掌。

这是一个已知的皮肤电导信号,

当你紧张

时它会上升,但事实证明,它也会
随着许多其他有趣的情况而上升。

但是用手上的电线测量它
真的很不方便。

所以我们
在麻省理工学院媒体实验室发明了很多其他方法来做到这一点。

有了这些可穿戴设备,

我们开始 24-7 收集第一个
临床质量数据。

是麻省理工学院学生第一次
在 24-7 收集手腕上的皮肤电导时的照片。

让我们在这里放大一点。

你看到的是24小时
从左到右

,这里是两天的数据。

首先,让我们感到惊讶的

是睡眠
是一天中最大的高峰。

现在,这听起来很糟糕,对吧?

你睡觉的时候很平静,
所以这里发生了什么事?

好吧,事实证明
,我们在睡眠

期间的生理机能与我们在清醒时的生理机能有很大不同

,虽然

这些高峰
通常是一天中最大的睡眠仍然有一点神秘,

但我们现在相信它们与记忆有关

睡眠期间的巩固和记忆形成。

我们还
看到了完全符合我们预期的事情。

当麻省理工学院的学生
在实验室

或家庭作业中努力工作时,

不仅有情绪压力,
还有认知负荷

,事实证明,认知负荷、
认知努力、精神投入、

对学习的兴奋——

这些事情也会使 信号上升。

不幸的是,让
我们麻省理工学院的教授们尴尬的是,

(笑声)

每天的低谷
是课堂活动。

现在,我只是在这里向您展示
一个人的数据,

但不幸的
是,这通常是正确的。

这条防汗带里面有
一个自制的皮肤电导传感器,

有一天,我们的一个本科生

在 12 月学期结束时敲响了我的门

,他说:“皮卡德教授,

我能借
你一个腕带传感器吗? ?

我的小弟弟有自闭症,
他不会说话

,我想看看
他有什么压力。”

我说,“当然,事实上,
不要只拿一个,拿两个,”

因为他们当时很容易坏掉。

于是他把它们带回家,
戴在他的小弟弟身上。

现在,我回到麻省理工学院,
看着笔记本电脑上的数据

,第一天,我想,
“嗯,这很奇怪,

他把它们戴在两只手腕上,
而不是等着一只折断。

好吧,好吧,不要” 不要听从我的指示。”

我很高兴他没有。

第二天——冷静。
看起来像课堂活动。

(笑声)

再过几天。

第二天,一个手腕信号是平的

,另一个是
我见过的最大峰值

,我想,“这是怎么回事?

我们在麻省理工学院给人们施加了
各种可以想象的压力。

我从未见过峰值 这么大。”

这只是一方面。

你怎么能在
身体的一侧而不是另一侧受到压力?

所以我认为必须损坏一个或两个传感器

现在,我是一名受过培训的电子工程师,

所以我开始了一大堆东西
来尝试调试这个

,长话短说,
我无法重现这个。

所以我求助于老式的调试。

我打电话给那个放假在家的学生。

“你好,你的小弟弟好吗?
你的圣诞节过得怎么样?

嘿,你知道
他怎么了吗?”

我给出了这个特定的日期和时间,

以及数据。

他说:“我不知道,
我去看看日记。”

日记? 麻省理工学院的学生写日记?

所以我等他回来。

他有确切的日期和时间

,他说,“那是在
他癫痫大发作之前。”

现在,当时我
对癫痫一无所知

,做了一堆研究,

意识到另一个学生的父亲
是波士顿儿童医院的神经外科主任,


鼓起勇气打电话给乔·马德森医生。

“嗨,马德森博士,
我叫罗莎琳德·皮卡德。

有没有可能有人会

出现巨大的
交感神经系统激增”——

这就是驱动皮肤电导的原因——

“癫痫发作前 20 分钟?”

他说,“可能不会。”

他说:“这很有趣。在癫痫发作前 20 分钟,

我们发现有人头发
竖立在一只手臂上

。”

我想,“在一只手臂上?”

起初我不想告诉他,

因为我觉得这太荒谬了。

他解释了这是
如何在大脑中发生的

,他对此产生了兴趣。
我给他看了数据。

我们制造了更多设备,
并通过了安全认证。

90 个家庭
参加了一项研究,

所有孩子都
将接受 24-7

小时的监测,在头皮上使用黄金标准 EEG

来阅读大脑活动、

观看行为的视频、

心电图 - ECG

  • 现在是 EDA ,皮肤电活动

,看看
这个外围是否有什么

东西可以很容易地捡起,
与癫痫发作有关。

我们
在第一批癫痫大发作的 100%

中发现了皮肤电导的这种巨大反应。

中间的蓝色,男孩的睡眠,

通常是一天中最大的高峰。

你在这里看到的这三起癫痫发作就像红杉树一样
从森林中冒出来

此外,当您
将顶部的皮肤电导

与手腕的运动相结合

并获得大量数据
并在其上训练机器学习和 AI 时,

您可以构建一个自动化 AI,它可以

比仅
使用抖动检测器更好地检测这些模式 做。

所以我们意识到我们需要
解决这个问题,

并且通过 Ming-Zher Poh 的博士工作

以及后来 Empatica 的重大改进,

这已经取得了进展,并且癫痫发作
检测更加准确。


在此期间,我们还了解了有关 SUDEP 的其他一些信息。

我们学到的一件事是 SUDEP,

虽然在
全身强直阵挛发作后很少见

,但它最有
可能发生 - 在那种类型之后。

当它发生时,
它不会在癫痫发作期间

发生,而且通常不会
立即发生,

但紧接着,

当这个人看起来
非常静止和安静时,

他们可能会进入另一个阶段
,呼吸停止,

然后在呼吸停止
后,心脏停止。

所以有一些
时间可以派人去那里。

我们还了解到大脑深处有一个区域
叫做杏仁核,

我们在情绪研究中一直在研究它。

我们有两个杏仁核

,如果你刺激正确的杏仁核,

你会得到一个很大的正确
皮肤电导反应。

现在,您必须立即注册
进行开颅手术才能完成这项工作,这

并不完全是
我们自愿做的事情,

但它会引起很大的右皮肤
电导反应。

刺激左一、手掌大左
皮肤电导反应。

此外,当你坐在那里时有人
刺激你的杏仁核,

而你可能只是在工作,

你不会表现出任何痛苦的迹象,

但你会停止呼吸,

直到有人刺激你才重新开始。

“嘿,罗兹,你在吗?”

你张开嘴说话。

当你屏住呼吸说话时,

你又开始呼吸。

因此,我们从压力研究开始,

这使我们
能够构建大量传感器

,这些传感器能够收集
足够高质量的数据

,我们可以离开实验室
并开始在野外得到这些数据;

意外发现
癫痫发作的巨大反应,

神经系统激活可以引起

比传统压力源更大的反应;

与医院和癫痫监测部门建立了许多合作伙伴关系

尤其是波士顿儿童医院

和布莱根医院;

机器学习和人工智能在此基础

上获取和收集更多数据

,以
尝试了解这些事件

以及我们是否可以防止 SUDEP。

这现在由 Empatica 商业化

,我
有幸与他人共同创立了一家初创公司,

那里的团队做了一项了不起的工作,
改进了技术

,制造了一个非常漂亮的传感器

,它不仅可以显示时间,还可以计算步数
和睡眠等等 好东西,

但这是运行实时
人工智能和机器学习

来检测全身性
强直-阵挛性癫痫发作,

在我癫痫发作
并失去知觉时发出求助警报。

这刚刚获得 FDA 批准

,成为第一款
在神经病学领域获得批准的智能手表。

(掌声)

现在,下一张幻灯片是什么让
我的皮肤电导上升。

一天早上,我正在查看我的电子邮件

,看到一位妈妈的故事,

她说她正在洗澡

,她的手机
在淋浴间旁边的柜台上

,上面说她的女儿
可能需要她的帮助。

于是她中断了淋浴,
跑到女儿的卧室,

发现女儿
脸朝下躺在床上,脸色苍白,没有呼吸。

她把她翻过来——人类的刺激

——她的女儿吸了一口气,
又吸了一口气

,她的女儿变成了粉红色,一切都好。

我想我读了这封邮件就变白了。

我的第一反应是,
“哦,不,它并不完美

。蓝牙可能会坏
,电池可能会没电。

所有这些都可能出错。
不要依赖这个。”

她说:“没关系。
我知道没有技术是完美的。

我们没有人可以
一直在那里。

但是这个,这个设备加上人工智能

让我能够及时到达那里
挽救我女儿的生命。”

现在,我一直在提到孩子

,但实际上,
SUDEP 在 20 多岁、30 多岁和 40 多岁的人群中达到顶峰

,我要提出的下一条线

可能会让
一些人感到不舒服,

但它比

如果此列表扩展
到您认识的人,我们都会。

这会发生在你认识的人身上吗?

我提出
这个令人不安的问题的原因

是因为你们中的 26 人中
会有一个人在某个时候会患上癫痫症,

而据我所知,

患有癫痫症的人通常不会告诉
他们的朋友和

邻居他们患有癫痫症。

因此,如果您愿意让他们
使用 AI 或其他任何东西

在可能需要的时候召唤您

如果您让他们知道这一点,

您就可以改变他们的生活。

为什么要为构建 AI 付出如此多的努力?

这里有几个原因:

一个是娜塔莎

,她的家人想让
我告诉你她的名字。

另一个是她的家人

那些想要在那里支持
那些

在过去向他人提及时感到不舒服的人的人。

另一个原因是你们所有人,

因为我们有
机会塑造人工智能的未来。

我们实际上可以改变它,

因为我们是建造它的人。

因此,让我们构建

让每个人的生活更美好的人工智能。

谢谢你。

(掌声)