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Do you know how many steps
you took today?

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How many calories you burned?
How many people you met?

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Or how many hours you slept?

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If you knew these things,
it might make you healthier,

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or even save your life.

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And finding them out
is no longer very difficult.

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These days, there's almost nothing
we can't measure about our lives,

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and we can do it with stuff
that almost all of us own.

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Whether it's apps on our phones
or the latest gadgets...

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You wear it as a headband,
so like this when you're asleep.

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..the promise is
that our health will be transformed.

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We're almost at Day Zero
of a whole new world of medicine.

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There are now doctors
giving out apps

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the way they used to prescribe
pills or surgery.

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That feels very Star Trek to me.

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Three volunteers are going
to join me

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to put this medical
revolution to the test.

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I've really got to up my game.

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These three weeks have been quite
a revelation for me.

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That's absolutely gobsmacking.

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I'm going to find out whether simply
monitoring ourselves can change us.

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Can this self-monitoring revolution
be the key to longer,

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healthier lives?

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I'm Kevin Fong.

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I'm getting ready for a day
on the medical frontline.

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I'm going to see how fundamental
the ability to monitor ourselves is

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to saving lives.

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So I'm here in the crew room
of London's Air Ambulance.

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These guys are ready to
fly off to the scene of an emergency

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at a moment's notice,

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and all they're waiting for
is for that klaxon to go.

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London's air ambulance exists
to get medical staff

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to the scene of an emergency
as fast as possible.

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With a senior trauma doctor
on board,

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they're trained to deal
with almost any situation.

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The team are expected
to be airborne

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within four minutes of the klaxon
sounding.

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There's no room for a film crew
aboard,

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so I'm going to be on my own
with this.

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On board are all the tools
the team needs to save lives.

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They've even performed heart surgery
at the roadside.

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But in many ways, the most important
thing of all on this helicopter

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is the monitoring equipment.

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If you don't know what's
going on inside your patient's body,

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you've got no hope of fixing them.

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We've been called out
to treat someone

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who's suffered
a severe head injury.

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I think I'll just put
a few stitches in that first.

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As soon as possible,

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the patient is hooked up
to the team's monitoring equipment.

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This is our monitor pack,

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and this carries all the vital bits
of kits, essentially,

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that we use to monitor heart rate,

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blood pressure, their oxygen level
and the gases that they breathe out.

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Essentially, this is a surrogate

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for everything
in the emergency department.

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We can have as much surgical
kit as we want,

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but it really is essentially useless

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if we can't tell what's happening
with the patient.

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So the team are dealing with quite
a serious head injury there.

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In addition to delivering a doctor
and a paramedic very rapidly,

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they're also able to bring with them
some quite advanced monitoring,

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the sort of thing you could get
in an intensive care unit, really,

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small enough and portable enough

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that they're able to describe that
injury in great detail

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before they ever get anywhere near
the hospital.

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Quite simply,

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this small box can make the
difference between life and death.

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The patient's been stabilised.

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The team will go with him by
ambulance to the nearest hospital.

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The crisis is over,
and the outlook is positive.

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You know, this is much more
than just a helicopter,

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it's essentially a mobile
accident and emergency unit.

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And it's possible

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only because you can take that
incredible suite of monitoring

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that you would normally find
in a hospital,

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shrink it down and stick it
in the back of a vehicle like that.

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But what if everybody could monitor
themselves to the same degree?

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What if we all had that capability?

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How would that improve our health?

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I'm going to start

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by checking out some
of the latest medical technology.

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But I'm not talking about MRI
scanners or surgical robots.

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I'm not heading to a hospital,
or a doctor's surgery.

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I've come to a sports shop.

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For a few years, people who are far
more committed to exercise than me

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have been using gadgets like these
to help them keep fit.

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You know, these are fundamentally
impressive devices.

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Take, for example, the GPS trackers,

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which grab information
from satellites

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and define your position
with unparalleled accuracy.

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And then there's
the heart rate monitors

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which can measure the faint spread
of electricity across your heart,

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through the full thickness
of your chest.

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In a few years,

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the number of us with wireless
health and fitness devices

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is expected to rise
to almost 200 million.

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When these products started
to become available a few years ago,

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it didn't occur to me that they
would become so advanced

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or deliver such a rich stream
of information.

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And I didn't anticipate

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that self-monitoring
would find its way into medicine.

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But it's beginning to. And that
could make a huge difference,

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so much so
that I've started to think

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that we might be on the brink
of a revolution in healthcare.

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This is a revolution
that takes monitoring

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out of doctors' hands, out of
hospitals, and it gives it to us.

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And by doing that, it places us
at the heart of our own healthcare,

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and makes doctors of all of us.

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There are few people that know
this new world of medicine

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better than Blaine Price.

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He's pretty obsessed
when it comes to the latest gadgets.

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You're pretty into self-monitoring.

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Yes, I get every app going.

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I buy all the devices I can
and try them out.

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And it's great, because I get
to play with all the toys

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and learn lots of things
about myself at the same time.

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'Blaine's gathered together
some of his favourite toys

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'for me to have a look at.'

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What have you got for me here?

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First of all, we've got these,
kind of a glorified pedometer

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to keep track of how many steps you
take, but it's a lot more than that.

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They'll monitor exactly
when you took your steps,

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how active they were and intense
they were, what time of day it was.

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Sleep is one that people
are often interested in.

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So, er, this one, you wear it
as a headband,

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so like this when you're asleep,

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and it measures a bit about your
brain activity.

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It can tell you what
phase of sleep you're in,

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deep sleep, light sleep, REM
and so on.

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And if heart information is
interesting to you,

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we've got a pulse oximeter here.

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Oh, yeah, the sort of stuff
I use in the hospital anyway.

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Sure. And before,
you only could get it in a hospital.

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This is now very inexpensive

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and what it's doing is measuring
cardiac rhythm and blood sats.

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Looks like I'm fairly healthy
at 98 or so.

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From the comfort of our own homes,

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we can now measure
many of our vital signs.

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We can also measure a few things
you might never have thought of.

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There are consumer devices
to check your posture...

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your blood alcohol levels...

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Do a quick jump.
How high you jump...

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And even how quickly
you're eating.

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And much of this, we can do
without even buying any new gadgets.

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There are now tens of thousands
of apps

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available on our phones to track
anything and everything about us.

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In fact, there are hundreds of apps
coming out probably every week

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which are health-related,
able to measure things, log things.

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Some of the latest apps use things
designed for one obvious purpose,

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like a phone's camera,
to do something utterly unexpected.

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We even have apps that can
measure your heart rate

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just by looking at you.
That's amazing.

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Give it a try.
You have to keep fairly still.

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OK, so I'm going to have to shut up
and stay still.

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And it will measure your heart rate
by looking at the colour changes

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in your face, and it might even
get your breathing rate in there.

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So there's the heart rate there
coming in, about 79 or 80.

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And breathing rate about 17.
That's really quite incredible

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because it must be,
the heart rate stuff there

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must be on just seeing
the small differences

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in the change and colour
of my face?

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So as the capillaries sort of swell
up and fall away with every beat?

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Yes, it's the resolution
of the camera that does it.

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The technology here has such
a high resolution in smartphones

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and tablets that we're looking
at the same range

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you would have had in medical
scientific instruments 20 years ago.

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I find that...just gobsmacking,
really.

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Blaine has set up an experiment
to help me find out

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whether this technology
can really make us healthier.

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He's roped me
into taking part as well.

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I'm Kevin, hi. I'm Celia. Celia, hi.

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'Celia, Cathy, and Pam
work together.'

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So I understand that you've
volunteered to be guinea pigs

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for this particular experiment.
Yes, we are the guinea pigs.

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What have we let ourselves in for?

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'They're hoping that by monitoring
themselves,

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'they can overcome an endless
struggle and lose some weight.'

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We're permanently on diets,
aren't we?

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We're all very conscious
about we eat too much

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and we drink too much,
but we love it.

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We all discuss what we ate
last night.

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"Oh, no, I had a glass of wine."
"Well, Celia had three."

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We've got
a set of scales in the office,

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and so every week, we weigh in

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and we keep a chart
of what our weight loss is,

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and sometimes weight gain.

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Until now, this,
standing on a set of scales,

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has been the only form of
self-monitoring that most people do.

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I've got to get
all my jewellery off.

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Moment of truth.
We do this every week, don't we?

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Does it make any difference? No.
I thought you'd been so good!

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Don't forget your watch.
I'll take my watch off.

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Get off, quick!

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OK, Cathy.

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It's stayed the same.
Oh, the same as last time.

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Same as the week before.

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It's the same story
for so many of us.

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There's too much going on
in our lives

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that stops us getting fit
and staying healthy.

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I find it really difficult
to wake up in the morning

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and think about doing some exercise.

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There's quite a lot of ready meals
going on,

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which doesn't help the diet.

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Any excuse.

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If I had all the time in the world,
I would exercise a lot more.

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But, you know, there's just work,
looking after the house,

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picking the children up from school,

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the usual domestic chores
that every mum has.

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So how exactly is Blaine hoping

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that monitoring ourselves can make
a difference to our health?

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There's actually only two
simple things you have to do.

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One is, you've got to carry around
with you a little device here.

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You can stick it in your pocket.

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It'll record how many steps you've
taken.

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The other bit of this study is,

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you need to have a smartphone
to measure your sleep at night.

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It's going to measure, hopefully,
how deeply you're sleeping,

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how well you're sleeping.

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It'll measure the time
you go to bed and wake up.

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So what you'll do is
get an email every day from me

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with a summary of your performance
during the past day,

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how it compares with the past week,

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and also how you compare
with the rest of the group.

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The hope is

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that by simply measuring the number
of steps we take every day,

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we can set ourselves targets
and get motivated to do more.

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And by keeping tabs on our sleep,

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we can find out what helps us
sleep better.

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I'm hoping that it's going
to give me a better understanding

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of what you actually do have to do
to kick-start a healthier life,

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to burn more calories, to
perhaps have a better night's sleep.

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I don't have a particularly
healthy lifestyle

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because I don't do exercise.

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I'm not aware of my health,
shall we say.

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I don't know what
my blood pressure is.

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My sleep pattern these days,
as I've got older, is not good.

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I'm hoping it's going to give me
the enthusiasm to do some exercise

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00:14:03,100 --> 00:14:05,740
because quite honestly,
I find exercise boring!

240
00:14:07,900 --> 00:14:11,060
Every day for the next three weeks,
each of us is going

241
00:14:11,060 --> 00:14:15,540
to be bombarded with numbers -
how much we've slept,

242
00:14:15,540 --> 00:14:20,580
how deeply we slept, how many steps
we've taken, when we took them.

243
00:14:22,220 --> 00:14:25,420
The question is whether
simply seeing those numbers

244
00:14:25,420 --> 00:14:27,340
will be enough to make us change.

245
00:14:34,020 --> 00:14:37,580
But there are people who already
use self-monitoring

246
00:14:37,580 --> 00:14:40,620
to alter their health
and fitness in a fundamental way.

247
00:14:46,820 --> 00:14:49,100
This is Twickenham,
the home of rugby,

248
00:14:49,100 --> 00:14:52,580
and I'm here to join the England
Rugby 7s team while they train.

249
00:14:54,700 --> 00:14:56,460
So if you go along it gives you

250
00:14:56,460 --> 00:14:58,780
pretty much everything you could
want.

251
00:14:58,780 --> 00:15:02,540
'Brett Davison is the team's
Head of Physical Performance.'

252
00:15:02,540 --> 00:15:05,060
..zones which we would have to
specify.

253
00:15:05,060 --> 00:15:06,940
'His players are amongst the most

254
00:15:06,940 --> 00:15:09,340
'closely monitored
people in the world.'

255
00:15:11,460 --> 00:15:14,460
So they've got on a little GPS unit
that sits in a little

256
00:15:14,460 --> 00:15:17,100
neoprene pocket on their jersey
between their shoulder blades.

257
00:15:17,100 --> 00:15:19,100
There we go.

258
00:15:19,100 --> 00:15:20,820
And then they've got a heart-rate
strap on,

259
00:15:20,820 --> 00:15:23,220
those two coordinate
between each other

260
00:15:23,220 --> 00:15:26,140
and then the information comes
straight back to us.

261
00:15:26,140 --> 00:15:27,420
'Now, I'm a doctor.

262
00:15:27,420 --> 00:15:29,020
'I'm used to examining people,

263
00:15:29,020 --> 00:15:33,140
'and looking for the subtle
signs of illness and injury.

264
00:15:33,140 --> 00:15:36,540
'And as far as I'm concerned this
international rugby team

265
00:15:36,540 --> 00:15:39,020
'looks more than match ready.

266
00:15:39,020 --> 00:15:42,380
'But Brett sees a lot more than
I can without even

267
00:15:42,380 --> 00:15:44,860
'glancing at the players.

268
00:15:44,860 --> 00:15:48,140
'He does it simply by looking at a
screen full of numbers.'

269
00:15:48,140 --> 00:15:50,380
Run me through what you've got here.

270
00:15:50,380 --> 00:15:52,260
OK, there's obviously speed -

271
00:15:52,260 --> 00:15:54,700
your current, your average and
you maximum.

272
00:15:54,700 --> 00:15:56,860
Heart rate, exactly the same.

273
00:15:56,860 --> 00:15:59,660
Distance, so that's for the whole
training session.

274
00:15:59,660 --> 00:16:03,220
Dynamic stress load, number of
accelerations, decelerations.

275
00:16:03,220 --> 00:16:06,220
High speed running is
the number of metres they've run,

276
00:16:06,220 --> 00:16:07,420
maximum speed.

277
00:16:08,820 --> 00:16:10,300
'All those numbers help Brett

278
00:16:10,300 --> 00:16:13,740
'detect problems well before
any doctor could.'

279
00:16:15,900 --> 00:16:18,380
You can see
the injuries in terms of their speed

280
00:16:18,380 --> 00:16:19,620
or their lack of, usually.

281
00:16:19,620 --> 00:16:22,500
Um, and certainly their running
intensity will be off

282
00:16:22,500 --> 00:16:26,140
what we know it could be for that
particular individual.

283
00:16:26,140 --> 00:16:28,740
This is Geoff's trace
and at the moment

284
00:16:28,740 --> 00:16:31,020
he's at 18-odd kilometres per hour,

285
00:16:31,020 --> 00:16:33,220
which is not very fast for
these guys.

286
00:16:35,900 --> 00:16:39,300
So you can certainly start to see
where somebody's struggling.

287
00:16:39,300 --> 00:16:42,740
'And the information Brett gathers
turns out to be an incredibly

288
00:16:42,740 --> 00:16:44,980
'sensitive indicator of injury.'

289
00:16:46,660 --> 00:16:49,940
It picks up their step balance,
their left-right step balance,

290
00:16:49,940 --> 00:16:51,500
uh, through the, accelerometer.

291
00:16:51,500 --> 00:16:54,180
So, we can tell how badly
somebody's limping,

292
00:16:54,180 --> 00:16:56,060
or how much they might be
favouring a leg.

293
00:16:56,060 --> 00:16:58,420
And this lad got hit on the knee.

294
00:16:58,420 --> 00:17:01,540
And the difference between his left
and his right is about

295
00:17:01,540 --> 00:17:03,100
one and a half per cent.

296
00:17:03,100 --> 00:17:06,380
So, although it's a really subtle
change, one and a half per cent

297
00:17:06,380 --> 00:17:09,180
off his top speed, because he's
limping a little bit,

298
00:17:09,180 --> 00:17:11,460
could be the
difference between a try or no try.

299
00:17:11,460 --> 00:17:14,820
'Since he started monitoring
his players this intensely,

300
00:17:14,820 --> 00:17:17,660
'Brett has found that their
soft-tissue injuries have fallen

301
00:17:17,660 --> 00:17:19,620
'by a stunning 80%.

302
00:17:21,020 --> 00:17:23,980
'He's stopping injuries
before they arise.

303
00:17:25,660 --> 00:17:29,100
'To Brett, it's become
something of a crystal ball,

304
00:17:29,100 --> 00:17:32,140
'allowing him to see
into the players' futures.'

305
00:17:32,140 --> 00:17:35,620
If they've had a bad night's sleep,
their heart rate will show it.

306
00:17:35,620 --> 00:17:38,260
If they're getting ill and they
don't know they're getting ill yet,

307
00:17:38,260 --> 00:17:40,660
usually their heart rate will
show it for us as well.

308
00:17:40,660 --> 00:17:41,900
So from that point of view,

309
00:17:41,900 --> 00:17:44,580
sometimes we know things about them
that they don't know yet.

310
00:17:44,580 --> 00:17:46,780
So you can tell that someone's ill

311
00:17:46,780 --> 00:17:50,660
before they themselves are conscious
of the fact that they're ill?

312
00:17:50,660 --> 00:17:53,700
It hasn't failed us yet,
where we've seen data

313
00:17:53,700 --> 00:17:56,540
and we haven't reacted to it,
and literally the player has

314
00:17:56,540 --> 00:17:59,180
woken up the next day and said,
"I'm crook, I can't train."

315
00:17:59,180 --> 00:18:01,540
And we've been a bit upset
that we haven't acted on it.

316
00:18:01,540 --> 00:18:03,740
But we generally pick up illness

317
00:18:03,740 --> 00:18:06,260
24 hours before they might
start to feel ill.

318
00:18:06,260 --> 00:18:09,740
You must have found that
remarkable when you first realised.

319
00:18:09,740 --> 00:18:13,620
Yeah. For a while we literally were
looking at it, going, "That can't be
right. That can't be right."

320
00:18:13,620 --> 00:18:16,220
And we looked at it for a long time,
and then started acting on it.

321
00:18:16,220 --> 00:18:18,980
And then, the results started
proving it, you know.

322
00:18:18,980 --> 00:18:22,180
Your body's not going to lie.
You might, but your body's not.

323
00:18:23,980 --> 00:18:27,180
'Imagine if we could all see
what lay ahead.

324
00:18:27,180 --> 00:18:31,020
'Imagine if we all knew what was
coming before it arrived.'

325
00:18:32,780 --> 00:18:35,540
It's remarkable, to see
illness and injury

326
00:18:35,540 --> 00:18:38,580
before the players themselves were
conscience of it.

327
00:18:38,580 --> 00:18:41,620
Because that in medicine is
essentially what we strive for.

328
00:18:41,620 --> 00:18:44,860
To be able to see the storm
before it's arrived,

329
00:18:44,860 --> 00:18:47,660
in the hope that we might navigate
safely through it.

330
00:18:47,660 --> 00:18:50,180
Or perhaps even avoid it altogether.

331
00:18:52,460 --> 00:18:55,220
Here we go, then. See if this works.

332
00:18:55,220 --> 00:18:57,020
Our volunteers are a few days into

333
00:18:57,020 --> 00:18:59,740
seeing what self-monitoring
might do for them.

334
00:18:59,740 --> 00:19:02,380
We'd better give this gadget a go,
then.

335
00:19:02,380 --> 00:19:04,220
When it comes to counting steps,

336
00:19:04,220 --> 00:19:08,180
the recommended daily goal in order
to keep fit and healthy is 10,000.

337
00:19:10,620 --> 00:19:12,700
All the way up, all the way down!

338
00:19:12,700 --> 00:19:16,180
But as the numbers start coming in
there's a bit of a surprise.

339
00:19:19,740 --> 00:19:23,260
I've been looking, just to see how
many steps I'm doing,

340
00:19:23,260 --> 00:19:28,540
and I'm really shocked, cos I really
don't even break 5,000 sometimes,

341
00:19:28,540 --> 00:19:31,300
and I'm supposed to be
doing at least 10,000.

342
00:19:31,300 --> 00:19:33,020
It's really hard.

343
00:19:33,020 --> 00:19:36,820
So today I've been to boot camp
and I've really got to up my game.

344
00:19:44,620 --> 00:19:47,660
The step logging's
come as a bit of a surprise really.

345
00:19:47,660 --> 00:19:51,420
I thought I was quite active
and thought I moved round a lot,

346
00:19:51,420 --> 00:19:56,180
but it's quite a bit lower than
I expected it to be,

347
00:19:56,180 --> 00:20:00,020
and I'm going to have to
rely on dancing to boost that count.

348
00:20:04,740 --> 00:20:10,540
It's been difficult to find enough
time to fit in the extra exercise.

349
00:20:10,540 --> 00:20:12,500
Jess, this way.

350
00:20:12,500 --> 00:20:14,260
'Mainly through walking,

351
00:20:14,260 --> 00:20:16,860
'but anyway we'll see
how we get on.'

352
00:20:24,420 --> 00:20:27,780
And, despite the fact that
I've come to sunny California,

353
00:20:27,780 --> 00:20:29,660
I'm not finding it any easier.

354
00:20:34,540 --> 00:20:38,260
This is harder than I remember it
being. I haven't done it in a while.

355
00:20:39,860 --> 00:20:42,500
I've never really felt the need to
pull on a pair of trainers

356
00:20:42,500 --> 00:20:44,500
and jog up and down a beach.

357
00:20:44,500 --> 00:20:47,100
But it's different
when you're confronted with

358
00:20:47,100 --> 00:20:50,540
cold, hard numbers telling you
exactly how lazy you're being.

359
00:20:52,380 --> 00:20:54,380
So I've had this now
for about a week,

360
00:20:54,380 --> 00:20:56,700
and I didn't really think it was
going to change the way

361
00:20:56,700 --> 00:21:00,940
I looked at what I did
and didn't do, but it really has.

362
00:21:00,940 --> 00:21:05,620
It does make you more competitive,
even if that's only with yourself.

363
00:21:05,620 --> 00:21:08,060
I know that I've
done 3,000 steps today,

364
00:21:08,060 --> 00:21:11,100
I know that this beach is worth
another 500, and I know that

365
00:21:11,100 --> 00:21:14,820
the difference between exercise and
no exercise is a pile of numbers

366
00:21:14,820 --> 00:21:17,180
that will appear on my computer
tonight

367
00:21:17,180 --> 00:21:19,260
and tell me how hard I've worked.

368
00:21:19,260 --> 00:21:21,620
So I guess it's probably time
I got a bit more

369
00:21:21,620 --> 00:21:23,060
serious about all of this.

370
00:21:25,740 --> 00:21:30,780
Because the fact is, at the moment,
I'm not working nearly hard enough.

371
00:21:36,700 --> 00:21:38,900
'I'm not here just to
run in the sunshine.

372
00:21:40,100 --> 00:21:42,580
'I've got an appointment to see
the doctor.'

373
00:21:42,580 --> 00:21:45,140
Hello. Good morning.
I'm here to see Dr Topol.

374
00:21:45,140 --> 00:21:50,220
Go ahead and have a seat,
he'll be with you shortly. Thank you
very much. You're welcome.

375
00:21:50,220 --> 00:21:54,980
'Californians are famously obsessed
with looking and feeling great.

376
00:21:54,980 --> 00:22:00,580
'So it's a natural home for
some of the pioneers of the
self-monitoring movement.'

377
00:22:00,580 --> 00:22:02,700
I've seen a lot of waiting rooms,

378
00:22:02,700 --> 00:22:06,780
and this one is pretty typical,
pretty average, but the doctor

379
00:22:06,780 --> 00:22:11,020
I'm about to see, his approach to
medicine is anything but.

380
00:22:11,020 --> 00:22:15,220
Kevin Fong, Dr Topol will
see you now. Thank you.

381
00:22:15,220 --> 00:22:18,220
'Normally, you expect
a visit to the doctor to end with

382
00:22:18,220 --> 00:22:19,740
'a prescription for pills.

383
00:22:21,020 --> 00:22:24,260
'But the doctor I'm going to see
is much more interested

384
00:22:24,260 --> 00:22:27,860
'in fixing his patients by
getting them to monitor themselves.

385
00:22:29,300 --> 00:22:32,180
'Dr Topol is a cardiologist.'

386
00:22:32,180 --> 00:22:35,540
So let me go ahead and start off,
we'll do a cardiogram, OK? OK.

387
00:22:35,540 --> 00:22:38,060
I've got my phone here.

388
00:22:38,060 --> 00:22:41,180
'I've never seen any doctor check
for the signs of a heart attack

389
00:22:41,180 --> 00:22:43,420
'with little more than their phone.'

390
00:22:43,420 --> 00:22:48,220
Put your fingers on that, and then
just make a circuit with your heart.

391
00:22:48,220 --> 00:22:52,660
So we'll look at this together, OK,
and that's your cardiogram.

392
00:22:52,660 --> 00:22:56,340
I find it incredible that you can do
that degree of monitoring.

393
00:22:56,340 --> 00:22:58,980
Normally when I'm doing that
in a hospital I wheel this sort of

394
00:22:58,980 --> 00:23:03,780
R2D2-looking thing into the
side of the bed and it takes about

395
00:23:03,780 --> 00:23:06,300
10 minutes to hook up to someone.

396
00:23:06,300 --> 00:23:09,740
That feels very Star Trek to me.
I mean, I...

397
00:23:09,740 --> 00:23:12,980
You're easily impressed,
this is nothing.

398
00:23:12,980 --> 00:23:15,620
'Whatever's wrong with you,
Dr Topol will try and find

399
00:23:15,620 --> 00:23:19,900
'a gadget to help, so that you can
look after yourself at home.

400
00:23:19,900 --> 00:23:22,100
'He even uses some of them himself.'

401
00:23:22,100 --> 00:23:24,180
Here's a sensor.

402
00:23:24,180 --> 00:23:27,820
'He's wearing a sensor like this,
with a hair-thin micro-needle that

403
00:23:27,820 --> 00:23:31,860
'implants under the skin, giving
constant blood-glucose readings.'

404
00:23:33,700 --> 00:23:37,020
I have this on and I can
monitor my glucose every minute.

405
00:23:37,020 --> 00:23:42,980
So right now my glucose is 91, OK,
and I can see what it's been doing

406
00:23:42,980 --> 00:23:47,740
in the last several hours,
and every minute it will update.

407
00:23:47,740 --> 00:23:52,900
For the huge number of people who
suffer with diabetes, this is...

408
00:23:52,900 --> 00:23:56,660
revelatory, because until now
they've had to prick their fingers.

409
00:23:56,660 --> 00:23:58,860
Oh, no,
the finger stick could be history.

410
00:23:58,860 --> 00:24:00,300
When you have this on...

411
00:24:00,300 --> 00:24:03,780
The average person looks
at their phone 150 times a day.

412
00:24:03,780 --> 00:24:07,020
So now you got your phone,
and you're looking at it, you say,

413
00:24:07,020 --> 00:24:09,900
"Am I going to eat that cookie, am
I going to eat that piece of cake?

414
00:24:09,900 --> 00:24:13,940
"Cos if I eat that my glucose is
going to shoot up to 160, 180."

415
00:24:13,940 --> 00:24:19,300
And you start to realise exactly
how your body is responding to food,

416
00:24:19,300 --> 00:24:21,540
to portions, to exercise.

417
00:24:21,540 --> 00:24:23,860
It really changes your lifestyle,
it did me at least.

418
00:24:23,860 --> 00:24:27,140
So you're prescribing...apps?

419
00:24:27,140 --> 00:24:31,380
You name the condition,
er, heart rhythm problem,

420
00:24:31,380 --> 00:24:34,420
we get the condition, the apps to
match up with your phone,

421
00:24:34,420 --> 00:24:37,740
and that's how you monitor yourself.

422
00:24:37,740 --> 00:24:39,580
Medicine is truly unplugged now,

423
00:24:39,580 --> 00:24:43,180
and it's going to change everything
we do in healthcare.

424
00:24:43,180 --> 00:24:47,100
Because now all the information
is going directly to the patient,

425
00:24:47,100 --> 00:24:49,260
not to the doctor.

426
00:24:49,260 --> 00:24:52,060
And it's more information than
we ever had before.

427
00:24:56,980 --> 00:24:59,260
'After visiting
the doctor in the future,

428
00:24:59,260 --> 00:25:02,060
'rather than leaving with pills,
we'll leave with something

429
00:25:02,060 --> 00:25:06,740
'far more important - information
that's impossible to hide from.'

430
00:25:10,860 --> 00:25:15,060
The whole opportunity to know
everything about the medical essence

431
00:25:15,060 --> 00:25:17,500
of each person is
pretty remarkable.

432
00:25:17,500 --> 00:25:20,780
To me at least, a student
of medicine for three decades,

433
00:25:20,780 --> 00:25:25,180
this is the biggest shake-up
in the history of medicine by far.

434
00:25:25,180 --> 00:25:28,460
'With all this information,
Eric hopes we'll be able to spot

435
00:25:28,460 --> 00:25:31,740
'even the most serious problems
before it's too late.'

436
00:25:32,940 --> 00:25:36,300
To be able to prevent a heart attack
with this type of, er,

437
00:25:36,300 --> 00:25:38,820
information, that to me
is the most exciting thing.

438
00:25:38,820 --> 00:25:42,580
And I do believe that they will be,
if not fully preventable,

439
00:25:42,580 --> 00:25:44,140
awfully darn close.

440
00:25:44,140 --> 00:25:46,740
We could stamp out
something like asthma attacks.

441
00:25:46,740 --> 00:25:49,700
You can pick up,
er, pollen count, air quality

442
00:25:49,700 --> 00:25:53,260
and how the chest is moving
long before the person feels

443
00:25:53,260 --> 00:25:55,700
a wheeze or is having
difficulty breathing.

444
00:25:55,700 --> 00:25:59,100
What do you think is going to
turn up in the next ten years or so

445
00:25:59,100 --> 00:26:00,380
that people will think,

446
00:26:00,380 --> 00:26:03,420
"I never would've imagined that
medicine would look like this"?

447
00:26:03,420 --> 00:26:08,100
For the person who really has a
significant illness or risk of one,

448
00:26:08,100 --> 00:26:11,860
putting in a tiniest implant,
smaller than a grain of sand, that

449
00:26:11,860 --> 00:26:17,020
essentially carries no risk, will be
commonplace. Er, little microchips.

450
00:26:17,020 --> 00:26:19,860
We have 'em in our pets to keep
track of where they are.

451
00:26:19,860 --> 00:26:22,700
Why don't we have 'em
in our people to prevent illness?

452
00:26:33,220 --> 00:26:36,580
You know, it's startling to hear
the way that Eric talks,

453
00:26:36,580 --> 00:26:38,740
to see the things that he's doing.

454
00:26:38,740 --> 00:26:41,180
He pretty much prescribes apps

455
00:26:41,180 --> 00:26:44,900
the way my colleagues would
prescribe drugs.

456
00:26:44,900 --> 00:26:48,100
And that right there is
an example of how

457
00:26:48,100 --> 00:26:51,140
we're leaving behind what
he would call the old medicine,

458
00:26:51,140 --> 00:26:57,260
how we're finally dragging the field
of medicine into the digital age.

459
00:26:57,260 --> 00:27:00,260
And if it works
the way that he says it will,

460
00:27:00,260 --> 00:27:03,140
then it has the potential to
change everything,

461
00:27:03,140 --> 00:27:06,540
it has the potential to be truly,
truly transformative.

462
00:27:21,820 --> 00:27:25,060
These days, we can monitor
one of the most fundamental

463
00:27:25,060 --> 00:27:30,740
but usually unseen aspects of our
lives - something that affects

464
00:27:30,740 --> 00:27:35,780
our physical and mental wellbeing,
and even how long we might live.

465
00:27:37,060 --> 00:27:38,860
Our pattern of sleep.

466
00:27:42,500 --> 00:27:44,740
First night in the United States

467
00:27:44,740 --> 00:27:48,220
and I'm going to give
Blaine's sleep app a go.

468
00:27:48,220 --> 00:27:52,260
Apparently all I have to do is press
that button,

469
00:27:52,260 --> 00:27:54,220
stick it on the end of my bed

470
00:27:54,220 --> 00:27:58,340
and it's going to tell me
how I slept, so let's give it a go.

471
00:28:03,020 --> 00:28:04,980
Every twist
or turn is monitored

472
00:28:04,980 --> 00:28:07,740
by a finely calibrated
sensor in the phone

473
00:28:07,740 --> 00:28:11,260
which measures tiny ripples
in the mattress as I move.

474
00:28:11,260 --> 00:28:14,220
It should allow me to see if
anything affects my sleep.

475
00:28:17,620 --> 00:28:19,100
Across the Atlantic,

476
00:28:19,100 --> 00:28:22,140
Celia is carrying out her own sleep
experiment.

477
00:28:23,740 --> 00:28:28,860
Tonight I have had too
much to drink, um, more than

478
00:28:28,860 --> 00:28:30,860
I've had to drink for quite a
while...

479
00:28:32,900 --> 00:28:37,180
..and, yes,
I am feeling...worse for wear.

480
00:28:37,180 --> 00:28:41,220
So I'm going to record my sleep
tonight to see what happens.

481
00:28:42,780 --> 00:28:46,740
Every night, each of us will produce
a graph detailing our sleep.

482
00:28:49,460 --> 00:28:52,100
RADIO: John Tamm in the morning
on San Diego's number one

483
00:28:52,100 --> 00:28:53,620
for new country, KSON.

484
00:28:53,620 --> 00:28:55,820
It's another sunny day
here in San Diego.

485
00:28:55,820 --> 00:28:57,940
HE TURNS RADIO OFF

486
00:28:57,940 --> 00:29:01,540
Well, let's see what the phone's
going to tell me about last night.

487
00:29:02,620 --> 00:29:05,620
So there's the graph of my sleep,
light sleep right up

488
00:29:05,620 --> 00:29:09,260
there at the top,
it says deep sleep at the bottom.

489
00:29:09,260 --> 00:29:15,380
These mountainous looking peaks here
are where I was wriggling around.

490
00:29:15,380 --> 00:29:19,020
And overall it says that
I slept for 8 hours,

491
00:29:19,020 --> 00:29:21,700
and about 64% of that was
deep sleep.

492
00:29:21,700 --> 00:29:24,300
Who ever thought that phones were
going to tell us

493
00:29:24,300 --> 00:29:26,100
about how well we were sleeping?

494
00:29:29,900 --> 00:29:33,860
After three weeks of monitoring our
sleep, we should all be able to find

495
00:29:33,860 --> 00:29:38,660
out what affects it - and change our
lifestyles to help us get a better
night's sleep.

496
00:29:44,380 --> 00:29:49,140
But self-monitoring might do
much more than just change
our habits and behaviour.

497
00:29:50,500 --> 00:29:53,540
We've all worried at some
point about what nasty surprises

498
00:29:53,540 --> 00:29:56,900
might be lurking inside our bodies,
what might be going wrong,

499
00:29:56,900 --> 00:29:58,300
without us even knowing.

500
00:30:00,260 --> 00:30:02,940
By monitoring ourselves,
we can find out,

501
00:30:02,940 --> 00:30:05,100
and potentially do
something about it.

502
00:30:11,460 --> 00:30:15,780
This is the house of probably
the most monitored man in the world.

503
00:30:15,780 --> 00:30:19,980
He monitors himself - he monitors
everything about himself.

504
00:30:21,340 --> 00:30:23,140
And I really do mean everything.

505
00:30:24,180 --> 00:30:26,460
But by monitoring himself so much,

506
00:30:26,460 --> 00:30:29,060
he discovered a
potentially fatal condition.

507
00:30:29,060 --> 00:30:32,380
DOORBELL RINGS

508
00:30:35,620 --> 00:30:38,540
Larry, I'm Kevin Fong,
nice to meet you.
Good to meet you. Come on in.

509
00:30:38,540 --> 00:30:43,940
Larry Smarr is one of the most
influential computer
scientists in the United States.

510
00:30:43,940 --> 00:30:47,140
He was instrumental in developing
networked computers -

511
00:30:47,140 --> 00:30:49,740
the predecessors of the internet.

512
00:30:49,740 --> 00:30:53,660
Today, he's putting all his talent
into monitoring himself.

513
00:30:53,660 --> 00:30:57,380
Larry just give me a shopping list
of what you monitor about yourself?

514
00:30:57,380 --> 00:31:00,100
Well, I monitor my weight.

515
00:31:00,100 --> 00:31:03,620
I monitor my steps
and caloric burn with my Fitbit.

516
00:31:03,620 --> 00:31:05,860
I monitor my sleep
every night.

517
00:31:05,860 --> 00:31:09,300
Urine, saliva, blood,
I monitor stool, actually...

518
00:31:09,300 --> 00:31:13,100
You even go so far as to
monitor your own stools?

519
00:31:13,100 --> 00:31:19,260
Yes. I mean that's by far the most
important part of what I've done.

520
00:31:19,260 --> 00:31:21,780
There is such a thing as too much
information, surely?

521
00:31:21,780 --> 00:31:25,460
No. There is
never too much information.

522
00:31:25,460 --> 00:31:26,860
It is a challenge to...

523
00:31:26,860 --> 00:31:29,220
to turn that information
into understanding,

524
00:31:29,220 --> 00:31:30,980
and that's what science is about.

525
00:31:30,980 --> 00:31:32,580
Am I missing out? You are.

526
00:31:32,580 --> 00:31:37,820
We produce stool every day,
everybody on Earth does,

527
00:31:37,820 --> 00:31:41,020
and it has this incredible
information about the state

528
00:31:41,020 --> 00:31:44,260
of your health
and we just flush it away.

529
00:31:44,260 --> 00:31:48,380
It's relatively challenging
things to do, to monitor,

530
00:31:48,380 --> 00:31:53,340
you know, that element of your life
- I mean how do you do that?

531
00:31:53,340 --> 00:31:56,340
Let me just show you.

532
00:31:56,340 --> 00:31:58,860
The point is you have to freeze it.

533
00:31:58,860 --> 00:32:03,300
And I do it every two weeks
so I'm going a very fine timescale.

534
00:32:04,580 --> 00:32:07,980
And so it's just sitting
here in the freezer.

535
00:32:09,420 --> 00:32:11,540
So each of these is labelled.

536
00:32:11,540 --> 00:32:15,340
That one's February 23rd,

537
00:32:15,340 --> 00:32:19,660
this one is, this one here
is January 26th.

538
00:32:19,660 --> 00:32:22,300
This is just in the freezer
in your kitchen,

539
00:32:22,300 --> 00:32:23,860
it's not even a separate freezer?

540
00:32:23,860 --> 00:32:26,700
Well, it's getting to the point
now that I've got enough of them

541
00:32:26,700 --> 00:32:28,940
that I'll take them to the
medical school.

542
00:32:28,940 --> 00:32:32,580
You just Fedex them,
and it's overnight delivery,

543
00:32:32,580 --> 00:32:35,660
and then 2 weeks later
I get back all this data.

544
00:32:35,660 --> 00:32:37,820
I sort of had it in my mind
that you'd have

545
00:32:37,820 --> 00:32:40,980
some special freezer in your garage
or something.

546
00:32:40,980 --> 00:32:45,980
Well, my wife probably thinks I
should but she's very understanding.

547
00:32:49,660 --> 00:32:53,020
At his laboratory, Larry has put
all his information together.

548
00:32:53,020 --> 00:32:57,580
So I was wondering how on earth you
were represent

549
00:32:57,580 --> 00:33:00,060
all of the data that you
collect about yourself.

550
00:33:00,060 --> 00:33:04,220
'Over the years, he's gathered
billions of different measurements
about his body.'

551
00:33:07,660 --> 00:33:11,620
From his enzymes
to his proteins, his minerals

552
00:33:11,620 --> 00:33:16,300
to his microbes,
nothing goes undetected.

553
00:33:16,300 --> 00:33:20,580
And this display shows just
a tiny fraction of them.

554
00:33:20,580 --> 00:33:26,140
These are 150 different variables
over either 5 or 10 years. On you?

555
00:33:26,140 --> 00:33:31,500
Just on me. Here's my cholesterol
variables, my magnesium.

556
00:33:31,500 --> 00:33:35,180
Phosphorous, sodium, thallium,
stuff I've never heard of.

557
00:33:35,180 --> 00:33:38,620
You're measuring stuff that I've I
don't even know how to pronounce.

558
00:33:38,620 --> 00:33:41,740
Yup, all of the things that
your doctor tells you to measure

559
00:33:41,740 --> 00:33:43,580
and a lot of others.

560
00:33:43,580 --> 00:33:47,740
'With this information, Larry has a
warning system in place,'

561
00:33:47,740 --> 00:33:50,780
'in case anything goes
wrong inside his body.'

562
00:33:50,780 --> 00:33:54,460
The colour coding is that if they're
in the green they're healthy,

563
00:33:54,460 --> 00:33:56,380
but if they're in the orange,

564
00:33:56,380 --> 00:34:01,380
that means you're 1-10 times
above the upper limit for healthy.

565
00:34:01,380 --> 00:34:05,060
I look at this and I say,
"Look at all that green I
must be pretty healthy."

566
00:34:08,300 --> 00:34:10,700
But a few years ago, he noticed
something was wrong.

567
00:34:13,020 --> 00:34:16,660
I said, "What's this thing up
here that is red"

568
00:34:16,660 --> 00:34:21,260
"that is spiking up to 30 times the
upper limit? And this one down here

569
00:34:21,260 --> 00:34:26,340
that's purple,
that's 125 times the healthy limit."

570
00:34:26,340 --> 00:34:29,860
Some of the measures of information
in Larry's bloodstream

571
00:34:29,860 --> 00:34:33,260
had shot to
worryingly high levels.

572
00:34:34,980 --> 00:34:37,620
Lactoferrin is supposed to
be less than 7,

573
00:34:37,620 --> 00:34:42,780
and this is 899,
125 times the upper limit.

574
00:34:44,820 --> 00:34:47,620
So far off scale that you don't have
to be a doctor to know that

575
00:34:47,620 --> 00:34:49,060
something's going wrong.

576
00:34:49,060 --> 00:34:50,060
Terribly wrong.

577
00:34:50,060 --> 00:34:53,380
So you look up Google

578
00:34:53,380 --> 00:34:57,180
and within an hour you can find 5
or 6 peer reviewed papers that say

579
00:34:57,180 --> 00:35:01,700
if you have a value of this
variable at these numbers,

580
00:35:01,700 --> 00:35:05,980
say 750 to 1,000, you have a chronic
incurable disease.

581
00:35:07,780 --> 00:35:12,860
He'd discovered that he had
Crohn's disease - a serious
disorder of the intestine.

582
00:35:14,220 --> 00:35:16,980
You must've been
terrified by this surely?

583
00:35:16,980 --> 00:35:18,700
I'm a scientist,

584
00:35:18,700 --> 00:35:23,020
so the way you fight that feeling
is get more knowledge.

585
00:35:23,020 --> 00:35:25,980
With the knowledge he'd gathered,
Larry was able to

586
00:35:25,980 --> 00:35:29,660
diagnose his disease at the earliest
possible opportunity.

587
00:35:31,940 --> 00:35:33,380
He believes that soon,

588
00:35:33,380 --> 00:35:36,180
we'll all be able to monitor
ourselves like he does.

589
00:35:38,980 --> 00:35:42,580
In a world in which you can see what
you're doing to yourself

590
00:35:42,580 --> 00:35:46,020
as you go along, the hope is that
people will take more personal

591
00:35:46,020 --> 00:35:50,020
responsibility for themselves,
in keeping themselves healthy.

592
00:35:50,020 --> 00:35:53,700
So it's like we're
almost at Day Zero of a whole new

593
00:35:53,700 --> 00:35:54,900
world of medicine.

594
00:35:54,900 --> 00:35:56,740
And what will come out
the other end,

595
00:35:56,740 --> 00:36:00,500
is a far healthier society that's
focused on wellness,

596
00:36:00,500 --> 00:36:04,100
rather than trying to fix sickness
when it's way too late.

597
00:36:13,340 --> 00:36:16,460
Larry's providing a new
self-awareness that would

598
00:36:16,460 --> 00:36:20,620
lead to a new kind of preventative
medicine, one that doesn't depend

599
00:36:20,620 --> 00:36:25,740
on vaccination, or programmes of
public health, but instead on data.

600
00:36:28,060 --> 00:36:31,020
And in that, I think
he really might be onto something.

601
00:36:38,380 --> 00:36:40,660
We're one week into Blaine's
experiment.

602
00:36:43,460 --> 00:36:47,100
When we started, I think we were all
a bit surprised at how hard

603
00:36:47,100 --> 00:36:51,340
it was to reach the recommended
daily level of 10,000 steps.

604
00:36:52,380 --> 00:36:54,820
So how's everyone doing now?

605
00:36:54,820 --> 00:36:57,940
Who's that there?
That red bar is Celia.

606
00:36:59,140 --> 00:37:00,740
Upping her game.

607
00:37:00,740 --> 00:37:02,940
Getting over 15,000 steps
on a couple of days

608
00:37:02,940 --> 00:37:04,380
which is pretty impressive.

609
00:37:04,380 --> 00:37:07,660
It does kind of give it
all that competitive edge.

610
00:37:09,460 --> 00:37:12,500
'Our little experiment seems to have
got rather serious.'

611
00:37:12,500 --> 00:37:15,980
PHONE RINGS
Well, it's ringing.

612
00:37:15,980 --> 00:37:18,180
Hello!
ALL: Hello!

613
00:37:18,180 --> 00:37:20,420
How's it all going?

614
00:37:20,420 --> 00:37:23,660
Well, we're a bit concerned
about how well you did.

615
00:37:23,660 --> 00:37:27,020
Last Monday,
you seemed to put on a good spurt.

616
00:37:27,020 --> 00:37:29,980
I did do a bit of running that day,
I have to say.

617
00:37:29,980 --> 00:37:33,420
But I see, Celia, you did
a couple of days over 15,000 steps.

618
00:37:33,420 --> 00:37:37,700
I have, yes,
and I'm definitely making sure that

619
00:37:37,700 --> 00:37:40,500
I walk places that
I wouldn't normally do

620
00:37:40,500 --> 00:37:43,100
and it's been going really well.

621
00:37:43,100 --> 00:37:46,220
Celia is winning.
She's beating all of us.

622
00:37:46,220 --> 00:37:49,060
Yeah, what are you going to do
about that, Cathy?

623
00:37:49,060 --> 00:37:50,700
I've been going to boot camp,

624
00:37:50,700 --> 00:37:55,140
but my step count is a bit
disappointing, I'm afraid.

625
00:37:55,140 --> 00:37:57,660
So I'm having to do a run
after boot camp,

626
00:37:57,660 --> 00:37:59,180
but, having said that,

627
00:37:59,180 --> 00:38:02,420
my steps are still nowhere near
as much as yours and Celia,

628
00:38:02,420 --> 00:38:04,100
I'm very upset.

629
00:38:04,100 --> 00:38:07,340
How's it been going with you, Pam?
I've been doing a lot more walking,

630
00:38:07,340 --> 00:38:08,980
and, er...

631
00:38:08,980 --> 00:38:13,020
going the long way round
to make the tea and the coffee.

632
00:38:13,020 --> 00:38:15,460
I'm a little bit concerned,
because I didn't think

633
00:38:15,460 --> 00:38:18,460
we'd be taking this
quite as seriously as we are.

634
00:38:18,460 --> 00:38:22,140
'Maybe this monitoring
really is changing our behaviour.

635
00:38:22,140 --> 00:38:23,980
'We'll find out in a couple of weeks

636
00:38:23,980 --> 00:38:26,020
'just how much difference
it can make.'

637
00:38:26,020 --> 00:38:28,300
See you later, lovely to see you.
ALL: See you! Bye!

638
00:38:33,740 --> 00:38:36,140
I'm out running...again.

639
00:38:38,060 --> 00:38:40,460
It's hard not to
when every single day

640
00:38:40,460 --> 00:38:43,300
you know exactly how many steps
you're clocking up.

641
00:38:44,820 --> 00:38:48,140
But, really, what I'm doing here
is one of the more obvious ways

642
00:38:48,140 --> 00:38:49,780
of monitoring your health.

643
00:38:54,420 --> 00:38:57,100
When we think about the way
that we monitor health,

644
00:38:57,100 --> 00:39:00,180
we talk about heart rates
and blood pressures, or the amount

645
00:39:00,180 --> 00:39:03,580
of exercise we're doing,
or the calories that we've burnt.

646
00:39:04,820 --> 00:39:07,940
But it turns out you can gain
a surprisingly profound

647
00:39:07,940 --> 00:39:12,140
insight into the state of
your health by tracking apparently

648
00:39:12,140 --> 00:39:14,740
trivial bits of information
about your life -

649
00:39:14,740 --> 00:39:18,260
stuff that until now,
we've completely ignored.

650
00:39:18,260 --> 00:39:21,780
So I'm here to find out
how that's done.

651
00:39:23,900 --> 00:39:28,820
'I've come to the Massachusetts
Institute of Technology.

652
00:39:28,820 --> 00:39:32,660
'I'm here to see how experts can
monitor our everyday behaviour and

653
00:39:32,660 --> 00:39:36,940
'peer into corners of our lives that
I never would've thought possible.'

654
00:39:36,940 --> 00:39:39,140
So, please have a seat here.
Thank you.

655
00:39:39,140 --> 00:39:42,620
'Professor Sandy Pentland
believes he can tell not just

656
00:39:42,620 --> 00:39:46,180
'what's going on in our bodies,
but in our minds too.'

657
00:39:47,460 --> 00:39:51,940
'And he can do it with something
that most of us already own -

658
00:39:51,940 --> 00:39:54,500
'a smartphone.'

659
00:39:54,500 --> 00:39:57,860
Phones know a lot about your social
life, who you call, who you

660
00:39:57,860 --> 00:40:02,900
communicate with, a lot about your
daily activities, where you go.

661
00:40:02,900 --> 00:40:05,500
And so if you put the two together,
you can do things like assess

662
00:40:05,500 --> 00:40:08,700
mental health, and you can actually
get a picture of how you're

663
00:40:08,700 --> 00:40:11,260
doing constantly, 24/7.

664
00:40:13,300 --> 00:40:17,940
Sandy was asked to develop an app
to help spot signs of depression

665
00:40:17,940 --> 00:40:21,580
and post-traumatic stress
in soldiers returning from war.

666
00:40:25,340 --> 00:40:28,540
I am curious because I've had
your app on my phone for a few

667
00:40:28,540 --> 00:40:32,020
days now and I'm not entirely
sure what it's doing,

668
00:40:32,020 --> 00:40:34,300
so I'm hoping you can explain.

669
00:40:34,300 --> 00:40:38,580
OK, well, it kept track of things
like your socialisation,

670
00:40:38,580 --> 00:40:41,100
your focus and your activity levels

671
00:40:41,100 --> 00:40:44,380
and these are key things
for assessing mental health.

672
00:40:44,380 --> 00:40:46,540
Tell me
what you've found out about me.

673
00:40:46,540 --> 00:40:48,660
Well, let's look at it here

674
00:40:48,660 --> 00:40:53,300
and see what you've been doing
and then what it's been doing.

675
00:40:53,300 --> 00:40:57,220
So, first of all, we can
see your activity level - are you

676
00:40:57,220 --> 00:41:00,180
curled in a ball some place and you
never get out of your bed, or

677
00:41:00,180 --> 00:41:03,860
are you out and around, or are you
sort of manic and you're everywhere?

678
00:41:03,860 --> 00:41:07,340
So you see a five over
on the left-hand side,

679
00:41:07,340 --> 00:41:10,380
that's how active you've been,
and on the right is

680
00:41:10,380 --> 00:41:14,860
the average, so you're just exactly
average when it comes to activity.

681
00:41:18,500 --> 00:41:22,900
A drop in physical activity often
goes hand in hand with depression.

682
00:41:23,940 --> 00:41:26,180
But Sandy can track much more.

683
00:41:27,380 --> 00:41:29,220
By monitoring my phone use,

684
00:41:29,220 --> 00:41:32,460
he can also tell
how I'm interacting socially.

685
00:41:34,300 --> 00:41:35,940
Do you call your friends?

686
00:41:35,940 --> 00:41:38,580
Do you call workmates,
things like that?

687
00:41:38,580 --> 00:41:41,220
Phones can also sense
when there's other people around

688
00:41:41,220 --> 00:41:44,220
because they have these little short
range radios called Bluetooth.

689
00:41:44,220 --> 00:41:48,260
And so my phone can see your phone,
and they can shake hands.

690
00:41:48,260 --> 00:41:52,020
And if we go over here, to Social,

691
00:41:52,020 --> 00:41:55,220
you'll see that you're quite a bit
more social than other people.

692
00:41:55,220 --> 00:41:58,860
So you're good to go here,
this is good.

693
00:41:58,860 --> 00:42:03,940
And then if we go down here,
this is Focus and you can see that

694
00:42:03,940 --> 00:42:08,060
you're a little bit more focused
than the average person.

695
00:42:08,060 --> 00:42:10,900
But how does it know about my
focus? What do you mean by that?

696
00:42:10,900 --> 00:42:13,500
We all know what happens
when you're not focused.

697
00:42:13,500 --> 00:42:16,780
One of the things that people do
is that they fuss with their phone,

698
00:42:16,780 --> 00:42:20,100
they look at their messages,
they read news, they...you know,

699
00:42:20,100 --> 00:42:23,500
so you can get a sense of
whether you're focused

700
00:42:23,500 --> 00:42:25,460
or whether you're distracted
all the time.

701
00:42:28,620 --> 00:42:32,020
Though it seems astonishing that
the way you use your phone

702
00:42:32,020 --> 00:42:36,260
could give an insight into your
state of mind, trials of Sandy's app

703
00:42:36,260 --> 00:42:40,100
have demonstrated its success
when compared with a doctor.

704
00:42:41,580 --> 00:42:45,380
Sandy's convinced that mobile
phones might have a huge role

705
00:42:45,380 --> 00:42:47,180
to play in keeping us healthy.

706
00:42:48,460 --> 00:42:51,540
In fact, he believes
they might even be able to prevent

707
00:42:51,540 --> 00:42:54,940
the spread of diseases
that affect millions.

708
00:42:59,020 --> 00:43:02,900
It turns out that when people get
the flu they behave differently.

709
00:43:02,900 --> 00:43:06,020
They begin to retract a little bit,
they don't feel so good,

710
00:43:06,020 --> 00:43:09,180
they call different people,
they tend to call their friends

711
00:43:09,180 --> 00:43:11,980
more than their workmates,
things like that.

712
00:43:11,980 --> 00:43:14,260
And it's actually a signature
that you can detect

713
00:43:14,260 --> 00:43:16,060
with about 80% accuracy.

714
00:43:19,500 --> 00:43:22,580
So I could see when you
look like you're getting the flu

715
00:43:22,580 --> 00:43:25,980
and I can see that somebody else
is not getting the flu...

716
00:43:27,900 --> 00:43:30,780
..and then I can see that the two
of you spent some time together...

717
00:43:32,820 --> 00:43:34,580
..and they began to get

718
00:43:34,580 --> 00:43:39,860
flu behaviour, which tells me that
you infected them at that meeting.

719
00:43:39,860 --> 00:43:43,100
And, of course, normal flu
is not that bad

720
00:43:43,100 --> 00:43:45,860
but every once in a while we get
these pandemics that kill

721
00:43:45,860 --> 00:43:47,540
literally hundreds
of millions of people

722
00:43:47,540 --> 00:43:49,460
and we're defenceless against it.

723
00:43:49,460 --> 00:43:52,460
This is a startling thing -
the idea that you might track the

724
00:43:52,460 --> 00:43:56,180
spread of a pandemic by something
other than taking blood tests from

725
00:43:56,180 --> 00:44:00,500
people or saliva samples, or them
going and seeing their physician.

726
00:44:00,500 --> 00:44:03,900
It's a rather amazing thing
that you could actually watch

727
00:44:03,900 --> 00:44:05,660
the progress of the disease...

728
00:44:08,100 --> 00:44:10,300
..because then you could actually
do something about it.

729
00:44:12,620 --> 00:44:15,060
You could say, "OK, people in this
neighbourhood

730
00:44:15,060 --> 00:44:16,740
"don't go to work today."

731
00:44:18,460 --> 00:44:21,460
Or, "Don't go to this cafeteria."

732
00:44:21,460 --> 00:44:24,020
Or whatever sort of
intervention you want.

733
00:44:25,340 --> 00:44:27,740
But you could actually begin
stopping it.

734
00:44:38,980 --> 00:44:42,500
But to bring about this
game-changing shift in health care,

735
00:44:42,500 --> 00:44:45,900
we'll need to give up
our most personal information

736
00:44:45,900 --> 00:44:50,340
to people who can mine it
and spot the patterns within.

737
00:44:50,340 --> 00:44:55,380
And, understandably, not everyone
will be comfortable with that.

738
00:44:56,860 --> 00:45:00,100
The world is now full of people
with their mobile phones

739
00:45:00,100 --> 00:45:04,260
and their mobile devices streaming
terabytes of information

740
00:45:04,260 --> 00:45:08,020
about their habits and their daily
lives. And I completely

741
00:45:08,020 --> 00:45:11,460
understand the unease that people
feel about giving

742
00:45:11,460 --> 00:45:14,660
that information up to others.

743
00:45:14,660 --> 00:45:17,980
But, in medicine,
that's all we've ever done.

744
00:45:17,980 --> 00:45:21,980
We've gone to doctors, strangers,
and we've told them

745
00:45:21,980 --> 00:45:27,100
those intimate details in the hope
that they might bring us help.

746
00:45:29,180 --> 00:45:33,620
And in a sense, that's what
Sandy Pentland and people like him

747
00:45:33,620 --> 00:45:37,780
are trying to do, just taking that
model and dragging it into

748
00:45:37,780 --> 00:45:42,620
the 21st century in the hope that
will change the face of medicine.

749
00:45:51,260 --> 00:45:54,100
Over the last couple of weeks,
I've become increasingly

750
00:45:54,100 --> 00:45:56,140
obsessed about monitoring myself.

751
00:45:57,180 --> 00:46:00,420
But I'm starting to realise that
there's much more to this

752
00:46:00,420 --> 00:46:02,540
than just doing more exercise.

753
00:46:03,860 --> 00:46:08,220
By monitoring ourselves
and pooling that information,

754
00:46:08,220 --> 00:46:09,580
we could unearth knowledge

755
00:46:09,580 --> 00:46:12,780
that would revolutionise
the way we practise medicine.

756
00:46:14,900 --> 00:46:19,260
We could share our data and begin
to look for patterns that unlock

757
00:46:19,260 --> 00:46:21,700
the secrets of human health.

758
00:46:32,500 --> 00:46:35,020
I've come to a small town
in Florida

759
00:46:35,020 --> 00:46:38,020
to meet someone
who's looking for those patterns,

760
00:46:38,020 --> 00:46:42,140
and who's moving forwards at a pace
that seems barely believable.

761
00:46:47,540 --> 00:46:50,380
So far, we've had a hint
of the shape of things to come

762
00:46:50,380 --> 00:46:52,180
for the future of medicine.

763
00:46:53,220 --> 00:46:56,980
But the girl I'm about to talk to
IS the future of medicine,

764
00:46:56,980 --> 00:47:00,540
and, incredibly, she doesn't have
a medical degree.

765
00:47:00,540 --> 00:47:02,860
In fact, she doesn't have
a degree at all

766
00:47:02,860 --> 00:47:05,820
and that's because
she's still at school.

767
00:47:10,700 --> 00:47:13,300
I mean, I think it's exciting
that as a teenager I've been

768
00:47:13,300 --> 00:47:14,740
able to find something

769
00:47:14,740 --> 00:47:18,580
I'm so passionate about that
I want to spend my weekends working.

770
00:47:18,580 --> 00:47:22,900
'What sets Brittany Wenger apart
are her computer-coding skills.'

771
00:47:22,900 --> 00:47:26,100
There is a community of us out there
who are really interested

772
00:47:26,100 --> 00:47:29,780
in science and through the different
kind of science competitions...

773
00:47:29,780 --> 00:47:32,580
'She recently won the
prestigious Google Science Fair

774
00:47:32,580 --> 00:47:34,540
'for a computer program
she's written.'

775
00:47:34,540 --> 00:47:38,100
I think I'd always had a pretty keen
interest in computers but then

776
00:47:38,100 --> 00:47:40,940
in seventh grade I was taking this
course on futuristic thinking.

777
00:47:40,940 --> 00:47:43,460
In seventh grade...
How old were you in seventh grade?

778
00:47:43,460 --> 00:47:45,620
So that would be about 11 or 12.
Right.

779
00:47:45,620 --> 00:47:48,540
And I came across a concept
that computers could actually be

780
00:47:48,540 --> 00:47:51,940
programmed to transcend human
knowledge and to detect

781
00:47:51,940 --> 00:47:55,620
really complicated patterns that
humans have no idea how to detect.

782
00:47:55,620 --> 00:47:59,060
So I was enthralled and I went home,
I started buying coding books

783
00:47:59,060 --> 00:48:01,860
and I decided to teach myself
how to code.

784
00:48:01,860 --> 00:48:05,540
'What happened next was a family
tragedy that inspired

785
00:48:05,540 --> 00:48:07,740
'Brittany to do something
remarkable.'

786
00:48:09,380 --> 00:48:12,460
I was 15, my cousin was actually
diagnosed with breast cancer

787
00:48:12,460 --> 00:48:14,860
and I saw first-hand
the kind of impact this disease

788
00:48:14,860 --> 00:48:16,500
has on a woman and her family.

789
00:48:16,500 --> 00:48:19,100
So I got really inspired to get
involved and make a difference

790
00:48:19,100 --> 00:48:20,980
and I started researching
breast cancer.

791
00:48:20,980 --> 00:48:23,820
And so that's when I really wanted
to connect my two passions

792
00:48:23,820 --> 00:48:27,500
and try to create a better
breast cancer diagnostic system.

793
00:48:27,500 --> 00:48:32,220
'And she's written this program
in her spare time.'

794
00:48:39,860 --> 00:48:43,100
'Looking at a biopsy of human tissue
to determine

795
00:48:43,100 --> 00:48:47,060
'whether it's cancerous or not
is a notoriously difficult thing
to do.'

796
00:48:48,780 --> 00:48:51,700
'Brittany's program is designed
to help doctors

797
00:48:51,700 --> 00:48:54,300
'to analyse what they're seeing.'

798
00:48:54,300 --> 00:48:57,700
So, for example, see these nucleoli,
they're the small dots.

799
00:48:57,700 --> 00:48:59,980
The small dots, right.

800
00:48:59,980 --> 00:49:03,180
They're really prominent and there
are multiple ones per cell.

801
00:49:03,180 --> 00:49:05,460
And that could mean
that the mass is cancerous.

802
00:49:05,460 --> 00:49:07,500
But that is actually benign.

803
00:49:07,500 --> 00:49:09,540
And this is just an example
of why they are

804
00:49:09,540 --> 00:49:12,940
so difficult to diagnose,
because even this benign mass is

805
00:49:12,940 --> 00:49:15,620
exhibiting some
cancerous attributes.

806
00:49:15,620 --> 00:49:18,660
I have horrible nightmares
of spending hours staring at these

807
00:49:18,660 --> 00:49:25,500
slides at medical school, trying to
decide whether it was cancer or not.

808
00:49:25,500 --> 00:49:28,620
And it just seemed nearly
impossible to me.

809
00:49:28,620 --> 00:49:31,140
I mean, this is a tough task.

810
00:49:31,140 --> 00:49:34,020
'It's an incredibly difficult task,

811
00:49:34,020 --> 00:49:36,660
'for which Brittany
has found a solution.'

812
00:49:36,660 --> 00:49:39,180
So what I did is I created
an artificial neural network

813
00:49:39,180 --> 00:49:41,460
which is this really cool type of
program that can

814
00:49:41,460 --> 00:49:44,900
model a brain's neurons and their
interconnections, so it can actually

815
00:49:44,900 --> 00:49:49,020
learn how to detect patterns that
humans have no idea how to detect.

816
00:49:49,020 --> 00:49:51,460
And in the end
it learns how to detect

817
00:49:51,460 --> 00:49:54,620
whether these masses are cancerous
or not.

818
00:49:54,620 --> 00:49:58,100
So your computer
knows how to do this?

819
00:49:58,100 --> 00:50:03,340
Yes. It actually diagnoses over
99% of cancer patients correctly,

820
00:50:03,340 --> 00:50:05,580
which is huge.

821
00:50:05,580 --> 00:50:08,540
Yes, so 99% of the time it
will pick it up?

822
00:50:08,540 --> 00:50:11,860
Yes, which... It's exciting
when you think about it.

823
00:50:11,860 --> 00:50:14,940
Er, it's more than exciting.

824
00:50:14,940 --> 00:50:18,180
'Brittany's program effectively
turns a doctor's hunch about

825
00:50:18,180 --> 00:50:23,580
'whether a biopsy is cancerous
into something far more scientific.'

826
00:50:23,580 --> 00:50:28,500
So what this does is provides
a set of nine pretty objective

827
00:50:28,500 --> 00:50:31,580
questions about what they're seeing
on the screen in front of them,

828
00:50:31,580 --> 00:50:37,500
and then feeds that quite
complicated set of information

829
00:50:37,500 --> 00:50:41,740
to your program which then instantly
decides cancer or not cancer?

830
00:50:41,740 --> 00:50:43,140
Yeah, exactly.

831
00:50:43,140 --> 00:50:47,260
It's able to detect patterns
in this scoring system that are too

832
00:50:47,260 --> 00:50:49,740
subtle for humans to detect.

833
00:50:49,740 --> 00:50:51,940
So doctors enter these
different values,

834
00:50:51,940 --> 00:50:55,100
and then they would click send,
and in under a second,

835
00:50:55,100 --> 00:50:56,820
the service is able to respond

836
00:50:56,820 --> 00:50:59,620
as to whether it thinks
it's cancerous or not,

837
00:50:59,620 --> 00:51:02,260
and so this particular mass
would be cancerous.

838
00:51:02,260 --> 00:51:07,260
Wow! That's gobsmacking.
I mean, absolutely gobsmacking!

839
00:51:12,100 --> 00:51:15,500
I feel like I've had a glimpse
of the future -

840
00:51:15,500 --> 00:51:18,340
a sense of the great prizes we might

841
00:51:18,340 --> 00:51:21,340
find in the huge volumes of data

842
00:51:21,340 --> 00:51:24,900
that monitoring our bodies
can give us.

843
00:51:33,780 --> 00:51:35,380
I've come back to the UK...

844
00:51:38,220 --> 00:51:41,580
..and to the information that could
change our lives today.

845
00:51:49,660 --> 00:51:53,220
'Three weeks ago, I began
an experiment in self-monitoring.'

846
00:51:53,220 --> 00:51:56,620
Hello! Hi, Kevin. Hi!

847
00:51:56,620 --> 00:52:01,980
'Celia, Cathy, Pam, and I wanted to
see if anyone could get healthier,

848
00:52:01,980 --> 00:52:05,740
'lose weight, or find out how
to sleep better.

849
00:52:05,740 --> 00:52:09,420
'Now it's time to see
if anything has changed.'

850
00:52:09,420 --> 00:52:11,140
And what have you found out
about us then?

851
00:52:11,140 --> 00:52:12,860
Well, quite a few interesting
things.

852
00:52:12,860 --> 00:52:15,340
I know when everyone goes to bed,
when everyone wakes up,

853
00:52:15,340 --> 00:52:18,220
where they go every day, erm...

854
00:52:18,220 --> 00:52:20,260
how much sleep they get,
how much deep sleep -

855
00:52:20,260 --> 00:52:22,300
pretty much everything.

856
00:52:22,300 --> 00:52:25,980
And, in fact, Kevin, you had the
lowest average sleep of everyone.

857
00:52:25,980 --> 00:52:30,220
I think it must be medical training
that did that.

858
00:52:30,220 --> 00:52:33,740
So, my average sleep was
what sort of hours?

859
00:52:33,740 --> 00:52:35,620
About 6.7 hours a night.

860
00:52:35,620 --> 00:52:38,740
It's well below what people
generally believe is normal.

861
00:52:38,740 --> 00:52:41,780
And, Cathy, you were the most
consistent of all because,

862
00:52:41,780 --> 00:52:44,020
as you can see, you were just under
eight hours.

863
00:52:44,020 --> 00:52:45,860
You're about 7.8 every night.

864
00:52:45,860 --> 00:52:50,300
And Pam had the highest average.
You have over eight hours a night,

865
00:52:50,300 --> 00:52:52,100
and that is fairly consistent.

866
00:52:52,100 --> 00:52:55,580
I think I'm sleeping better
than I used to.

867
00:52:55,580 --> 00:52:58,020
My sleep pattern was really,
really bad.

868
00:52:58,020 --> 00:53:03,260
And I do think I have slept better
with the extra exercise.

869
00:53:04,940 --> 00:53:07,860
The peaks on Pam's sleep graphs
tell us

870
00:53:07,860 --> 00:53:10,420
when she was awake
or sleeping lightly.

871
00:53:11,460 --> 00:53:14,660
The troughs show
when she was sleeping deeply.

872
00:53:16,300 --> 00:53:18,540
With graphs from every night,

873
00:53:18,540 --> 00:53:22,420
there's the potential to find out
how to sleep better.

874
00:53:24,700 --> 00:53:28,220
It was saying that I was having
about an hour of deep sleep

875
00:53:28,220 --> 00:53:31,380
and I found that slightly concerning
because I'm wondering

876
00:53:31,380 --> 00:53:35,220
whether I need more deep sleep
than just that short amount.

877
00:53:35,220 --> 00:53:37,860
You may only need an hour of deep
sleep to feel good.

878
00:53:37,860 --> 00:53:41,100
You've got to know what's normal for
you, and what affects your sleep.

879
00:53:41,100 --> 00:53:43,140
So did you find anything
affected your sleep?

880
00:53:43,140 --> 00:53:47,340
Well, there was two nights this week
when I had one glass of red wine.

881
00:53:47,340 --> 00:53:51,260
Now, I try not to drink during
the week, but up until that point,

882
00:53:51,260 --> 00:53:55,580
I'd been having round about
the hour of deep sleep in a night.

883
00:53:55,580 --> 00:53:59,380
On those two nights, my deep sleep
went down to 36 minutes

884
00:53:59,380 --> 00:54:01,620
on one night,
and 34 minutes on another.

885
00:54:01,620 --> 00:54:05,060
Perhaps red wine and me don't mix
for my deep sleep.

886
00:54:05,060 --> 00:54:08,340
I realised that
even if I have a decaf coffee,

887
00:54:08,340 --> 00:54:12,380
which I used to have about 9ish,
I have a bad sleep,

888
00:54:12,380 --> 00:54:15,020
so I've knocked that on the head
completely now.

889
00:54:15,020 --> 00:54:18,700
That's one of the incredible
benefits of self-monitoring -

890
00:54:18,700 --> 00:54:21,260
it allows us to learn things
about ourselves

891
00:54:21,260 --> 00:54:23,740
and change our behaviour
for the better.

892
00:54:23,740 --> 00:54:28,380
So did it make a difference
to our fitness or even our weight?

893
00:54:28,380 --> 00:54:32,300
So we've got
the daily step count total.

894
00:54:32,300 --> 00:54:34,220
Everyone started coalescing,
actually,

895
00:54:34,220 --> 00:54:36,580
around a 10,000 step average per day,

896
00:54:36,580 --> 00:54:39,980
which is what the general guideline
is to keep active,

897
00:54:39,980 --> 00:54:42,540
especially for people
in sedentary jobs like us.

898
00:54:42,540 --> 00:54:45,100
This three weeks has been quite
a revelation for me.

899
00:54:45,100 --> 00:54:49,980
Cos I went out consciously
most days to do extra steps.

900
00:54:49,980 --> 00:54:52,020
You sort of get in this
you can't stop

901
00:54:52,020 --> 00:54:54,580
until you've reached
that magic 10,000.

902
00:54:54,580 --> 00:54:56,100
In a way it's a bit crazy.

903
00:54:56,100 --> 00:54:59,380
And, Celia, did you ever get
to the point of madness
with any of this stuff?

904
00:54:59,380 --> 00:55:03,660
I had got to the point where I would
set myself a goal for the day

905
00:55:03,660 --> 00:55:08,340
and, if I hadn't met it, then
I did end up running on the spot

906
00:55:08,340 --> 00:55:13,140
as I was watching television, or
just trying to get those steps up.

907
00:55:13,140 --> 00:55:15,580
Do you think you've seen
improvements in your health

908
00:55:15,580 --> 00:55:17,700
other than just doing
a whole bunch of steps?

909
00:55:17,700 --> 00:55:20,620
We've all lost weight doing the
challenge so that's a good thing.

910
00:55:20,620 --> 00:55:22,180
I lost about four pounds.

911
00:55:22,180 --> 00:55:23,860
I lost four and a half, so...

912
00:55:23,860 --> 00:55:27,900
I lost two and a half
so the extra exercise does pay off.

913
00:55:27,900 --> 00:55:29,780
I did very little before.

914
00:55:29,780 --> 00:55:31,980
I'd sit at my desk all day
in front of a computer,

915
00:55:31,980 --> 00:55:34,300
I didn't walk the dog that often.

916
00:55:34,300 --> 00:55:38,100
Now I go home from work
and I'm out there walking the dog.

917
00:55:38,100 --> 00:55:42,580
Same as Pam. We're going out
for walks, I'm going out for walks
in the evening.

918
00:55:42,580 --> 00:55:45,380
So I am... I have changed
and I will continue.

919
00:55:47,420 --> 00:55:49,660
It's interesting that Cathy, Celia

920
00:55:49,660 --> 00:55:53,620
and Pam all in their own way managed
to change their behaviour.

921
00:55:53,620 --> 00:55:56,860
They all increased the amount
of activity they did.

922
00:55:56,860 --> 00:56:00,220
And that's more than a bit of fun,
that's important

923
00:56:00,220 --> 00:56:03,460
because, in medicine, if you could
prescribe one thing

924
00:56:03,460 --> 00:56:05,700
that would improve
everybody's health,

925
00:56:05,700 --> 00:56:07,780
then that thing would be exercise.

926
00:56:07,780 --> 00:56:11,260
Exercise improves your physiology
in ways that doctors

927
00:56:11,260 --> 00:56:13,660
and pills alone never could.

928
00:56:13,660 --> 00:56:18,020
And so that's what even those simple
devices have managed to achieve -

929
00:56:18,020 --> 00:56:22,740
they've managed to help people
change their behaviour in ways

930
00:56:22,740 --> 00:56:25,060
that were otherwise
impossible before.

931
00:56:30,300 --> 00:56:34,580
Today we all have the capacity
to monitor our health.

932
00:56:34,580 --> 00:56:38,340
The devices we carry already do it
without us even noticing.

933
00:56:40,340 --> 00:56:43,500
And in the data that we gather
lies great opportunity.

934
00:56:45,140 --> 00:56:48,940
But ultimately, it's what we choose
to do with that information

935
00:56:48,940 --> 00:56:50,780
that will make all the difference.

936
00:56:54,700 --> 00:56:57,140
We stand early
in the 21st century,

937
00:56:57,140 --> 00:57:00,860
looking for the things that will
transform medicine in the same way

938
00:57:00,860 --> 00:57:04,620
that antibiotics and vaccinations
did at the start of the 20th.

939
00:57:05,860 --> 00:57:08,660
But I've become convinced
over the last few weeks,

940
00:57:08,660 --> 00:57:10,940
through everything I've seen,

941
00:57:10,940 --> 00:57:14,180
that this digital revolution
really might achieve that.

942
00:57:15,380 --> 00:57:18,780
By giving us access to information
that we never before had,

943
00:57:18,780 --> 00:57:21,100
by helping us understand our bodies

944
00:57:21,100 --> 00:57:24,140
and the consequences of the things
we do in our lives,

945
00:57:24,140 --> 00:57:31,180
I really do think that this might be
the key to longer, healthier lives.

946
00:57:53,700 --> 00:57:57,220
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