TEDxNijmegen
Peter van Manen: Better baby care -- thanks to Formula 1
Piter van Menen (Peter van Manen): Kako Formula 1 može da pomogne... bebama?
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Tokom trke Formule 1, kola šalju stotine miliona jedinica podataka svojoj garaži radi analize i povratne informacije u stvarnom vremenu. Zašto ne bismo koristili taj detaljan i rigorozan sistem podataka negde druge, kao u... dečijoj bolnici? Piter van Menen nam govori više o tome.
Peter van Manen - Electronic systems expert
Peter van Manen is the Managing Director of McLaren Electronics, which provides data systems to major motorsports series. Full bio
Peter van Manen is the Managing Director of McLaren Electronics, which provides data systems to major motorsports series. Full bio
Double-click the English transcript below to play the video.
00:12
Motor racing is a funny old business.
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Trka automobila
je zanimljiva stara zabava.
je zanimljiva stara zabava.
00:14
We make a new car every year,
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Pravimo nove automobile
svake godine
svake godine
00:16
and then we spend the rest of the season
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i onda tokom ostatka sezone
00:19
trying to understand what it is we've built
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pokušavamo da razumemo
šta smo to napravili
šta smo to napravili
00:21
to make it better, to make it faster.
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da bi bili bolji i brži.
00:25
And then the next year, we start again.
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A naredne godine, počinjemo ispočetka.
00:28
Now, the car you see in front of you is quite complicated.
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Kola koja vidite ispred vas
su dosta komplikovana.
su dosta komplikovana.
00:32
The chassis is made up of about 11,000 components,
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Šasija je sastavljena
od oko 11.000 komponenti,
od oko 11.000 komponenti,
00:36
the engine another 6,000,
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motor od još oko 6.000,
00:38
the electronics about eight and a half thousand.
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elektronika od oko 8.500.
00:41
So there's about 25,000 things there that can go wrong.
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Znači, 25.000 stvari
može da pođe po zlu.
može da pođe po zlu.
00:46
So motor racing is very much about attention to detail.
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U trci automobila
se najviše radi o detaljima.
se najviše radi o detaljima.
00:51
The other thing about Formula 1 in particular
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Druga stvar naročito vezana
za Formulu 1
za Formulu 1
00:54
is we're always changing the car.
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je da uvek menjamo automobil.
00:56
We're always trying to make it faster.
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Uvek pokušavamo da ga napravimo bržim.
00:58
So every two weeks, we will be making
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Svake dve nedelje, napravićemo
01:01
about 5,000 new components to fit to the car.
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oko 5.000 novih komponenti
za automobil.
za automobil.
01:05
Five to 10 percent of the race car
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5 do 10% trkačkih automobila
01:08
will be different every two weeks of the year.
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biće drugačije
svake dve nedelje u godini.
svake dve nedelje u godini.
01:11
So how do we do that?
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Kako to postižemo?
01:14
Well, we start our life with the racing car.
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Počnemo život sa trkačkim kolima.
01:17
We have a lot of sensors on the car to measure things.
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Imamo mnogo senzora
za merenje na kolima.
za merenje na kolima.
01:21
On the race car in front of you here
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Na trkačkim kolima ispred vas
01:23
there are about 120 sensors when it goes into a race.
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ima oko 120 senzora
kada je u trci.
kada je u trci.
01:26
It's measuring all sorts of things around the car.
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Oni mere svakakve stvari.
01:30
That data is logged. We're logging about
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Podaci se beleže.
01:32
500 different parameters within the data systems,
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Beležimo oko 500 različitih parametara
unutar sistema,
unutar sistema,
01:36
about 13,000 health parameters and events
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oko 13.000 zdravstvenih parametara
i događaja
i događaja
01:39
to say when things are not working the way they should do,
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da nam saopšte kada stvari ne rade
kako bi trebalo.
kako bi trebalo.
01:44
and we're sending that data back to the garage
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I šaljemo te podatke nazad u garažu
01:47
using telemetry at a rate of two to four megabits per second.
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koristeći telemetriju, brzinom
od dva do četiri megabita po sekundi.
od dva do četiri megabita po sekundi.
01:52
So during a two-hour race, each car will be sending
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Tako da tokom dvosatne trke,
svaka kola će poslati
svaka kola će poslati
01:55
750 million numbers.
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750 miliona brojki.
01:57
That's twice as many numbers as words that each of us
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To je duplo više brojeva
od reči koje svaki od nas
od reči koje svaki od nas
02:00
speaks in a lifetime.
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izgovori tokom života.
02:02
It's a huge amount of data.
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To je velika količina podataka.
02:05
But it's not enough just to have data and measure it.
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Ali nije dovoljno samo
da imate podatke i da ih merite.
da imate podatke i da ih merite.
02:07
You need to be able to do something with it.
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Treba da ste sposobni
da uradite nešto sa njima.
da uradite nešto sa njima.
02:09
So we've spent a lot of time and effort
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Potrošili smo puno vremena i truda
02:12
in turning the data into stories
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pretvarajući podatke u priče
02:14
to be able to tell, what's the state of the engine,
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da bismo mogli da ispričamo
kakvo je stanje motora,
kakvo je stanje motora,
02:17
how are the tires degrading,
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kako se troše gume,
02:19
what's the situation with fuel consumption?
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kakvo je stanje sa potrošnjom goriva?
02:23
So all of this is taking data
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Sve ovo meri neke podatke
02:26
and turning it into knowledge that we can act upon.
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i pretvara u znanje po kojem
možemo da postupamo.
možemo da postupamo.
02:29
Okay, so let's have a look at a little bit of data.
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U redu, hajde da pogledamo
delić podataka.
delić podataka.
02:32
Let's pick a bit of data from
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Uzmimo delić podatka
02:34
another three-month-old patient.
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o drugom tromesečnom pacijentu.
02:37
This is a child, and what you're seeing here is real data,
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Ovo je dete i ono što vidite ovde
su pravi podaci
su pravi podaci
02:41
and on the far right-hand side,
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i na krajnjoj desnoj strani,
02:43
where everything starts getting a little bit catastrophic,
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gde sve počinje
da bude pomalo katastrofično,
da bude pomalo katastrofično,
02:46
that is the patient going into cardiac arrest.
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to pacijent doživljava
srčani zastoj.
srčani zastoj.
02:49
It was deemed to be an unpredictable event.
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Smatralo se da je to bio
nepredvidljivi događaj.
nepredvidljivi događaj.
02:53
This was a heart attack that no one could see coming.
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Bio je to srčani udar
koji niko nije mogao da predvidi.
koji niko nije mogao da predvidi.
02:56
But when we look at the information there,
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Ali ako tu pogledamo podatke,
02:59
we can see that things are starting to become
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vidimo da se stvari počinju mutiti
03:01
a little fuzzy about five minutes or so before the cardiac arrest.
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oko pet minuta pred srčani zastoj.
03:05
We can see small changes
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Vidimo male promene
03:07
in things like the heart rate moving.
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u stvarima kao što je promena pulsa.
03:10
These were all undetected by normal thresholds
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One su bile neprimećene
pri normalnim pragovima
pri normalnim pragovima
03:12
which would be applied to data.
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koji bi se mogli primeniti na podatke.
03:15
So the question is, why couldn't we see it?
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Pitanje je,
zašto to nismo mogli da primetimo?
zašto to nismo mogli da primetimo?
03:18
Was this a predictable event?
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Da li je to bio predvidljiv događaj?
03:20
Can we look more at the patterns in the data
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Da li možemo bolje
da sagledamo obrasce u podacima
da sagledamo obrasce u podacima
03:23
to be able to do things better?
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da bismo bolje radili?
03:27
So this is a child,
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Ovo je dete,
03:29
about the same age as the racing car on stage,
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otprilike iste dobi
kao trkački automobili na bini,
kao trkački automobili na bini,
03:33
three months old.
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tri meseca.
03:34
It's a patient with a heart problem.
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To dete je pacijent
sa srčanim problemom.
sa srčanim problemom.
03:37
Now, when you look at some of the data on the screen above,
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Ako pogledamo neke od podataka
na ekranu iznad,
na ekranu iznad,
03:40
things like heart rate, pulse, oxygen, respiration rates,
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stvari poput otkucaja srca, pulsa,
kiseonika, brzine disanja,
kiseonika, brzine disanja,
03:45
they're all unusual for a normal child,
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sve su neobične za normalno dete,
03:48
but they're quite normal for the child there,
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ali su sasvim normalne za ovo dete.
03:51
and so one of the challenges you have in health care is,
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Jedan od izazova zdravstva
03:55
how can I look at the patient in front of me,
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je kako mogu da pregledam pacijenta
03:58
have something which is specific for her,
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za koga je nešto specifično
04:01
and be able to detect when things start to change,
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i da uočim stvari
kada počnu da se menjaju
kada počnu da se menjaju
04:04
when things start to deteriorate?
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i da se pogoršavaju?
04:06
Because like a racing car, any patient,
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Isto kao i trkački automobil,
za svakog pacijenta
za svakog pacijenta
04:09
when things start to go bad, you have a short time
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kada se stvari pogoršaju,
imate malo vremena
imate malo vremena
04:12
to make a difference.
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da napravite razliku.
04:14
So what we did is we took a data system
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Uzeli smo sistem podataka
04:17
which we run every two weeks of the year in Formula 1
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koji koristimo svake dve nedelje
tokom godine za Formulu 1
tokom godine za Formulu 1
04:20
and we installed it on the hospital computers
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i instalirali smo ih
u bolničke kompjutere
u bolničke kompjutere
04:23
at Birmingham Children's Hospital.
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u dečijoj bolnici u Birmingemu.
04:25
We streamed data from the bedside instruments
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Pratili smo podatke
sa instrumenata pored kreveta
sa instrumenata pored kreveta
04:27
in their pediatric intensive care
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u intenzivnoj nezi pedijatrije
04:30
so that we could both look at the data in real time
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kako bismo mogli da sagledamo podatke
u stvarnom vremenu
u stvarnom vremenu
04:33
and, more importantly, to store the data
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i što je važnije, da sačuvamo podatke
04:36
so that we could start to learn from it.
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kako bismo mogli da učimo iz njih.
04:39
And then, we applied an application on top
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Tada smo primenili aplikaciju
04:44
which would allow us to tease out the patterns in the data
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koja bi nam omogućila
da izvučemo obrasce iz podataka
da izvučemo obrasce iz podataka
04:47
in real time so we could see what was happening,
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u stvarnom vremenu,
da bismo videli šta se dešava
da bismo videli šta se dešava
04:50
so we could determine when things started to change.
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i kako bismo odredili
kada su stvari počele da se menjaju.
kada su stvari počele da se menjaju.
04:54
Now, in motor racing, we're all a little bit ambitious,
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U trkama automobila
svi smo pomalo ambiciozni,
svi smo pomalo ambiciozni,
04:58
audacious, a little bit arrogant sometimes,
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drski, ponekad pomalo arogantni,
05:00
so we decided we would also look at the children
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pa smo odlučili
da posmatramo decu
da posmatramo decu
05:04
as they were being transported to intensive care.
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dok se prenose u intenzivnu negu.
05:06
Why should we wait until they arrived in the hospital
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Zašto da čekamo da stignu u bolnicu
pre nego što počnemo
pre nego što počnemo
05:09
before we started to look?
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da ih posmatramo?
05:11
And so we installed a real-time link
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Tako da smo postavili vezu
u stvarnom vremenu
u stvarnom vremenu
05:14
between the ambulance and the hospital,
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između ambulantnih kola i bolnice,
05:16
just using normal 3G telephony to send that data
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koristeći samo normalnu 3G telefoniju
da šaljemo podatke,
da šaljemo podatke,
05:20
so that the ambulance became an extra bed
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pa bi ambulantna kola postala
dodatni krevet
dodatni krevet
05:23
in intensive care.
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u intenzivnoj nezi.
05:26
And then we started looking at the data.
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Zatim smo počeli
da pregledamo podatke.
da pregledamo podatke.
05:30
So the wiggly lines at the top, all the colors,
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Krivudave linije na vrhu, sve boje,
05:32
this is the normal sort of data you would see on a monitor --
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to je normalna vrsta podataka
koju biste videli na monitoru –
koju biste videli na monitoru –
05:36
heart rate, pulse, oxygen within the blood,
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otkucaji srca, puls, kiseonik u krvi
05:39
and respiration.
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i disanje.
05:42
The lines on the bottom, the blue and the red,
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Linije da dnu, plave i crvene,
05:45
these are the interesting ones.
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te su zanimljive.
05:46
The red line is showing an automated version
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Crvena pokazuje automatizovanu verziju
05:49
of the early warning score
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ranog upozoravajućeg rezultata
05:51
that Birmingham Children's Hospital were already running.
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koju dečija bolnica
u Birmingemu već koristi.
u Birmingemu već koristi.
05:53
They'd been running that since 2008,
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Koriste to već od 2008. godine
05:56
and already have stopped cardiac arrests
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i već su zaustavili srčane zastoje
05:58
and distress within the hospital.
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i uznemirenost u bolnici.
06:01
The blue line is an indication
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Plava linija je pokazatelj
06:03
of when patterns start to change,
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kada obrasci počinju
da se menjaju,
da se menjaju,
06:06
and immediately, before we even started
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i momentalno,
pre nego što smo i počeli
pre nego što smo i počeli
06:08
putting in clinical interpretation,
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kliničku interpretaciju,
06:10
we can see that the data is speaking to us.
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možemo videti da nam podaci govore.
06:13
It's telling us that something is going wrong.
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Govore nam da nešto nije u redu.
06:16
The plot with the red and the green blobs,
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Crtež sa crvenim i zelenim mrljama,
06:20
this is plotting different components
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ovo zapliće različite
komponente podataka
komponente podataka
06:23
of the data against each other.
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jedne protiv drugih.
06:25
The green is us learning what is normal for that child.
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Zeleno je ono što nam pokazuje
šta je normalno za to dete.
šta je normalno za to dete.
06:29
We call it the cloud of normality.
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To zovemo oblakom normalnosti.
06:32
And when things start to change,
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A kada stvari počnu da se menjaju,
06:34
when conditions start to deteriorate,
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kada uslovi počnu da se pogoršavaju,
06:37
we move into the red line.
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dolazimo do crvene linije.
06:39
There's no rocket science here.
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Nije nuklearna fizika.
06:41
It is displaying data that exists already in a different way,
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Pokazuje podatke koji već postoje
na različite načine,
na različite načine,
06:45
to amplify it, to provide cues to the doctors,
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da ih pojača,
da obezbedi naznake lekarima,
da obezbedi naznake lekarima,
06:48
to the nurses, so they can see what's happening.
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medicinskim sestrama,
kako bi videli šta se dešava.
kako bi videli šta se dešava.
06:51
In the same way that a good racing driver
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Na isti način kao što se dobar vozač
06:54
relies on cues to decide when to apply the brakes,
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oslanja na naznake da odluči
kada da koristi kočnice,
kada da koristi kočnice,
06:58
when to turn into a corner,
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kada da skrene u krivinu,
06:59
we need to help our physicians and our nurses
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treba da pomognemo našim lekarima
i medicinskim sestrama
i medicinskim sestrama
07:02
to see when things are starting to go wrong.
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da uoče stvari
kada počnu da budu loše.
kada počnu da budu loše.
07:06
So we have a very ambitious program.
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Tako da imamo
jako ambiciozan program.
jako ambiciozan program.
07:09
We think that the race is on to do something differently.
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Mislimo da je trka počela
da bi se uradilo nešto drugačije.
da bi se uradilo nešto drugačije.
07:14
We are thinking big. It's the right thing to do.
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Mislimo veliko.
To je prava stvar da se uradi.
To je prava stvar da se uradi.
07:17
We have an approach which, if it's successful,
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Imamo pristup koji, ako je uspešan,
07:20
there's no reason why it should stay within a hospital.
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nema razloga
zašto da ostane unutar bolnica.
zašto da ostane unutar bolnica.
07:22
It can go beyond the walls.
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Može da ide van zidova.
07:24
With wireless connectivity these days,
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Sa bežičnim povezivanjem današnjice,
07:26
there is no reason why patients, doctors and nurses
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nema razloga zašto pacijenti,
lekari i medicinske sestre
lekari i medicinske sestre
07:30
always have to be in the same place
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uvek moraju da budu na istom mestu,
07:32
at the same time.
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u isto vreme.
07:34
And meanwhile, we'll take our little three-month-old baby,
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U međuvremenu,
uzećemo našu tromesečnu bebu,
uzećemo našu tromesečnu bebu,
07:38
keep taking it to the track, keeping it safe,
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nosićemo je na stazu, čuvaćemo je
07:42
and making it faster and better.
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i učinićemo da bude brža i bolja.
07:44
Thank you very much.
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Hvala vam najlepše.
07:45
(Applause)
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(Aplauz)
ABOUT THE SPEAKER
Peter van Manen - Electronic systems expertPeter van Manen is the Managing Director of McLaren Electronics, which provides data systems to major motorsports series.
Why you should listen
To say that Peter van Manen has a high-speed job would be an understatement. As Managing Director of McLaren Electronics, which provides electronics and data collection software to motorsports events, he and his team work in real time during a race to improve cars on about 500 different parameters. That's about 750 million data points in two hours.
But recently van Manen and his team have been wondering: Why can't the extremely precise and subtle data-collection and analysis systems used in motorsports be applied elsewhere, for the benefit of all? They have applied their systems to ICU units at Birmingham Children's Hospital with real-time analysis that allows them to proactively prevent cardiac arrests. The unit has seen a 25 percent decrease in life-threatening events. And it's just the beginning.
Peter van Manen | Speaker | TED.com