Return to Video

A test for Parkinson's with a phone call

  • 0:01 - 0:03
    So, well, I do applied math,
  • 0:03 - 0:04
    and this is a peculiar problem
  • 0:04 - 0:06
    for anyone who does applied math, is that
  • 0:06 - 0:08
    we are like management consultants.
  • 0:08 - 0:10
    No one knows what the hell we do.
  • 0:10 - 0:13
    So I am going to give you some -- attempt today
  • 0:13 - 0:15
    to try and explain to you what I do.
  • 0:15 - 0:18
    So, dancing is one of the most human of activities.
  • 0:18 - 0:22
    We delight at ballet virtuosos and tap dancers
  • 0:22 - 0:23
    you will see later on.
  • 0:23 - 0:26
    Now, ballet requires an extraordinary level of expertise
  • 0:26 - 0:29
    and a high level of skill,
  • 0:29 - 0:31
    and probably a level of initial suitability
  • 0:31 - 0:33
    that may well have a genetic component to it.
  • 0:33 - 0:36
    Now, sadly, neurological disorders such as Parkinson's disease
  • 0:36 - 0:39
    gradually destroy this extraordinary ability,
  • 0:39 - 0:41
    as it is doing to my friend Jan Stripling, who was
  • 0:41 - 0:44
    a virtuoso ballet dancer in his time.
  • 0:44 - 0:47
    So great progress and treatment has been made over the years.
  • 0:47 - 0:50
    However, there are 6.3 million people worldwide
  • 0:50 - 0:53
    who have the disease, and they have to live with
  • 0:53 - 0:56
    incurable weakness, tremor, rigidity
  • 0:56 - 0:58
    and the other symptoms that go along with the disease,
  • 0:58 - 1:00
    so what we need are objective tools
  • 1:00 - 1:03
    to detect the disease before it's too late.
  • 1:03 - 1:06
    We need to be able to measure progression objectively,
  • 1:06 - 1:09
    and ultimately, the only way we're going to know
  • 1:09 - 1:11
    when we actually have a cure is when we have
  • 1:11 - 1:14
    an objective measure that can answer that for sure.
  • 1:14 - 1:17
    But frustratingly, with Parkinson's disease
  • 1:17 - 1:20
    and other movement disorders, there are no biomarkers,
  • 1:20 - 1:22
    so there's no simple blood test that you can do,
  • 1:22 - 1:24
    and the best that we have is like
  • 1:24 - 1:26
    this 20-minute neurologist test.
  • 1:26 - 1:28
    You have to go to the clinic to do it. It's very, very costly,
  • 1:28 - 1:31
    and that means that, outside the clinical trials,
  • 1:31 - 1:34
    it's just never done. It's never done.
  • 1:34 - 1:37
    But what if patients could do this test at home?
  • 1:37 - 1:39
    Now, that would actually save on a difficult trip to the clinic,
  • 1:39 - 1:43
    and what if patients could do that test themselves, right?
  • 1:43 - 1:45
    No expensive staff time required.
  • 1:45 - 1:47
    Takes about $300, by the way,
  • 1:47 - 1:49
    in the neurologist's clinic to do it.
  • 1:49 - 1:51
    So what I want to propose to you as an unconventional way
  • 1:51 - 1:53
    in which we can try to achieve this,
  • 1:53 - 1:55
    because, you see, in one sense, at least,
  • 1:55 - 1:58
    we are all virtuosos like my friend Jan Stripling.
  • 1:58 - 2:02
    So here we have a video of the vibrating vocal folds.
  • 2:02 - 2:05
    Now, this is healthy and this is somebody making speech sounds,
  • 2:05 - 2:08
    and we can think of ourselves as vocal ballet dancers,
  • 2:08 - 2:11
    because we have to coordinate all of these vocal organs
  • 2:11 - 2:13
    when we make sounds, and we all actually
  • 2:13 - 2:15
    have the genes for it. FoxP2, for example.
  • 2:15 - 2:18
    And like ballet, it takes an extraordinary level of training.
  • 2:18 - 2:20
    I mean, just think how long it takes a child to learn to speak.
  • 2:20 - 2:23
    From the sound, we can actually track
  • 2:23 - 2:25
    the vocal fold position as it vibrates,
  • 2:25 - 2:28
    and just as the limbs are affected in Parkinson's,
  • 2:28 - 2:30
    so too are the vocal organs.
  • 2:30 - 2:32
    So on the bottom trace, you can see an example of
  • 2:32 - 2:34
    irregular vocal fold tremor.
  • 2:34 - 2:35
    We see all the same symptoms.
  • 2:35 - 2:38
    We see vocal tremor, weakness and rigidity.
  • 2:38 - 2:40
    The speech actually becomes quieter and more breathy
  • 2:40 - 2:42
    after a while, and that's one of the example symptoms of it.
  • 2:42 - 2:45
    So these vocal effects can actually be quite subtle,
  • 2:45 - 2:48
    in some cases, but with any digital microphone,
  • 2:48 - 2:51
    and using precision voice analysis software
  • 2:51 - 2:53
    in combination with the latest in machine learning,
  • 2:53 - 2:55
    which is very advanced by now,
  • 2:55 - 2:58
    we can now quantify exactly where somebody lies
  • 2:58 - 3:01
    on a continuum between health and disease
  • 3:01 - 3:03
    using voice signals alone.
  • 3:03 - 3:06
    So these voice-based tests, how do they stack up against
  • 3:06 - 3:08
    expert clinical tests? We'll, they're both non-invasive.
  • 3:08 - 3:12
    The neurologist's test is non-invasive. They both use existing infrastructure.
  • 3:12 - 3:15
    You don't have to design a whole new set of hospitals to do it.
  • 3:15 - 3:17
    And they're both accurate. Okay, but in addition,
  • 3:17 - 3:20
    voice-based tests are non-expert.
  • 3:20 - 3:22
    That means they can be self-administered.
  • 3:22 - 3:25
    They're high-speed, take about 30 seconds at most.
  • 3:25 - 3:27
    They're ultra-low cost, and we all know what happens.
  • 3:27 - 3:30
    When something becomes ultra-low cost,
  • 3:30 - 3:32
    it becomes massively scalable.
  • 3:32 - 3:36
    So here are some amazing goals that I think we can deal with now.
  • 3:36 - 3:38
    We can reduce logistical difficulties with patients.
  • 3:38 - 3:40
    No need to go to the clinic for a routine checkup.
  • 3:40 - 3:43
    We can do high-frequency monitoring to get objective data.
  • 3:43 - 3:47
    We can perform low-cost mass recruitment for clinical trials,
  • 3:47 - 3:49
    and we can make population-scale screening
  • 3:49 - 3:51
    feasible for the first time.
  • 3:51 - 3:53
    We have the opportunity to start to search
  • 3:53 - 3:56
    for the early biomarkers of the disease before it's too late.
  • 3:56 - 3:59
    So, taking the first steps towards this today,
  • 3:59 - 4:01
    we're launching the Parkinson's Voice Initiative.
  • 4:01 - 4:03
    With Aculab and PatientsLikeMe, we're aiming
  • 4:03 - 4:05
    to record a very large number of voices worldwide
  • 4:05 - 4:09
    to collect enough data to start to tackle these four goals.
  • 4:09 - 4:10
    We have local numbers accessible to three quarters
  • 4:10 - 4:12
    of a billion people on the planet.
  • 4:12 - 4:15
    Anyone healthy or with Parkinson's can call in, cheaply,
  • 4:15 - 4:17
    and leave recordings, a few cents each,
  • 4:17 - 4:19
    and I'm really happy to announce that we've already hit
  • 4:19 - 4:23
    six percent of our target just in eight hours.
  • 4:23 - 4:27
    Thank you. (Applause)
  • 4:27 - 4:33
    (Applause)
  • 4:33 - 4:36
    Tom Rielly: So Max, by taking all these samples of,
  • 4:36 - 4:39
    let's say, 10,000 people,
  • 4:39 - 4:42
    you'll be able to tell who's healthy and who's not?
  • 4:42 - 4:44
    What are you going to get out of those samples?
  • 4:44 - 4:46
    Max Little: Yeah. Yeah. So what will happen is that,
  • 4:46 - 4:47
    during the call you have to indicate whether or not
  • 4:47 - 4:49
    you have the disease or not, you see. TR: Right.
  • 4:49 - 4:51
    ML: You see, some people may not do it. They may not get through it.
  • 4:51 - 4:54
    But we'll get a very large sample of data that is collected
  • 4:54 - 4:57
    from all different circumstances, and it's getting it
  • 4:57 - 4:59
    in different circumstances that matter because then
  • 4:59 - 5:02
    we are looking at ironing out the confounding factors,
  • 5:02 - 5:05
    and looking for the actual markers of the disease.
  • 5:05 - 5:07
    TR: So you're 86 percent accurate right now?
  • 5:07 - 5:08
    ML: It's much better than that.
  • 5:08 - 5:10
    Actually, my student Thanasis, I have to plug him,
  • 5:10 - 5:12
    because he's done some fantastic work,
  • 5:12 - 5:16
    and now he has proved that it works over the mobile telephone network as well,
  • 5:16 - 5:19
    which enables this project, and we're getting 99 percent accuracy.
  • 5:19 - 5:21
    TR: Ninety-nine. Well, that's an improvement.
  • 5:21 - 5:23
    So what that means is that people will be able to —
  • 5:23 - 5:25
    ML: (Laughs)
  • 5:25 - 5:27
    TR: People will be able to call in from their mobile phones
  • 5:27 - 5:30
    and do this test, and people with Parkinson's could call in,
  • 5:30 - 5:33
    record their voice, and then their doctor can check up
  • 5:33 - 5:35
    on their progress, see where they're doing in this course of the disease.
  • 5:35 - 5:36
    ML: Absolutely.
  • 5:36 - 5:38
    TR: Thanks so much. Max Little, everybody.
  • 5:38 - 5:43
    ML: Thanks, Tom. (Applause)
Title:
A test for Parkinson's with a phone call
Speaker:
Max Little
Description:

Parkinson’s disease affects 6.3 million people worldwide, causing weakness and tremors, but there's no objective way to detect it early on. Yet. Applied mathematician and TED Fellow Max Little is testing a simple, cheap tool that in trials is able to detect Parkinson's with 99 percent accuracy -- in a 30-second phone call.

more » « less
Video Language:
English
Team:
closed TED
Project:
TEDTalks
Duration:
06:04

English subtitles

Revisions Compare revisions