So, well, I do applied math, and this is a peculiar problem for anyone who does applied math, is that we are like management consultants. No one knows what the hell we do. So I am going to give you some -- attempt today to try and explain to you what I do.
嗯.我是做應用數學的 而對於任何做應用數學的人來說, 我們就像是 管理的諮詢師 沒人知道我們到底幹什麼 因此呢我準備試試 向你解釋一下我幹什麼
So, dancing is one of the most human of activities. We delight at ballet virtuosos and tap dancers you will see later on. Now, ballet requires an extraordinary level of expertise and a high level of skill, and probably a level of initial suitability that may well have a genetic component to it. Now, sadly, neurological disorders such as Parkinson's disease gradually destroy this extraordinary ability, as it is doing to my friend Jan Stripling, who was a virtuoso ballet dancer in his time. So great progress and treatment has been made over the years. However, there are 6.3 million people worldwide who have the disease, and they have to live with incurable weakness, tremor, rigidity and the other symptoms that go along with the disease, so what we need are objective tools to detect the disease before it's too late. We need to be able to measure progression objectively, and ultimately, the only way we're going to know when we actually have a cure is when we have an objective measure that can answer that for sure.
舞蹈可以說是最具人類化的活動了 我們都喜歡芭蕾舞蹈和踢踏舞 你一會兒會看到的 芭蕾要求很高的專業技巧 和很高的技術水準 甚至還需要一些天賦 因此跟你的基因組成也有關 不過可惜的是,像帕金森癥這樣的神經系統疾病 會慢慢的毀滅這樣的能力 就像發生在我一位跳芭蕾舞的朋友, Jan Stripling的身上一樣 近年來在治療上已經有很多進步和應用了 但是呢,這世界上有630萬人有帕金森症 他們每天都得面對 這無法治愈的虛弱,顫抖,僵硬 以及其他一些的癥狀 因此我們需要的是能夠在早期 就探測到疾病的良好工具 我們需要能夠客觀地測量進程, 並且最終,只有我們有能客觀地測量 我們才能研究出 能夠治愈帕金森症的方法
But frustratingly, with Parkinson's disease and other movement disorders, there are no biomarkers, so there's no simple blood test that you can do, and the best that we have is like this 20-minute neurologist test. You have to go to the clinic to do it. It's very, very costly, and that means that, outside the clinical trials, it's just never done. It's never done.
但是遺憾的是,帕金森症和 其他生理障礙還是沒有一個生物標記 因此不可能做一個簡單的驗血就能查出來 目前我們能做到的只是一個 20分鐘的神經系統的測試 你必須去臨床醫院去做,而且十分的貴, 這樣就意味著,除了在臨床試驗中, 我們是不會去做這個測試的
But what if patients could do this test at home? Now, that would actually save on a difficult trip to the clinic, and what if patients could do that test themselves, right? No expensive staff time required. Takes about $300, by the way, in the neurologist's clinic to do it.
不過要是病人在家裡能做的話會怎麼樣? 當然這樣一來他們不必去臨床醫院,對吧? 而且工作人員寶貴的 時間也會節省下來 順便提一下,做這個測試要花醫院 大約300美金呢
So what I want to propose to you as an unconventional way in which we can try to achieve this, because, you see, in one sense, at least, we are all virtuosos like my friend Jan Stripling.
因此我想告訴你一種非傳統的方法 從而達到這個目的 因為你可以看到,至少,一定程度上 我們都是像我朋友Jan Stripling一樣的舞蹈家
So here we have a video of the vibrating vocal folds. Now, this is healthy and this is somebody making speech sounds, and we can think of ourselves as vocal ballet dancers, because we have to coordinate all of these vocal organs when we make sounds, and we all actually have the genes for it. FoxP2, for example. And like ballet, it takes an extraordinary level of training. I mean, just think how long it takes a child to learn to speak. From the sound, we can actually track the vocal fold position as it vibrates, and just as the limbs are affected in Parkinson's, so too are the vocal organs. So on the bottom trace, you can see an example of irregular vocal fold tremor. We see all the same symptoms. We see vocal tremor, weakness and rigidity. The speech actually becomes quieter and more breathy after a while, and that's one of the example symptoms of it.
我這有一個關於波動聲音的視頻 這個是健康的而這個是某人在說話的聲音 我們可以把自己想像為聲音芭蕾舞者 因為我們必須使所有聲音器官都協調起來 當我們發聲的時候,我們都有 固定的基因在配合.比如說FoxP2 跟芭蕾一樣,這需要很高的訓練水準 就想想一個小孩學會說話得多長時間吧 從發出的聲音裏,我們實際上可以 在它震動時找到聲音的位置 就跟肢體一樣,聲音器官 在帕金森症中也會被影響 在這底下,你可以看到一個不尋常的 聲音腫瘤 我們看到的都是一樣的症狀 我們看到腫瘤,虛弱以及僵硬 說話變得越來越虛弱多氣 過一會,就成了其中一個症狀的表現
So these vocal effects can actually be quite subtle, in some cases, but with any digital microphone, and using precision voice analysis software in combination with the latest in machine learning, which is very advanced by now, we can now quantify exactly where somebody lies on a continuum between health and disease using voice signals alone.
這些對聲音的影響可能會很細微, 在有些情況下,使用精細聲音分析軟體 以及目前發展很快的機器製造學中的知識 加上一個數位的麥克風 我們就可以準確地 辨認出人們在健康 和疾病之間的狀態 只用聲音信號就能鑒別
So these voice-based tests, how do they stack up against expert clinical tests? We'll, they're both non-invasive. The neurologist's test is non-invasive. They both use existing infrastructure. You don't have to design a whole new set of hospitals to do it. And they're both accurate. Okay, but in addition, voice-based tests are non-expert. That means they can be self-administered. They're high-speed, take about 30 seconds at most. They're ultra-low cost, and we all know what happens. When something becomes ultra-low cost, it becomes massively scalable. So here are some amazing goals that I think we can deal with now. We can reduce logistical difficulties with patients. No need to go to the clinic for a routine checkup. We can do high-frequency monitoring to get objective data. We can perform low-cost mass recruitment for clinical trials, and we can make population-scale screening feasible for the first time. We have the opportunity to start to search for the early biomarkers of the disease before it's too late.
那麼這些聲音測試是怎麼跟專業 的臨床測試相對比呢?嗯,他們都是不具侵略性的 他們都使用目前存在的設備 你不需要重新設計一套新的設備去做這個測試 而且他們都是準確的.不過呢, 聲音測試不是專家性的 這就意味著這個測試可以由病人自己來做 他們很方便,最多30秒就能做完 而且費用極低,而且我們知道 有些東西一旦十分便宜, 就可以被大規模生產 因此呢我認為我們可以實現一些十分驚人的目標 我們可以減少運輸病人的困難 他們不再需要去臨床做常規檢查 我們可以做高頻率的測控去得到客觀的數據 我們還可以為臨床檢查進行大批的低廉的雇傭 這樣我們就可以使得大規模的檢查 有史以來第一次變得可行 我們可以及時檢查 初期疾病的標誌
So, taking the first steps towards this today, we're launching the Parkinson's Voice Initiative. With Aculab and PatientsLikeMe, we're aiming to record a very large number of voices worldwide to collect enough data to start to tackle these four goals. We have local numbers accessible to three quarters of a billion people on the planet. Anyone healthy or with Parkinson's can call in, cheaply, and leave recordings, a few cents each, and I'm really happy to announce that we've already hit six percent of our target just in eight hours. Thank you. (Applause) (Applause)
因此呢,我們建立了在帕金森聲音 初始計畫上,邁出了第一步 通過Aculab和像我一樣的病人,我們準備 在全球記錄大量的聲音 去收集足夠的數據來實現這四個目標 我們有這地球上7.5億人的 當地電話號碼 任何健康或者有帕金森症的人都可以打電話來, 並且留下一段錄音,一次只花幾美分 而且我很高興地說我們 已經在8個小時內得到了600萬個錄音 謝謝.(鼓掌) (鼓掌)
Tom Rielly: So Max, by taking all these samples of,
Tom Rielly: Max, 通過收集這些,比如說10000人
let's say, 10,000 people, you'll be able to tell who's healthy and who's not? What are you going to get out of those samples?
的樣本, 你就可以看出誰健康誰不是? 你能從這些樣本中看出什麼?
Max Little: Yeah. Yeah. So what will happen is that, during the call you have to indicate whether or not you have the disease or not, you see. TR: Right. ML: You see, some people may not do it. They may not get through it. But we'll get a very large sample of data that is collected from all different circumstances, and it's getting it in different circumstances that matter because then we are looking at ironing out the confounding factors, and looking for the actual markers of the disease.
Max Little: 是的,是的.在通話期間你必須 說明你到底有沒有 帕金森綜合症. TR: 好 ML: 不過有些人可能就不會這麼做 不過我們可以得到一大批從不同境況下 得到的數據,這樣的話這些數據都有用 因為我們就可以找出 混淆的因子 這樣找到真正疾病的標誌
TR: So you're 86 percent accurate right now?
TR: 那目前為止你有百分之86的正確率?
ML: It's much better than that. Actually, my student Thanasis, I have to plug him, because he's done some fantastic work, and now he has proved that it works over the mobile telephone network as well, which enables this project, and we're getting 99 percent accuracy.
ML: 比百分之86還好很多 實際上,我的一個學生Thanasis, 我必須把他提出來 因為他做了一些極棒的工作 現在他已經證明了在移動電話網上也可以測試 這樣一來我們這個計畫基本就有百分之99的正確率
TR: Ninety-nine. Well, that's an improvement. So what that means is that people will be able to — ML: (Laughs) TR: People will be able to call in from their mobile phones and do this test, and people with Parkinson's could call in, record their voice, and then their doctor can check up on their progress, see where they're doing in this course of the disease.
TR: 99. 嗯,這改進還挺高的 那麼這就意味著人們可以---- ML: (笑) TR: 人們就可以從他們手機打來電話 來做這個測試,患有帕金森症的人 可以記錄他們的聲音,然後醫生可以監控 他們的進程,以及他們在做些什麼
ML: Absolutely.
ML: 沒錯,就是這樣
TR: Thanks so much. Max Little, everybody.
TR: 非常感謝, Max Little, 在場的每隔人
ML: Thanks, Tom. (Applause)
ML: 謝謝, Tom.(鼓掌)