Diagnosing Parkinson's in a phone call with a computer
Source: Liz Else
A speech-processing algorithm could use the sound of your voice to diagnose a range of diseases, and spell the end of invasive physical exams
THOUSANDS of people may soon be making a very important three-minute phone call - to a computer. It could tell them whether or not they have Parkinson's disease.
Technology has long promised a revolution in "smart medicine", allowing painful pokes and prods to be replaced with faster, more accurate and non-invasive ways of diagnosing a range of diseases. That vision took a big step forward last week, when Max Little of the Massachusetts Institute of Technology's Media Lab appealed for people worldwide to test a voice-based system he helped develop for diagnosing Parkinson's. The software uses a speech-processing algorithm to identify telltale changes in the voice of a person with the disease.
Parkinson's affects some 6 million people worldwide. Although surgery and drugs can hold back its progression, there is no cure. Diagnosing it and tracking its course usually relies on an assessment of someone's symptoms using the Unified Parkinson's Disease Rating Scale, which involves tests of motor skills, for example. The process is time-consuming, expensive and requires people to attend a clinic for the tests to be carried out. It is partly because of this that it is thought that around a fifth of cases of Parkinson's are never diagnosed.
But the disease often manifests early on in the voice, as it affects the ability to control the vocal cords and soft palate. Common signs include a quaver in the voice, softer speech and breathiness or hoarseness, though they can be subtle at first. This makes Parkinson's a perfect candidate for diagnosis over the phone.
At the TEDglobal conference in Edinburgh, UK, Little explained how he and colleagues used their speech algorithm to process 263 recordings of 43 people, who had been asked to sustain six or seven vowel "ah" sounds. After being trained on 10 impairments or "dysphonias" in these recordings, the algorithm managed to diagnose Parkinson's speech markers 99 per cent of the time in the lab.
Parkinson's is a good place for the telemedicine revolution to start in earnest. "This kind of non-invasive technology, which can be seamlessly integrated into people's lives, could give you data on their social life, daily patterns, and track them over time," Little says. "We end up with a giant database with far fewer risk factors, which will give researchers a way to streamline the hunt."
Little's Parkinson's Voice Initiative website lists phone numbers for people to call the computerised diagnostic system. At the time of writing, the system was a quarter of the way towards the target of 10,000 callers that Little and colleagues are hoping to achieve.
Speech algorithms are already being applied in other diagnostic tests. Spin-offs from other projects at MIT, for example, are being used to spot depression, anxiety and post-traumatic stress disorder to help soldiers returning from battle.
With "life-loggers" and "quantified-selfers" now tracking all aspects of their own lives online, Little expects that freely available data of potential use to healthcare will become increasingly available. That will help create huge data sets and baselines of healthy people that software systems can use to hone their diagnostic capability and identify those who are in need of care.
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