In the digital age, we have become increasingly aware of our own health and the core symptoms that can be indicative of illness. This has made it far easier for people recognise when they are unwell, increasing their chances of successfully treating ailments and returning to full health over time.
A similar trend has driven preventative medicine throughout the age, as innovation and research have enabled healthcare service providers to improve diagnostics and pre-treatment options rather than focusing solely on reactive measures. This was seen during the recent outbreak of the Zika virus in South America, where a novel vaccine candidate was quickly presented to protect citizens in affected areas.
Why the Sound of your Voice is now a key Diagnostic Tool
In terms of diagnostics, technology has also enabled doctors to improve their accuracy while determining new methods of identifying specific illnesses. Most recently, employees at the Massachusetts Institute of Technology have developed an innovation that has introduced a new diagnostic metric, which is the sound of each individual patient’s voice. This hardware, which is still under development, analyses voices according to tone and the speed at which words and sentences are formed.
By analysing various aspects of a patient’s voice, doctors are able to determine subtle vocal tics that will enable them to diagnose illnesses at a very early stage. This includes everything from mental health issues such as depression to respiratory disorders, as healthcare professionals search for time-dependent variations in pitch and subtle shifts in pace. In laymen terms, this technology builds on accepted knowledge pertaining to the links between voice patterns and certain illnesses (such as the fact that those with depression may occasionally speak with a flatter tone) to drive informed, accurate and insightful diagnostics.
The hardware has been tested extensively across several groups of subjects, which were required to read standard, sample paragraphs. The technology breaks these statements down into individual components called phonemes, known by linguistic experts as the building blocks of language. These phonemes are then analysed using proprietary algorithms, highlighting potential issues and singling out specific symptoms. These can relate to numerous ailments, from mild traumatic brain disease to dementia and Parkinson’s disease.
Is this just the beginning for voice analysis in Diagnostics?
The research team working on this technology are not alone in their quest, with IMB currently teaming its own, Watson super-computer with academic research teams to identify potential psychological issues in subjects using speech patterns. A Berlin-based company has also worked on developing hardware that can diagnose ADHD patients with voice recordings, while apps are also being developed across the globe base on tone and speech patterns. Make no mistake; however, the research being conducted at the Massachusetts Institute of Technology is at an advanced stage while the current hardware requires only a minute of speech to identify the vocal biomarkers that represent symptoms of mental and physical illness.
What is more, this may be just the tip of the iceberg for the utilisation of tone and speech patterns, particularly as the voice remains a complex and scarcely understood aspects of our physiology. With huge data sets hidden within the composition of our voice, this latest innovation may herald a new dawn in the field of diagnostics and preventative care, particularly in relation to ailments that are chronically under-diagnosed and difficult to identify. This includes complex mood disorders and mild cases of depression, where there remains a lack of easily distinguishable symptoms and objective screening. Ultimately, this technology may eradicate these issues in some cases, while also advancing to the point where it is accessible to laymen through a downloadable mobile application.
The post The Sound Of Your Voice Could Help Doctors Diagnose Disease, Research Finds appeared first on Lifehack.
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