It is indeed a cutting-edge, non-invasive diagnostic technique that can predict chronic hypertension (hypertension) with a high degree of accuracy simply using the patient’s voice. Research advances early detection of chronic high blood pressureone of the most worrying health burdens since it affects 1 in 3 adults worldwide and causes a number of serious complications, including heart attacks, kidney problems and dementia.
The diagnostic potential of vocal biomarkers
The study is conducted with 245 participants invited to record their voice 6 times a day for 2 weeks while speaking in a mobile application developed for the study. Speech markers considered in the model included hundreds of speech biomarkers indistinguishable to the human ear, including pitch variability (fundamental frequency), speech energy distribution patterns (MFCC: Mel Frequency Cepstral Coefficients) and the sharpness of sound changes (spectral contrast). Voice analysis, combined with artificial intelligence (AI), has made it possible to:
- detect hypertension with an accuracy of 84% in women and 77% in men.
“So this is a more accessible way to detect hypertension, which we hope will lead to earlier intervention”summarizes the main author, Yan Fossat, vice-president of Klick Labs.
Tracking the “silent killer” by voice
“Silent killer” is the term used by the World Health Organization (WHO) to qualify hypertension. Because half of people with hypertension are unaware of their condition and are therefore not treated. Conventional methods of measuring blood pressure may require technical expertise, specialized equipment and are not always easily accessible to people living in certain regions of the world.
The Klick Labs team had previously worked on using voice technology to identify diabetes, and this new development confirms the potential of voice markers in detecting chronic diseases.
“Voice technology has the potential to exponentially transform healthcare, making it more accessible and affordable, particularly for dense, poorer, and underserved healthcare populations.”
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