When someone speaks, a listener’s brain makes numerous assumptions based on vocal qualities, both consciously and unconsciously. Vocal tone, rhythm, pitch, and other components help us assess age, intent, and emotional state, along with many other characteristics.
Voice can also tell us about the speaker’s health: not just through the human ear but also through AI data science. The Mayo Clinic previously worked with Beyond Verbal to identify vocal biomarkers of coronary artery disease. Now, in a joint effort with Vocalis Health, the Mayo Clinic will initiate a robust study to establish vocal indicators of health conditions, beginning with pulmonary hypertension (PH).
The partnership between Vocalis Health and the Mayo Clinic isn’t new; in a previous trial, the team discovered a link between certain vocal traits and the disease. The new, more extended study will strive to clinically validate specific vocal biomarkers and their ability to enhance diagnosis. In the second phase of the trial, research will expand to include additional symptoms and health conditions.
Pulmonary hypertension refers to high blood pressure in the blood vessels of the lungs. Diagnosing the condition presents a challenge as it presents symptoms that also could indicate several other heart and lung conditions. PH is also a possible complication associated with more severe cases of COVID-19. It can eventually lead to heart failure.
The clinical trial will use Vocalis Health’s software platform to analyze patient voice recordings. Subjects record their voices on a smartphone, tablet, or computer. The study seeks to accurately detect the presence of PH via Vocalis Health’s advanced AI algorithms using only these recordings.
Voice analysis could soon help physicians diagnosis PH and other conditions earlier when treatment outcomes are more likely to succeed. It also offers a no-contact, remote way for providers to screen patients for symptoms of illness with high accuracy. In addition to working with the Mayo Clinic, Vocalis Health is currently focusing on voice analysis for chronic disease monitoring and COVID-19 screening.
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