Voice analysis used to predict coronary artery disease
A study by the American College of Cardiology (ACC) is the first to use an artificial intelligence (AI)-based system to predict incidences of coronary artery disease (CAD) by analysing voice markers. Cardiology fellow Dr. Jaskanwal Deep Singh Sara said that the autonomic nervous system, which regulates the voice box and vital aspects of the cardiovascular system, may play a role.
For the new study, Dr. Sara and other researchers recruited 108 participants who were referred for a coronary angiogram (an X-ray imaging procedure used to assess the condition of the heart’s arteries). Participants were also asked to record three 30-second voice samples using the US-based Vocalis Health smartphone application. For the first sample, participants read from a prepared text; for the second sample, they were asked to speak freely about a positive experience; and for the third, they were asked to speak about a negative experience.
The Vocalis Health AI algorithm then analysed the participants’ voice samples, picking out features such as frequency, amplitude, pitch, and cadence, based on a training set of over 10,000 voice samples collected in Israel. These features were catagorised into a single score, expressed as a number between -1 and 1 for each individual: one-third of participants had a high score, and two-thirds had a low score.
In the two years that followed, those with a high voice biomarker score, 58.3% reported visiting the hospital for chest pain or suffered acute coronary syndrome (a type of major heart problem that includes heart attacks). This score was compared with 30.6% of those with a low voice biomarker score. Participants with a high voice biomarker score were also more likely to have a positive stress test or be diagnosed with CAD during a subsequent angiogram.
As mentioned earlier, it is possible that the voice could provide clues about how the autonomic nervous system is functioning, and by extension, provide insights into cardiovascular health. Voice analysis could be a powerful screening tool in identifying patients who may benefit from closer monitoring for CAD-related events – this approach could be particularly useful in remote health care delivery and telemedicine/telehealth.
“Telemedicine is non-invasive, cost-effective and efficient and has become increasingly important during the pandemic,” said, Dr. Sara. “We’re not suggesting that voice analysis technology would replace doctors or replace existing methods of health care delivery, but we think there’s a huge opportunity for voice technology to act as an adjunct to existing strategies.
“Providing a voice sample is very intuitive and even enjoyable for patients, and it could become a scalable means for us to enhance patient management.”
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