Can AI-based voice analysis help identify mental disorders? – News 24 | News in France and abroad

This article is part of a limited series on the potential of artificial intelligence to solve everyday problems.

Imagine a test as simple and quick as taking your temperature or measuring your blood pressure that could reliably identify an anxiety disorder or predict an impending relapse of depression.

Health care providers have many tools to assess a patient’s physical condition, but no reliable biomarkers – objective indicators of medical conditions observed from outside the patient – ​​to assess mental health.

But some artificial intelligence researchers now think the sound of your voice could be the key to understanding your mental state – and AI is perfectly suited to detect such changes, which are difficult, if not impossible, to perceive otherwise. The result is a collection of apps and online tools designed to track your mental state, as well as programs that provide real-time mental health assessments to telehealth and call center providers.

Psychologists have long known that some mental health problems can be detected not just by listening What one person says but How? ‘Or’ What they say so, said Maria Espinola, a psychologist and assistant professor at the University of Cincinnati College of Medicine.

In depressed patients, Dr. Espinola said, “their speech is usually more monotonous, flatter, and softer. They also have a reduced pitch range and lower volume. They take more breaks. They stop more often.

Anxiety patients feel more tension in their body, which can also alter the sound of their voice, she said. “They tend to speak faster. They have more difficulty breathing.

Today, these types of voice characteristics are being exploited by machine learning researchers to predict depression and anxiety, as well as other mental illnesses like schizophrenia and post-traumatic stress disorder. Using deep learning algorithms can reveal additional patterns and characteristics, as captured in short voice recordings, that might not be obvious even to trained experts.

“The technology we’re using now can extract features that may be meaningful that even the human ear can’t pick up,” said Kate Bentley, assistant professor at Harvard Medical School and clinical psychologist at Massachusetts General Hospital.

“There is a great deal of enthusiasm around the search for biological or more objective indicators of psychiatric diagnoses that go beyond the more subjective forms of assessment that are traditionally used, such as clinician-rated interviews or measures of self-assessment,” she said. Other clues researchers track include changes in activity levels, sleep patterns, and social media data.

These technological advances come at a time when the need for mental health care is particularly acute: According to a report by the National Alliance on Mental Illness, one in five adults in the United States experienced mental illness in 2020. And the numbers continue to rise.

While AI technology can’t address the shortage of skilled mental health care providers — there aren’t enough to meet the country’s needs, Dr Bentley said — there is hope it can reduce barriers to getting a correct diagnosis, help clinicians identify patients who may be hesitant to seek treatment, and facilitate self-monitoring between visits.

“A lot can happen between appointments, and technology can really give us the potential to improve monitoring and evaluation on a more continuous basis,” Dr. Bentley said.

To test this new technology, I started by downloading the Mental fitness app from Sonde Health, a health technology company, to see if my feelings of being unwell were a sign of something serious or just languishing. Described as “a voice-activated mental fitness tracking and journaling product,” the free app prompted me to record my first recording, a 30-second verbal diary entry, which would rank my mental health on a scale from 1 to 100.

A minute later, I had my score: a terrible 52. “Be careful” warned the application.

The app reported that the level of liveliness detected in my voice was particularly low. Did I sound monotonous just because I tried to speak softly? Should I heed the app’s suggestions for improving my mental fitness by walking around or decluttering my space? (The first question may indicate one of the possible defects of the application: as a consumer, it may be difficult to know Why your vocal levels fluctuate.)

Credit…Juan Carlos Pagan

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Can AI-based voice analysis help identify mental disorders? – News 24 | News in France and abroad


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