Researchers from the University of Maryland in US showed that certain vocal features change as patients' feelings of depression worsen.
Rather than relying solely on patients' self-reports, the app could monitor both physical and psychological symptoms of mental illness on a regular basis and provide both patients and their mental health providers with feedback about their status.
To conduct a quantitative experiment on the vocal characteristics of depression acoustician Carol Espy-Wilson and her colleagues repurposed a dataset collected from a 2007 study from an unaffiliated lab also investigating the relationship between depression and speech patterns.
The researchers used data from six patients who, over the six-week course of the previous study, had registered as depressed some weeks and not depressed other weeks.
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They compared these patients' Hamilton scores with their speech patterns each week, and found a correlation between depression and certain acoustic properties.
When patients' feelings of depression were worst, their speech tended to be breathier and slower.
The team also found increases in jitter and shimmer, two measures of acoustic disturbance that measure the frequency and amplitude variation of the sound, respectively. Speech high in jitter and shimmer tends to sound hoarse or rough.
A phone app could use this information to analyse patients' speech, identify acoustic signatures of depression and provide feedback and support.
Espy-Wilson hopes the interactive technology will appeal to teens and young adults, a particularly vulnerable group for mental health problems.
"Their emotions are all over the place during this time, and that's when they're really at risk for depression. We have to reach out and figure out a way to help kids in that stage," she said.
The technology could also promote communication between therapists and patients, allowing for continuous, responsive care in addition to regular in-person appointments.