NYREADERS.COM – At today’s fast-changing and challenging environment, people could easily fall into depression and may lead to serious health problems. Therefore, there is a need to detect depression as early as possible before it is too late.
Thanks to the discovery of Dartmouth researchers who have recently managed to develop the first smartphone application that uses artificial intelligence, paired with facial-image processing software, to reliably detect the onset of depression before the users even know something is wrong.
Called MoodCapture, the app uses a phone's front camera to capture a person's facial expressions and surroundings during regular use, then evaluates the images for clinical cues associated with depression, Dartmouth's Department of Computer Science and Geisel School of Medicine said in a statement.
In a study of 177 people diagnosed with major depressive disorder, the app correctly identified early symptoms of depression with 75 percent accuracy.
These results suggest the technology could be publicly available within the next five years with further development, said the researchers. The team published their paper on the arXiv preprint database in advance of presenting it at the Association of Computing Machinery's CHI 2024 conference in May.
Papers presented at CHI are peer-reviewed before acceptance and will be published in the conference proceedings.
"This is the first time that natural 'in-the-wild' images have been used to predict depression," said Andrew Campbell, the paper's corresponding author and Dartmouth's Albert Bradley 1915 Third Century Professor of Computer Science.
"There's been a movement for digital mental-health technology to ultimately come up with a tool that can predict mood in people diagnosed with major depression in a reliable and non-intrusive way," Campbell said.
"People use facial recognition software to unlock their phones hundreds of times a day," said Campbell, whose phone recently showed he had done so more than 800 times in one week.
"MoodCapture uses a similar technology pipeline of facial recognition technology with deep learning and AI hardware, so there is terrific potential to scale up this technology without any additional input or burden on the user," he said.
"A person just unlocks their phone and MoodCapture knows their depression dynamics and can suggest they seek help."
For the study, the application captured 125,000 images of participants over 90 days. People in the study consented to have their photos taken via their phone's front camera but did not know when it was happening.
The first group of participants was used to program MoodCapture to recognize depression. They were photographed in random bursts using the phone’s front-facing camera as they answered the question, "I have felt down, depressed, or hopeless."
The question is from the eight-point Patient Health Questionnaire or PHQ-8, which is used by clinicians to detect and monitor major depression.
