{"id":10727,"date":"2026-09-01T06:00:00","date_gmt":"2026-09-01T13:00:00","guid":{"rendered":"https:\/\/keck.usc.edu\/news\/?p=10727"},"modified":"2026-09-09T08:43:55","modified_gmt":"2026-09-09T15:43:55","slug":"usc-researchers-to-develop-ai-powered-platform-to-predict-depression-suicide-risk-and-resilience","status":"publish","type":"post","link":"https:\/\/keck.usc.edu\/news\/usc-researchers-to-develop-ai-powered-platform-to-predict-depression-suicide-risk-and-resilience\/","title":{"rendered":"USC researchers\u00a0to\u00a0develop\u00a0AI-powered platform to predict depression,\u00a0suicide risk, and resilience"},"content":{"rendered":"\n

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USC researchers\u00a0to\u00a0develop\u00a0AI-powered platform to predict depression,\u00a0suicide risk, and resilience<\/h1>\n\n\n<\/div>\n \n \n
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Funded by ARPA-H, the research team will collect detailed data on brain activity, sleep, smartphone use and more to build a picture of risks and protective factors among USC students with depression.<\/p>\n\n\n\n<\/div>\n \n

\n Zara Abrams<\/span>\n \n September 01, 2026<\/span>\n <\/div>\n \n \n
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In the United States, more than 47,000 people die by suicide each year and more than 10 million seriously consider it, according to the U.S. Centers for Disease Control and Prevention. But clinicians often have few ways to detect when someone is heading toward a crisis before it happens.<\/p>\n

To shift from reaction toward prevention, a team of USC researchers is developing an AI-driven platform that aims to predict both risk factors and protective factors for depression and suicide using patterns in brain activity and behavior. The project, supported by a contract award of up to $4 million from the Advanced Research Projects Agency for Health (ARPA-H<\/a>), will continuously monitor college student mental health through a combination of lab tests, wearable sensors and smartphone data. Its findings could help pinpoint when a mental health crisis is imminent and how best to intervene.<\/p>\n

The new study, known as Scalable Evaluation of Neurobehavioral Trajectories in Everyday Life (SENTINEL), will track approximately 210 USC students for up to 36 months. Study participants will be evenly split between three groups: students with no mental health concerns, students with depression, and students with depression that includes suicidal thoughts or behaviors.<\/p>\n

Earlier research<\/a> from the same team found that adults experiencing suicidal thoughts show distinct patterns in eye movements, brain activity and other measurable biological signals, such as sweat.<\/p>\n

\u201cThis project allows us to look at big questions about mental health that no single discipline could answer on its own. By combining different perspectives, expertise and tools, we hope to connect the dots in ways that haven\u2019t been possible until now,\u201d said principal investigator Shrikanth (Shri) Narayanan, PhD<\/a>, a University Professor, the Niki and Max Nikias Chair in Engineering, vice president for presidential initiatives at USC, and professor of electrical and computer engineering, computer science, linguistics, pediatrics, otolaryngology-head and neck surgery, and music.<\/p>\n

\u201cWe know that mental health is a serious issue among college students, but we still have much to learn about the early warning signs that someone is starting to struggle,\u201d said Assal Habibi, PhD<\/a>, an associate professor of psychology at the Brain and Creativity Institute<\/a> at the USC Dornsife College of Letters, Arts and Sciences and one of the project\u2019s co-principal investigators.<\/p>\n

SENTINEL is funded by ARPA-H, an agency within the U.S. Department of Health and Human Services that supports rapid innovation to solve the country\u2019s toughest health challenges. After two years, the award may be renewed for an additional two years, bringing total funding to up to $7 million. SENTINEL includes experts from the USC Viterbi School of Engineering, Keck School of Medicine of USC <\/a>and USC Dornsife <\/a>with a combination of clinical, technical and neuroscientific expertise.<\/p>\n

Detecting risk and resilience<\/strong><\/h2>\n

Once enrolled in SENTINEL, participants will complete a series of tasks and tests in the laboratory every six months. These include EEG (a measure of brain activity), eye tracking and detailed psychiatric questionnaires.<\/p>\n

They will also be given wearable devices, such as an Oura Ring or Fitbit, to gather additional data on their daily habits and well-being. These devices provide information on heart rate, heart rate variability, skin temperature, skin conductance (a measure of stress), blood oxygen levels, physical activity, and sleep stages and duration.<\/p>\n

In addition, students will complete weekly questionnaires through a smartphone app about their stress, anxiety, mood, overall well-being, and daily challenges and positive experiences. They will answer some questions by voice so researchers can analyze speech patterns. With consent, researchers will also collect smartphone data on app usage, communication patterns and attention.<\/p>\n

The study is designed to capture not just periods of distress, but also moments when students are doing well.<\/p>\n

\u201cNot only are we interested in the risk factors that make someone vulnerable to depression and suicidal thoughts, but also what makes them resilient,\u201d said Rael Cahn, MD, PhD<\/a>, a clinical associate professor of psychiatry and the behavioral sciences at the Keck School of Medicine and a co-principal investigator of SENTINEL.<\/p>\n

Averting a crisis<\/strong><\/h2>\n

While the study is observational, the researchers aim to rapidly translate its findings into tools that can help clinicians identify risk and intervene early. For example, the research may identify patterns in sleep, activity or stress that signal someone is becoming more vulnerable, helping clinicians decide when to offer therapy, mindfulness exercises, medication or other forms of support.<\/p>\n

Over the longer term, the technology could also be adapted to monitor other mental health conditions and to support high-stress populations such as health care workers, first responders and military personnel.<\/p>\n

In addition to Habibi, Narayanan and Cahn, Richard M. Leahy, PhD<\/a>, a professor of electrical and computer engineering, biomedical engineering and radiology at the USC Viterbi School of Engineering, is a co-principal investigator on the project.<\/p>\n

About this research<\/strong><\/h2>\n

The project is supported by \u00a0ARPA-H\u2019s EVIDENT initiative<\/a>, which aims to accelerate behavioral health research through detailed, real-time clinical data collection. Using digital tools, brain measures, and biological sampling, EVIDENT-supported projects contribute de-identified data to a secure national repository, helping researchers identify patterns associated with rapid changes in mental health. ARPA-H is an agency within the U.S. Department of Health and Human Services that supports bold, high-impact research designed to transform health outcomes.<\/p>\n

This research was funded, in part, by the Advanced Research Projects Agency for Health (ARPA-H). The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the U.S. Government.<\/p>\n

For more information about ARPA-H, visit\u00a0ARPA-H.gov<\/a>.<\/p>\n\n\n\n<\/div>\n <\/div>\n\n\n <\/div><\/div>\n","protected":false},"excerpt":{"rendered":"","protected":false},"author":278,"featured_media":10728,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"advgb_blocks_editor_width":"","advgb_blocks_columns_visual_guide":"","footnotes":"","_links_to":"","_links_to_target":""},"categories":[6],"tags":[640,476,513,446,169,20,230],"class_list":["post-10727","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-press-release","tag-alfred-e-mann-department-of-biomedical-engineering","tag-brain-health","tag-department-of-psychiatry-and-the-behavioral-sciences","tag-homepage","tag-latest","tag-research","tag-usc-viterbi-school-of-engineering"],"acf":[],"yoast_head":"\nUSC researchers\u00a0to\u00a0develop\u00a0AI-powered platform to predict depression,\u00a0suicide risk, and resilience<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/keck.usc.edu\/news\/usc-researchers-to-develop-ai-powered-platform-to-predict-depression-suicide-risk-and-resilience\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"USC researchers\u00a0to\u00a0develop\u00a0AI-powered platform to predict depression,\u00a0suicide risk, and resilience\" \/>\n<meta property=\"og:url\" content=\"https:\/\/keck.usc.edu\/news\/usc-researchers-to-develop-ai-powered-platform-to-predict-depression-suicide-risk-and-resilience\/\" \/>\n<meta property=\"og:site_name\" content=\"Newsroom\" \/>\n<meta property=\"article:publisher\" content=\"https:\/\/www.facebook.com\/KECKschoolUSC\/\" \/>\n<meta property=\"article:published_time\" content=\"2026-09-01T13:00:00+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2026-09-09T15:43:55+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/keck.usc.edu\/news\/wp-content\/uploads\/sites\/68\/2026\/08\/iStock-2266142686.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"2309\" \/>\n\t<meta property=\"og:image:height\" content=\"1299\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"author\" content=\"sheilaro\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:creator\" content=\"@KeckSchool_USC\" \/>\n<meta name=\"twitter:site\" content=\"@KeckSchool_USC\" \/>\n<meta name=\"twitter:label1\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data1\" content=\"5 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\\\/\\\/keck.usc.edu\\\/news\\\/usc-researchers-to-develop-ai-powered-platform-to-predict-depression-suicide-risk-and-resilience\\\/#article\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/keck.usc.edu\\\/news\\\/usc-researchers-to-develop-ai-powered-platform-to-predict-depression-suicide-risk-and-resilience\\\/\"},\"author\":{\"name\":\"sheilaro\",\"@id\":\"https:\\\/\\\/keck.usc.edu\\\/news\\\/#\\\/schema\\\/person\\\/e82dc048d2c960e661893c9fca68c083\"},\"headline\":\"USC researchers\u00a0to\u00a0develop\u00a0AI-powered platform to predict depression,\u00a0suicide risk, and resilience\",\"datePublished\":\"2026-09-01T13:00:00+00:00\",\"dateModified\":\"2026-09-09T15:43:55+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\\\/\\\/keck.usc.edu\\\/news\\\/usc-researchers-to-develop-ai-powered-platform-to-predict-depression-suicide-risk-and-resilience\\\/\"},\"wordCount\":13,\"publisher\":{\"@id\":\"https:\\\/\\\/keck.usc.edu\\\/news\\\/#organization\"},\"image\":{\"@id\":\"https:\\\/\\\/keck.usc.edu\\\/news\\\/usc-researchers-to-develop-ai-powered-platform-to-predict-depression-suicide-risk-and-resilience\\\/#primaryimage\"},\"thumbnailUrl\":\"https:\\\/\\\/keck.usc.edu\\\/news\\\/wp-content\\\/uploads\\\/sites\\\/68\\\/2026\\\/08\\\/iStock-2266142686.jpg\",\"keywords\":[\"Alfred E. 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