Researchers at the University of Texas at Dallas are exploring a groundbreaking way to detect mental health crises before they happen by analyzing how people move.<\/p>\n
Gu Eon Kang, PhD, an assistant bioengineering professor at UTD, is leading a team of student researchers to identify markers for depression, anxiety, and psychological distress through physical motion.<\/p>\n
The “Hallmark” of Movement<\/p>\n
While many might assume a mental health struggle would simply result in a slower walking pace, researchers found that the indicators are much more subtle.<\/p>\n
“When you think of someone who’s sad, I was really expecting people who walked slower,” said doctoral student Angeloh Stout. “In doing my analysis, the big hallmark is all about your posture… not necessarily how fast you walk.”<\/p>\n
Professor Kang demonstrated that jerky or stiff movements\u2014such as an elbow extension that isn’t smooth\u2014are significant indicators of a potential crisis.<\/p>\n
Inside the Lab<\/p>\n
The team uses a sophisticated setup to capture this data:<\/p>\n
Reflective Markers: Small, thimble-like nodules are attached to a subject’s skin and clothing.<\/p>\n
Infrared Cameras: Cameras surrounding the lab bounce light off the markers to track precise movement.<\/p>\n
Complex Data: Computers record intricate measurements as participants walk across platforms or stand up from a chair.<\/p>\n
By comparing this computer data to participants’ self-assessments, the team found high levels of accuracy. A standard straight walk predicted anxiety or depression with 75% accuracy, while the “sit to walk” movement increased that accuracy to 78%.<\/p>\n
A Tool for the Future<\/p>\n
The goal of the research is to provide technology-based solutions for a demographic that needs it most. Stout noted that statistics show nearly half of college students experience depression or anxiety.<\/p>\n
“Now we are exploring a way to predict suicidal thoughts, especially in college students, just based on body movement,” Professor Kang explained. “We want to help people, and we want to save people.”<\/p>\n
The team envisions a future where wearable or in-home devices could flag a mental health risk and prompt someone to seek care\u2014perhaps even triggering soothing music if a risk is detected during a morning routine.<\/p>\n
While the research is not intended to replace professional mental health care, the team believes it can become a vital tool for early intervention.<\/p>\n
“It works,” said Professor Kang. “It works pretty well.”<\/p>\n
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