Facing their fears: VR goggles will be used to treat teens with anxiety and depression by Erin Kayata October 28, 2023 Share Facebook LinkedIn Twitter Sarah Ostadabbas, associate professor of electrical and computer engineering and her PhD students, Xiaofei Huang and Shaotong Zhu, are working on augmented reality technologies that’ll help therapists treat teens with depression and anxiety by allowing patients to face their fears in a more realistic way. Photos by Matthew Modoono/Northeastern University Depression and anxiety rates — high even before COVID-19 — have increased over the last few years thanks to the pandemic. The World Health Organization estimates these illnesses affect a quarter of the world’s population and cost the global economy $1 trillion annually. Treatment includes talk therapy, but only so much can be done within the confines of a clinician’s office. A Northeastern professor is part of the solution to try to change this. Sarah Ostadabbas, an associate professor in the electrical and computer engineering department, is leading a National Science Foundation grant with the University of Pittsburgh to develop technology that’ll use augmented reality (AR) to help treat teens with anxiety and depression. The proposed system would use hardware — specifically AR goggles — and machine learning software to create an immersive 3D environment to help patients confront their fears in a more realistic way while an EEG cap monitoring their brain activities would allow therapists to track patients’ brain signals, its responses to the fear stimuli, and their progress after a course of prescribed treatment. Sarah Ostadabbas, associate professor of electrical and computer engineering and her PhD students, Xiaofei Huang and Shaotong Zhu, are working on augmented reality technologies that’ll help therapists treat teens with depression and anxiety by allowing patients to face their fears in a more realistic way. Photos by Matthew Modoono/Northeastern University “Depression and anxiety have been on the rise dramatically, and unfortunately a lot of these teens do not respond well to the therapy that is prescribed to them,” Ostadabbas said. “Teens who don’t respond to standard therapy are at a greater risk of serious consequences, including suicide and shortened life expectancy. Exposure therapy, a well-known treatment, involves gradual real-world exposure to fears. However, asking teenagers to self-monitor fear levels can be challenging. It disrupts their immersion in real-life experiences, reduces authenticity, and might be forgotten, especially during times of heightened social anxiety” Ostadabbas, with expertise in machine learning, computer vision, and mixed reality technology development, has partnered with engineers at the University of Pittsburgh in the past to create the first of its kind technology to analyze signals from the brain to control the display of contents in the AR environment. The new grant will take things a step further by advancing this technology to change treatment by offering the chance to expose patients to their stressors using augmented reality. This, combined with the monitoring of brain signals, can allow therapists to monitor patients’ progress and change the exposure intensity as needed. “Our expertise within … augmented reality systems allows us to make specific scenarios in the augmented reality environment which means that the specific scenario can then be very immersive,” Ostadabbas said. “It’s going to be 3D and also can be overlaid on different environments and conditions.” There is currently no product like this on the market. Researchers hope the new technology will fill the existing gap in treatment by allowing teens to practice facing their fears in a more realistic way. The goggles can be used to expose patients to fears like public speaking, Ostadabbas said. Monitoring brain signals can help the therapists make diagnoses and track progress over time by seeing how patients react to their fears in the goggles and working with them to overcome them accordingly. Ostadabbas said this can be a more effective way of determining whether treatment is working because it shows what patients are feeling rather than relying on them to communicate this. “This project entails creating innovative machine learning algorithms for detecting and quantifying fear levels in response to various stimuli solely through the analysis of brain signals,” she added. The researchers will also partner with community experts and offer training to partners working with students from high school to the graduate level. Erin Kayata is a Northeastern Global News reporter. Email her at firstname.lastname@example.org. Follow her on X/Twitter @erin_kayata.