Tag : Wearable

Washington: Managing one's mental health has been a higher priority in recent years, with an increased emphasis on self-care. Every year, more than 300 million people worldwide suffer from depression. Recognizing this, there is a lot of interest in using popular wearable gadgets to monitor a person's mental health by tracking markers like activity level, sleep, and heart rate. A team of researchers at Washington University in St. Louis and at the University of Illinois Chicago used data from wearable devices to predict outcomes of treatment for depression on individuals who took part in a randomized clinical trial. They developed a novel machine learning model that analyzes data from two sets of patients -- those randomly selected to receive treatment and those who did not receive treatment -- instead of developing a separate model for each group. This unified multitask model is a step toward personalized medicine, in which physicians design a treatment plan specific to each patient's needs and predict outcome based on an individual's data. Findings of the research were published in the Proceedings of the ACM on Interactive, Model, Wearable and Ubiquitous Technologies and will be presented at the UbiComp 2022 conference in September. Chenyang Lu, the Fullgraf Professor at the McKelvey School of Engineering, led a team including Ruixuan Dai, who worked in Lu's lab as a doctoral student and is now a software engineer at Google; Thomas Kannampallil, associate professor of anesthesiology and associate chief research information officer at the School of Medicine and associate professor of computer science and engineering at McKelvey Engineering; and Jun Ma, MD, PhD, professor of medicine at the University of Illinois Chicago (UIC); and co ...