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Wearable device for detecting compulsive behaviours

Addressing the challenge of monitoring and treating Obsessive-Compulsive Disorder (OCD), where nearly 40% of patients do not respond to traditional therapies. The solution is a wearable device using MXene electrodes to detect compulsive behaviour by capturing high-quality neuromotor signals from the forearm. The data is processed through a machine-learning algorithm, which identifies OCD with 80% accuracy. This innovation has the potential to enhance treatment outcomes by integrating it into closed-loop Deep Brain Stimulation systems, offering a more precise therapeutic approach

Student

Juan Lopez Luna
University of Pennsylvania
Juan Lopez Luna earned a master’s in electrical engineering from the Research and Advanced Studies Center in Mexico City, focusing on medical devices for breast cancer treatment. He later co-founded a tech consulting firm with projects spanning IoT applications to web app development in the health industry. In 2020, he joined Princeton Neuroscience Institute as a research and development engineering manager, designing and building setups for behavioral training and neural recordings. Now a Ph.D. candidate at the University of Pennsylvania, his research focuses on developing a wearable device to collect behavioral data from patients with Obsessive Compulsive Disorder.more