The e-Prevention Challenge provided participants with an extensive dataset of continuous recordings from wearable sensors like accelerometers, gyroscopes, and heart rate monitors, along with supplementary data such as sleep patterns, daily step counts, and demographics. Participants were tasked with developing innovative algorithms to analyze this multimodal data for early signs of potential mental health relapses.
About the e-Prevention Project
The e-Prevention project aims to develop an integrated digital phenotyping system leveraging wearable biosensors and AI techniques to facilitate effective monitoring and relapse prevention for patients with mental disorders. More details are available at: https://robotics.ntua.gr/icassp2024-eprevention-spgc/