Data From Wearables Could Be A Boon To Mental Health Diagnosis

Researchers at Washington University in St. Louis have developed a deep-learning model called WearNet to detect depression and anxiety using data collected by a Fitbit activity tracker. WearNet was able to detect depression and anxiety better than state-of-the-art machine learning models, and produced individual-level predictions of mental health outcomes. The next step is to convince a hospital system or company to implement the model.