The implementation of digital biomarkers in the diagnosis, treatment and monitoring of mood disorders: a narrative review - Garzón-Partida, Andrea P.; Padilla-Gómez, Citlali B.; Martínez-Fernández, Diana Emilia; García-Estrada, Joaquín; Luquin, Sonia; Fernández-Quezada, David (Frontiers in Digital Health, 2025)
Mood Disorders are a group of mental health conditions characterized by a disruption of the emotional state that affects the quality of life of the people living with them. Mental Disorders are difficult to diagnose and treat due to the complex processes involved and limitations of the healthcare system. Digital biomarkers have created accessible, long-term, non-invasive, and user-friendly alternatives for the diagnosis, treatment, and monitoring of these conditions. The use of everyday devices like smartphones and smartwatches and specialized tools like actigraphy, in conjunction with powerful statistical tools, artificial intelligence, and machine learning, represents a promising avenue for the implementation of personalized strategies to monitor and treat Mood Disorders, and potentially higher adherence to treatment. We conducted several studies that implement a variety of methodologies and tools to better understand Mood Disorders, using a patient-focused approach with the ultimate goal of identifying better strategies to improve their quality of life.