Digital Phenotyping

Digital Phenotyping for the early detection of mental health problems

Depression and other mental disorders have increased significantly in recent years. This has motivated interest in developing systems for the early detection of these mental disorders. Currently, the diagnosis of mental disorders and the monitoring of patients are mainly based on clinical assessments that involve completing surveys or face-to-face interviews. Unfortunately, these procedures are not scalable and diagnosis often does not occur until the patient’s condition is critical, at which point treatment will be less effective than if it had been carried out in earlier stages of the disorder.

The aim of this research is to study the use of Digital Phenotyping for the early detection of symptoms related to mental health disorders. The idea of digital phenotyping is to use Artificial Intelligence techniques to analyze data that can be passively captured by digital devices, such as mobile phones or smart watches, and automatically extract from this data information that has interest from a clinical point of view. 

PI: Agata Lapedriza Garcia

Research group: Artificial Intelligence for Human Well-being (AIWELL)

Institution: UOC eHealth Research Center

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