An Ambient Intelligent Agent for Relapse and Recurrence Monitoring in Unipolar Depression

Mental healthcare is a prospective area for applying AI techniques. For example, a computerized system could support individuals with a history of depression in maintaining their well-being throughout their lifetime. In this paper, the design of an ambient intelligent agent to support these individuals is presented. It incorporates an analysis and support model for diagnostics based on observed features and for suggested actions. The model used is based on dynamic relations that describe the occurrence of relapse in unipolar depression. By incorporating this model into an ambient agent system, the agent is able to reason about the state of the human and the effect of possible actions. Several simulation experiments have been conducted to illustrate the functioning of the proposed model in different scenarios.