Abstract
Personal Health Systems: The Help4Mood Project
In the last issues, we discussed the role of personal health systems in offering therapists significant new abilities to monitor patients' conditions, thereby enabling them to diagnose problems earlier and treat them more effectively. The EU is supporting research in this area under the Seventh Framework Programme (FP7—
Coordinator: Dr. Albert Vidal
I2Cat Fundaciao
E-mail:
Tel: +34 935 532 517
The problem
Major depression affects between 5% and 10% of the population in Western Europe. Studies have shown that in 28 countries (comprising a population of 466 million), 21 million were affected by depression, representing an estimated cost of 118 billion euros in 2004, or 253 euros per inhabitant. The effect of major depression on sufferers' quality of life and morbidity is similar to the effects of chronic diseases like hypertension, rheumatoid arthritis, and diabetes. Moreover, the World Health Organization reports suicide to be among the top 10 causes of death worldwide, with the lifetime risk of suicide in people with mood disorders (mainly depression) estimated to be 6–15%.
Goals of the project
The main aim of the Help4Mood project is to provide a closed-loop approach supporting the control, communication, and treatment management of patients with major depression. Specifically, the project proposes to advance significantly the state of the art in computerized support for people with major depression by monitoring mood, thoughts, physical activity, and voice characteristics, prompting adherence and promoting behaviors in response to monitored inputs.
The technology
This approach will be a distributed system with three main components (the personal monitoring system, the virtual agent component, and the DSS for treatment management) deployed in both places: at the patient's site and at the clinician sites. The virtual agent (VA) will interact with the patient through a combination of enriched prompts, dialogue, body movements, and facial expressions. Monitoring will combine existing (movement sensor, psychological ratings) and novel (voice analysis) technologies as inputs to a pattern-recognition-based decision support system for treatment management.
Expected outcomes
The advances in Help4Mood will provide a closed-loop approach to treatment support for MD patients. Outputs include a validated personal monitoring system, a personal interaction system embodied in a VA, and a clinical decision support module. By identifying and supporting patients with delayed recovery, Help4Mood has the potential to target added support for patients most in need and lead to their earlier return to normal health and social and economic activity.