E-Prevention: Advanced Support System for Monitoring and Relapse Prevention in Patients with Psychotic Disorders...

Area of Science:

• Digital Health
• Psychiatry
• Machine Learning

Background:

• Wearable technologies and digital phenotyping offer new ways to support mental health.
• Current practices can be enhanced by intelligent electronic services for conditions like schizophrenia and bipolar disorder.

Purpose of the Study:

• To present e-Prevention, an integrated system for monitoring and relapse prevention in mental health patients.
• To describe methodologies for identifying features predicting psychopathology and relapses.

Main Methods:

• Utilizing a smartwatch for continuous biometric and behavioral data collection.
• Employing tablet-based video recordings during clinical interviews.
• Storing data on a cloud server for analysis.
• Applying Machine and Deep Learning techniques for relapse detection and prediction.

Main Results:

• The e-Prevention system demonstrates promising results in detecting and predicting relapses.
• Identified feature representations correlate with psychopathology.
• The system has the potential for early intervention and relapse prevention.

Conclusions:

• The e-Prevention system shows potential to revolutionize psychiatric clinical practice.
• AI-driven analysis of digital data can lead to improved patient outcomes.
• This technology facilitates proactive mental healthcare and relapse prevention.