Efficacy of a Novel Web-based Fatigue and Cognitive Assessment Platform in Detecting Fatigue and Depression

What this Trial Is About

This observational study evaluates the accuracy of the Okaya AI platform in detecting fatigue and depression among cardiology patients. It compares the platform's assessments to standard screening tools like the PHQ-9 and Fatigue Assessment Scale (FAS). The study aims to address underdiagnosis of these symptoms by using advanced technology to analyze facial and vocal biomarkers during conversations. Participants will complete a single baseline check-in using the Okaya platform, which collects facial expressions, eye contact, speech pitch, volume, and patterns. These features are processed by computer vision and natural language processing to create an AI-based score that reflects fatigue and depression levels. Participants also complete the PHQ-9 and FAS questionnaires for comparison. No treatments or interventions are provided. During the study visit, participants undergo the Okaya assessment and complete the PHQ-9 and FAS questionnaires. Researchers will measure how well the AI-based score correlates with the traditional assessments and evaluate the usability and patient satisfaction with the platform. The study involves a one-time visit and concludes with analysis of baseline data. The total duration of participation is limited to this single assessment.

AI Platform for Fatigue and Depression Detection