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OpenTrials
Completed

NCT Number: NCT07218263

AI Platform for Fatigue and Depression Detection

This study evaluates the accuracy of the Okaya AI platform in detecting fatigue and depression in cardiology patients, comparing its assessments to PHQ-9 and Fatigue Assessment Scale scores.

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Key information

Conditions

Depression Disorders Behavior Behavioral Symptoms Cardiovascular Depression Fatigue Fatigue Symptom Pathological Conditions, Signs and Symptoms Signs and Symptoms

Age range

18 year and older

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

Indiana University Health - Methodist Hospital, Indianapolis, Indiana, United States

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About this study

Patients frequently experience fatigue and depression, which are often underdiagnosed due to limitations in traditional screening tools. This study introduces the Okaya platform, a browser-based AI system that analyzes facial and vocal biomarkers collected during conversational check-ins. The platform uses computer vision and natural language processing to extract features such as eye contact, facial affect, pitch, volume, and speech patterns. These features are processed through regression models to generate a composite AI based score. The study aims to validate this score against PHQ-9 and FAS assessments. Participants will complete a single baseline check-in using the Okaya platform and complete standard questionnaires. No clinical interventions will be provided.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Patients referred to the cardiology clinic with acute or chronic issues, or hospitalized for acute cardiology issues will be enrolled.

Inclusion criteria

  • Age ≥18, English-speaking, able to consent

Exclusion criteria

  • Active substance use, nonverbal, cognitive disability, active suicidal/homicidal ideation
  • English is not primary language or requires a translator

Treatment and study plan

AI-enabled Okaya platform

Diagnostic Test

AI-based conversational assessment using facial and vocal features to evaluate fatigue and depression.

Primary outcomes

  1. Correlation between Okaya (AI based) score and PHQ-9

    Time frame: Baseline

    Regression analysis comparing Okaya scores to PHQ-9

  2. Correlation between Okaya (AI) based score and PHQ-9 and FAS

    Time frame: Baseline

    Regression analysis comparing Okaya scores to standard assessments

  3. Correlation between Okaya (AI based) score and FAS

    Time frame: Baseline

    Regression analysis comparing Okaya scores to FAS

Secondary outcomes

  1. Usability and patient satisfaction

    Time frame: Baseline

    Ease-of-use ratings on the Okaya platform

Sponsors and collaborators

Lead sponsor

Brijesh Patel

Other

Collaborators

  • SmartTec Inc

Registry information

Official study title

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

Important dates

Study start
2025
Primary completion
2026
Study completion
2026
First posted
Oct 20, 2025
Registry last updated
Aug 19, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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