ZenZone: AI-Powered Peace of Mind
summary
A prototype web app uses text, voice and facial cues to flag early depression, integrating an LLM comfort bot (Llama 2 tested), facial emotion features from DeepFace and a Bashin translation layer with Azure PostgreSQL for health-record linking. The system reports 91% empathetic accuracy on conversational responses but so far runs on a five-sample prototype, produces dashboarded mood reports, and routes high-risk users to human therapists while noting privacy and safety limits.
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chapters (8)
- 0:00AI in mental health
- 1:54Mental health access challenges
- 3:40Early detection methods
- 5:27Prototype tech stack
- 7:39Emotion detection bot
- 9:26Data security and privacy
- 10:29AI as virtual psychologist
- 11:31Q&A: Safeguards
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