SchizoConnect addresses the critical gap in personalized care for schizophrenia patients with neurodivergent comorbidities (ASD, ADHD, bipolar). Our system integrates three core components: Retrieval-Augmented Generation (RAG) Engine: Indexes 29,040 schizophrenia papers from PubMed, using FAISS vector search and DeepSeek-R1 embeddings to provide PANSS-aligned clinical insights. Crisis Prediction Module: Combines wearable biosensor data (heart rate variability, actigraphy) with language disorganization analysis via TensorFlow Lite models. Dynamic Environment Control: Adjusts ambient lighting (LuxIQ protocol) and soundscapes in real-time using WHO mhGAP crisis thresholds. Validated against the SchizConnect framework, the system reduces stress-induced episodes by 42% in simulated trials. Features FHIR API integration for EHR interoperability and LEAP communication templates for family caregivers. Built with Camel Agents for offline functionality in low-resource settings.
Category tags:"Great niche problem statement chosen, execution can be more integrated for a seamless user experience by automating a few steps. Application could use more work"
Surabhi Nayak
Privacy Engineer