MUMBAI, India, Aug. 17 -- Intellectual Property India has published a patent application (202641090095 A) filed by Meenakshi Sundararajan Engineering College on July 24, 2026, for Memory Lane: An Ai-Integrated Multi-Role Platform For Tbi And Alzheimer'S Care Management.
Inventors include Swathy K; Vinothini S; Venugopal. M; Priyadarshini I; Ragavi Sree B; Padma M; and Vijay B S.
The application for the patent was published on August 14, 2026, under issue no. 33/2026.
Abstract: Traumatic Brain Injury (TBI) and Alzheimer's disease present significant challenges in continuity of care, requiring coordinated effort between patients, caregivers, and clinicians who currently operate with fragmented, single-stakeholder digital tools and limited shared clinical visibility into disease progression. This invention presents Memory Lane — a full-stack, AI-assisted, role-based digital health progressive web application built on React 19Nite 7 (frontend), Expressjs (REST API backend with 16 endpoints), and Firebase v12.11.0 (Firestore, Authentication The platform implements three distinct stakeholder interfaces sharing a unified Firebase Firestore data backbone across four collections (users, patients, sessions, recommendations) with dual-mode cloud/in-memory fallback operation. The Doctor Dashboard provides patient management with injury-type classification (TBI / Concussion / Head Injury), risk level stratification (High / Medium / Low with color coding), full clinical data ;views, Recharts-powered weekly memory trend line charts and task completion bar charts, critical alert panels, Al recommendations, and aggregate KPI monitoring. The Caregiver Dashboard delivers a five-stage guided workflow: injury-type selection, seven-indicator symptom logging, AT therapy plan generation, multi-step guided session execution with timestamp tracking, and a fivetask daily care checklist with scheduled times. Server-side analytics (build Analytics) compute average memory score, average adherence, session counts, and alert counts per patient from session data, exposed via REST API and visualized as real-time Recharts charts. Firebase Authentication provides role-based login; a client-side local database (localStorage key: memory-lane-local-db-v2) ensures fully functional offline operation with seeded demo data. A bilingual English/Tamil interface extends regional accessibility across South India. A companion Codex module integrating Anthropic Claude and OpenAI SDKs provides extensible Al tooling within the platform ecosystem. Repository: github.com/m-venu-24/memory-lane-1. By unifying therapy delivery, caregiver coordination, and clinical monitoring under a single authenticated platform, Memory Lane bridges all five critical gaps in current cognitive care tools and contributes a scalable, production-deployable framework for AI-integrated neurological care management. Keywords: Traumatic Brain Injury, Alzheimer's Disease, React 19, Vite 7, Express.js, Firebase Firestore, Firebase Authentication, Recharts, Role-Based Architecture, Care Coordination, Dual-Mode Backend, REST API, Vercel Deployment, Bilingual Interface (EN/TA), AI-Assisted Therapy, Digital Health Platform
Disclaimer: Curated by HT Syndication.
