Background

Osteoarthritis (OA) is one of the most common musculoskeletal disorders affecting elderly individuals and physically active populations, leading to chronic pain, joint stiffness, mobility issues, and reduced quality of life. In the North Eastern Region (NER), difficult terrain, physically demanding livelihoods, aging population, and limited access to specialized orthopaedic care further increase the burden of undiagnosed and untreated osteoarthritis cases. Early identification of OA risk markers is critical for timely intervention and preventive healthcare management. However, healthcare facilities in many remote and rural areas of NER lack affordable screening tools, specialist support, and diagnostic infrastructure for early-stage detection of osteoarthritis. There is a need for a technology-driven solution that can assist healthcare workers in identifying early OA indicators and supporting preventive screening in low-resource settings across the North Eastern Region.

Description

This problem statement seeks to develop an AI-assisted screening and detection system for identifying early risk markers and symptoms associated with Osteoarthritis (OA) in the North Eastern Region. The solution should

Expected Solution

A scalable Al-enabled healthcare screening solution with: Al-based OA risk analysis and screening module Portable assessment interface or sensor-assisted screening mechanism Digital patient record and report generation system Mobile/web-based healthcare worker interface Offline synchronization capability for remote areas Multilingual support and simplified workflow for field deployment Secure patient data management and analytics dashboard The solution should support early diagnosis, preventive healthcare intervention, and improved accessibility to musculoskeletal healthcare services in the North Eastern Region.

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