Low-Cost OA Assessment: CNN-Based Integration of Knee Sounds and Patient-Reported Measures

Osteoarthritis (OA) remains a leading cause of disability worldwide, with significant socioeconomic impact.Current diagnostic methods rely heavily on radiological imaging and clinical assessment, which are costly, resource-intensive, and often limited in accessibility.This paper presents a low-cost, highimpact diagnostic framework that fuses knee acoustic emissions (KAE) with patient-reported measures (PRM) using convolutional neural networks (CNNs).