A Standardized Benchmark for Skeleton-Based Rehabilitation Assessment Using Deep Learning

SignBart is an efficient Isolated Sign Language Recognition model that decouples x and y coordinates using a lightweight encoder-decoder architecture. It achieves high accuracy with fewer than 750K parameters, outperforming traditional models on datasets like LSA-64, WLASL, and ASL-Citizen.