DavidRobinson05/strokevision-bench

StrokeVision-Bench是一个针对中风患者进行动作识别的数据集，包含1000个标注视频（每个1秒，30帧/秒），分为四个具有临床意义的动作类别：非任务动作、抓握、带积木的运输、不带积木的运输。每个样本以两种模态表示：原始视频片段和2D骨骼关键点。该数据集提供了多种最先进的视频和基于骨骼的动作分类方法的基准测试，以建立该领域的性能基线，并促进自动化中风康复评估的未来研究。

StrokeVision-Bench is an action recognition dataset of short segments of stroke patients performing the Box-Block Test, containing 1,000 annotated videos (1 s @ 30 FPS) categorized into four clinically meaningful action classes: Non-task movement, Grasping, Transport with block, Transport without block. Each sample is represented in two modalities: raw video segments and 2D skeletal keypoints. The dataset provides benchmarking for several state-of-the-art video and skeleton-based action classification methods to establish performance baselines for this domain and to facilitate future research in automated stroke rehabilitation assessment.