GaitMoText: A Multimodal Dataset for Clinical Gait Analysis compromising Optical Motion Capture and Textual Gait Analyses from Patients undergoing Total Knee Arthroplasty

GaitMoText is a multimodal dataset designed to advance automated clinical gait analysis by combining high-quality motion capture data with expert textual gait assessments. The dataset contains recordings from 23 patients undergoing total knee arthroplasty (TKA), collected both pre-operatively and six weeks post-operatively during a standardized 6-minute walking test (6MWT). Motion data was captured using the SIMI Motion markerless system and is provided in multiple representations, including 3D keypoint trajectories, joint angle time series, and SMPL-based motion parameters. In addition to quantitative motion data, the dataset includes rich qualitative annotations in the form of clinical gait assessments. Each recording session is annotated by multiple expert physiotherapists, resulting in detailed textual descriptions of gait abnormalities and compensatory mechanisms. The annotations are available in both German and English. This dataset enables research at the intersection of biomechanics, computer vision, and natural language processing, supporting tasks such as automatic gait assessment, anomaly detection, rehabilitation monitoring, and multimodal motion understanding. The dataset is fully anonymized and contains only privacy-preserving skeletal and parametric representations. Raw video data is not included. For more details, please refer to the associated publication.GaitMoText是一款多模态数据集，旨在通过结合高质量运动捕捉数据与专家文本步态评估，推动自动化临床步态分析领域的发展。 该数据集涵盖23名接受全膝关节置换术（total knee arthroplasty, TKA）患者的步态记录数据，采集时段分别为术前与术后六周的标准化6分钟步行试验（6-minute walking test, 6MWT）。运动数据采用SIMI Motion无标记捕捉系统采集，并以多种表征形式提供，包括三维关键点轨迹、关节角度时间序列以及基于SMPL的运动参数。 除定量运动数据外，本数据集还包含形式为临床步态评估的丰富定性注释。每一次记录会话均由多名专业物理治疗师进行标注，最终生成关于步态异常与代偿机制的详细文本描述。上述注释同时提供德语与英语两种版本。 本数据集可支撑生物力学、计算机视觉与自然语言处理交叉领域的研究，可助力自动步态评估、异常检测、康复监测及多模态运动理解等相关任务。 该数据集已完成完全匿名化处理，仅包含保护隐私的骨骼与参数化表征形式，不包含原始视频数据。 如需了解更多细节，请参阅相关发表文献。