ROAG (Reaching Over A Grid): Dataset of Human Reaching Motions Over a Discretely Sampled Workspace

Joint absence in people with upper limb differences leads to compensatory motions. Such compensation has long been a topic of study, but typically only for a single object/user layout, which is unlikely to generalise across a workspace.To better understand how arm motion and compensatory movements vary over the workspace, we created the ROAG dataset. ROAG is pronounced 'Rogue' and stands for Reaching Over A Grid. The dataset was recorded at the GRAB Lab of Yale University (USA) and has since been processed at the Manipulation and Touch Lab of Imperial College London (UK). ROAG is a motion capture dataset involving arm and torso pose during reach-to-grasp actions for 49 equally spaced cylindrical targets, orientated horizontally or vertically. The data is collected from seven able-bodied participants and two transradial amputees who use prosthetic devices. In the case of able-bodied participants, different bracing systems were applied to the arm to immobilise wrist joints and simulate transradial limb loss, leading to compensatory motions. In total, the dataset consists of 2450 reaching trajectories. This resource hosts the collected dataset and the related MATLAB analysis files.The dataset has been the basis of the following publications: A. J. Spiers, Y. Gloumakov and A. M. Dollar, "Transradial Amputee Reaching: Compensatory Motion Quantification Versus Unaffected Individuals Including Bracing," in IEEE Transactions on Medical Robotics and Bionics, vol. 6, no. 2, pp. 706-717, May 2024, https://doi.org/10.1109/TMRB.2024.3381339 Qihan Yang, Yuri Gloumakov, and Adam J. Spiers. "Multi-feature Compensatory Motion Analysis for Reaching Motions Over a Discretely Sampled Workspace." in IEEE RAS EMBS 10th International Conference on Biomedical Robotics and Biomechatronics (BioRob 2024), https://doi.org/10.48550/arXiv.2409.05871 Adam J Spiers, Yuri Gloumakov, Aaron M Dollar, "Examining the impact of wrist mobility on reaching motion compensation across a discretely sampled workspace", in IEEE 7th International Conference on Biomedical Robotics and Biomechatronics (BioRob 2018), https://doi.org/10.1109/BIOROB.2018.8487871上肢存在功能差异的人群因关节协同运动缺失，会产生代偿性动作。长期以来，这类代偿动作一直是研究热点，但既往研究通常仅针对单一的任务对象/使用者布局展开，难以推广至完整工作空间。为更深入地探究手臂运动与代偿动作在工作空间中的变化规律，我们构建了ROAG数据集。ROAG发音近似英文单词“Rogue”，全称为“网格间伸手抓取（Reaching Over A Grid）”。该数据集于美国耶鲁大学GRAB实验室录制，后续在英国帝国理工学院操纵与触觉实验室完成数据处理。ROAG是一款动作捕捉（motion capture）数据集，记录了受试者在完成49个等间距分布的水平/垂直定向圆柱形目标的伸手抓取（reach-to-grasp）动作时，手臂与躯干的姿态数据。数据采集自7名健康受试者与2名佩戴假肢的经桡骨截肢受试者。针对健康受试者，我们采用不同的制动支具系统固定其腕关节，以模拟经桡骨肢体缺失的状态，进而诱导代偿动作产生。本数据集总计包含2450条抓取轨迹。本资源收录了采集得到的原始数据集与相关MATLAB分析文件。本数据集已支撑以下学术成果发表： A. J. Spiers、Y. Gloumakov与A. M. Dollar，《经桡骨截肢者伸手抓取动作：制动条件下代偿运动量化分析与健康个体的对比》，发表于《IEEE医学机器人与仿生学汇刊》，2024年5月，第6卷第2期，第706-717页，DOI: 10.1109/TMRB.2024.3381339 Qihan Yang、Yuri Gloumakov与Adam J. Spiers，《离散采样工作空间内伸手抓取动作的多特征代偿运动分析》，发表于IEEE机器人与自动化学会（RAS）、工程医学与生物学学会（EMBS）联合主办的第10届生物医学机器人与生物机电一体化国际会议（BioRob 2024），DOI: 10.48550/arXiv.2409.05871 Adam J Spiers、Yuri Gloumakov与Aaron M Dollar，《探究腕关节活动度对离散采样工作空间内伸手抓取代偿运动的影响》，发表于IEEE第7届生物医学机器人与生物机电一体化国际会议（BioRob 2018），DOI: 10.1109/BIOROB.2018.8487871