AnDy suit: human weight lifting wearable data

This dataset comprises wearable data, collected using An.Dy. suit, from two weight lifting experiments of a human subject. Wearable data include kinematic measurements acquired with the Xsens Motion Tracking system (composed by 17 IMUs) and iFeel shoes (force/torque sensorized shoes developed by Istituto Italiano di Tecnologia). The experimental design is the following: <strong>Experiment 01</strong> Lifting task Geometry, accordingly to NIOSH convention: H = 63 cm V = 30 cm D = 40 cm CM = 0.9 Load = 7 kg The task is executed 10 times. <strong>Experiment 02</strong> Lifting task Geometry, accordingly to NIOSH convention: H = 31 cm V = 66 cm D = 42 cm CM = 1 Load = 5 kg The task has been executed: 5 minutes: Lifting with back only 5 minutes: Lifting with back plus leg <strong>Data Structure</strong> Data structure is the following: - experiment0x - wearable_data - FTshoes - xsens - subject_model <strong>Data Interpretation</strong> Data have been collected using YARP datadumper tool using the thrift message implemented in wearables library. <strong>Data Usage</strong> Data can be used by human-dynamics-estimation devices for replicating the results presented in: Rapetti, L.; Tirupachuri, Y.; Darvish, K.; Dafarra, S.; Nava, G.; Latella, C.; Pucci, D. Model-Based Real-Time Motion Tracking Using Dynamical Inverse Kinematics. <em>Algorithms</em> 2020, <em>13</em>, 266. https://doi.org/10.3390/a13100266 Latella, C.; Traversaro, S.; Ferigo, D.; Tirupachuri, Y.; Rapetti, L.; Andrade Chavez, F.J.; Nori, F.; Pucci, D. Simultaneous Floating-Base Estimation of Human Kinematics and Joint Torques. <em>Sensors</em> 2019, <em>19</em>, 2794. https://doi.org/10.3390/s19122794 Tirupachuri, Y. ; Ramadoss, P. ; Rapetti, L. ; Latella, C. ; Darvish, K. ; Traversaro, S. ; Pucci D. Online Non- Collocated Estimation of Payload and Articular Stress for Real-Time Human Ergonomy Assessment. <em>IEEE Access</em>, <em>pp. 1–1, Aug. </em>2021, https://ieeexplore.ieee.org/document/9526592.本数据集包含通过An.Dy.套装采集的可穿戴传感数据，源自一名人类受试者的两次举重实验。可穿戴数据涵盖由Xsens运动捕捉系统（由17个惯性测量单元（IMU）组成）以及iFeel智能鞋（意大利理工学院（Istituto Italiano di Tecnologia）研发的力/扭矩传感鞋）采集的运动学测量数据。 实验设计如下： <strong>实验01</strong> 遵循美国国家职业安全与健康研究所（NIOSH）规程的举重任务参数：H=63cm，V=30cm，D=40cm，CM=0.9，负载=7kg，该任务重复执行10次。 <strong>实验02</strong> 遵循NIOSH规程的举重任务参数：H=31cm，V=66cm，D=42cm，CM=1，负载=5kg。该实验分为两个阶段： - 5分钟：仅依靠背部发力举重 - 5分钟：依靠背部与腿部协同发力举重 <strong>数据结构</strong> 数据结构如下： - experiment0x - wearable_data - FTshoes - xsens - subject_model <strong>数据解读</strong> 本数据集通过YARP数据转储工具，结合可穿戴库中实现的Thrift消息格式完成采集。 <strong>数据用途</strong> 本数据集可用于人体动力学估计设备，以复现以下已发表研究成果： 1. Rapetti, L.; Tirupachuri, Y.; Darvish, K.; Dafarra, S.; Nava, G.; Latella, C.; Pucci, D. 基于模型的实时运动跟踪：动态逆运动学算法的应用[J]. 算法, 2020, 13, 266. https://doi.org/10.3390/a13100266 2. Latella, C.; Traversaro, S.; Ferigo, D.; Tirupachuri, Y.; Rapetti, L.; Andrade Chavez, F.J.; Nori, F.; Pucci, D. 人体运动学与关节力矩的浮动基座联合估计[J]. 传感器, 2019, 19, 2794. https://doi.org/10.3390/s19122794 3. Tirupachuri, Y.; Ramadoss, P.; Rapetti, L.; Latella, C.; Darvish, K.; Traversaro, S.; Pucci D. 面向实时人体工效学评估的负载与关节应力在线非接触估计[J]. IEEE Access, 2021年8月, pp.1-1. https://ieeexplore.ieee.org/document/9526592.