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.