AnDy suit: human weight lifting wearable data
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下载链接:
https://zenodo.org/record/5776189
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资源简介:
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:
Experiment 01
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.
Experiment 02
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
Data Structure
Data structure is the following:
- experiment0x
- wearable_data
- FTshoes
- xsens
- subject_model
Data Interpretation
Data have been collected using YARP datadumper tool using the thrift message implemented in wearables library.
Data Usage
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. Algorithms 2020, 13, 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. Sensors 2019, 19, 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. IEEE Access, pp. 1–1, Aug. 2021, https://ieeexplore.ieee.org/document/9526592.
创建时间:
2021-12-13



