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:

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.