804402
doi
10.3390/s17061257
oai:zenodo.org:804402
user-ieee
Ruffaldi, Emanuele
Scuola Superiore Sant'Anna
Dataset of Survey of Motion Tracking Methods Based on Inertial Sensors: A Focus on Upper Limb Human Motion
Filippeschi, Alessandro
Scuola Superiore Sant'Anna
doi:10.3390/s17061257
info:eu-repo/semantics/openAccess
Creative Commons Attribution Share Alike 4.0 International
https://creativecommons.org/licenses/by-sa/4.0/legalcode
imu
inertial
human motion
<p>MATLAB Dataset for the paper. </p>
<p>Paper Abstract:</p>
<p>Motion tracking based on commercial inertial measurements units (IMUs) has been widely studied in the latter years as it is a cost-effective enabling technology for those applications in which motion tracking based on optical technologies is unsuitable. This measurement method has a high impact in human performance assessment and human-robot interaction. IMU motion tracking systems are indeed self-contained and wearable, allowing for long-lasting tracking of the user motion in situated environments. After a survey on IMU-based human tracking, five techniques for motion reconstruction were selected and compared to reconstruct a human arm motion. IMU based estimation was matched against motion tracking based on the Vicon marker-based motion tracking system considered as ground truth. Results show that all but one of the selected models perform similarly (about 35 mm average position estimation error).</p>
https://github.com/eruffaldi/imu_comparison_data
Zenodo
2017-06-01
info:eu-repo/semantics/other
804401
user-ieee
1579893904.196204
75404751
md5:827541a85f6ca92474846dcb4ed0d98a
https://zenodo.org/records/804402/files/zenodo.zip
public
10.3390/s17061257
Is supplement to
doi
Sensors
17
6
2017-06-01