Kinect v2 skeleton datasets of simulated abnormal gaits

Citation Author(s):
Kooksung
Jun
Gwangju Institute of Science and Technology
Yongwoo
Lee
Gwangju Institute of Science and Technology
Sanghyub
Lee
Gwangju Institute of Science and Technology
Deok-Won
Lee
Gwangju Institute of Science and Technology
Mun Sang
Kim
Gwangju Institute of Science and Technology
Submitted by:
Kooksung Jun
Last updated:
Mon, 10/18/2021 - 04:43
DOI:
10.21227/21wx-kh75
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Abstract 

Skeleton datasets for Normal, Antalgic, Stiff legged, Lurching, Steppage, and Trendelenburg gaits.

Instructions: 

Data Quantity

10 people x 6 gaits x 120 instances

Data Form

time, 0, joint0_x, joint0_y, joint0_z, 1, joint1_x, joint1_y, joint1_z, ... , joint24_x, joint24_y, joint24_z

The joint numbers can be found in Reference.

Data Collection

We collected datasets by using multiple Kinect system (6 Kinect v2). We calibrated the coordinate systems of all sensors by using ArUco markers. For more information, please refer to the below reference or contact me.

Reference

K. Jun, Y. Lee, S. Lee, D. Lee and M. S. Kim, "Pathological Gait Classification Using Kinect v2 and Gated Recurrent Neural Networks," in IEEE Access, vol. 8, pp. 139881-139891, 2020, doi: 10.1109/ACCESS.2020.3013029.

Contact

kooksung930@gm.gist.ac.kr