Bibliographic Details
| Title: |
Precision analysis of kinect to measure the motion of the upper body and calibration based on deep learning. |
| Authors: |
Kyeong, Seulki1 (AUTHOR), Kim, Yundong2 (AUTHOR), Abunya, Philip2 (AUTHOR), Kang, Bong-Soo2 (AUTHOR) bskang@hnu.kr |
| Source: |
Journal of Mechanical Science & Technology. Jun2025, Vol. 39 Issue 6, p3539-3545. 7p. |
| Subjects: |
Motion capture (Cinematography), Measurement errors, Abduction (Kinesiology), Arm exercises, Deep learning, Shoulder exercises |
| Abstract: |
This study analyzed the characteristics of the Kinect sensor developed for video games as a motion capture device. In addition, a calibration method was developed using deep learning technique to improve the precision of the Kinect while maintaining its convenience: no marker, low cost, easy-to-install, etc. When the proposed calibration scheme was applied to four types of arm exercises for three subjects, measurement errors were reduced by 68 % for shoulder movements and 43 % for elbow movements. Also, the measurement precision for shoulder flexion and abduction was improved up to 4 degrees, which sufficiently satisfied the requirement of rehabilitation exercises for patients with frozen shoulder. [ABSTRACT FROM AUTHOR] |
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| Database: |
Engineering Source |