지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2023.8
- 수록면
- 331 - 344 (14page)
- DOI
- 10.5143/JESK.2023.42.4.331
이용수
초록· 키워드
오류제보하기
Objective: The purpose of this study is to compare two different motion capture systems based on wrist motion measurements. The measurement equipment compared in this study are motion capture systems using electronic goniometer and IMU (Inertial Measurement Units).
Background: Electronic goniometers (EGs) have been widely used in various task situations to measure human body motion without significantly interfering with the subject"s real activity, especially for measuring wrist motion. Recently, IMU-based motion capture systems (IMCs) are preferred for measuring human body movements in real-world environments. This is because the sensor is relatively small and the system typically operates wirelessly. Although several studies have validated the use of electronic goniometers, few studies have validated IMU-based systems in wrist motion measurement, especially compared to electronic goniometers. When evaluating human motion using these measurement systems, it is helpful to understand the characteristics of the various motion capture systems.
Method: A laboratory experiment was carried out with 10 male college students. Subjects wore an electronic goniometer and an IMC on their right wrist. Wrist flexion/extension and ulnar/radial deviation angles were measured in neutral, intermediate and extreme static postures. Subjects were asked to move their right wrist as desired at three given speeds: 50, 100, and 150bpm. Finally, they were asked to perform the simple task of assembling knots for 3min. While the subject moved his right wrist, joint angles were measured simultaneously with an electronic goniometer and IMC. Joint angles in static postures were measured with a manual goniometer and used as reference values for the joint angles. The absolute values of error, MDF, 10%, 50%, and 90% APDF of joint angles, angular velocity, and angular acceleration were calculated. Analyses of variance (ANOVAs) were applied to find significant effects of equipment on wrist motion measurements.
Results: For static postures, IMC showed a lower value of absolute error than EG and the error in flexion/extension was higher than the error in deviation (p<0.05). The measurement errors showed higher values as the joint angle increased. EG showed higher errors than IMC in extension and ulnar deviation, while the errors of two equipment showed similar values in other positions. The errors of EG seemed to be related to the cross-talk effect of 2D goniometers, since the extension and ulnar deviation of wrists are closely related. For different speeds of wrist motions, it was found that two equipment showed similar values of MDFs, while the difference between two equipment increased as the motion speed increased. For simulated repetitive manual tasks, similar performances of measurement were found in the two equipment.
Conclusion: It was found that EG and IMC showed similar performances of measurement of wrist motion, while the error of measurement by EG is relatively large in severe extension and ulnar deviation of the wrist as compared to IMC. In normal working tasks, two equipment showed similar performance of measurement. For future study, it needs to measure the joint angles using other validated method, so that the frequency, angular velocity, and angular acceleration can be verified with respect to the golden values.
Application: The results of this study can be used in the studies of ergonomics to measure the human body motion for the purpose of work evaluation or product usability evaluation.
Background: Electronic goniometers (EGs) have been widely used in various task situations to measure human body motion without significantly interfering with the subject"s real activity, especially for measuring wrist motion. Recently, IMU-based motion capture systems (IMCs) are preferred for measuring human body movements in real-world environments. This is because the sensor is relatively small and the system typically operates wirelessly. Although several studies have validated the use of electronic goniometers, few studies have validated IMU-based systems in wrist motion measurement, especially compared to electronic goniometers. When evaluating human motion using these measurement systems, it is helpful to understand the characteristics of the various motion capture systems.
Method: A laboratory experiment was carried out with 10 male college students. Subjects wore an electronic goniometer and an IMC on their right wrist. Wrist flexion/extension and ulnar/radial deviation angles were measured in neutral, intermediate and extreme static postures. Subjects were asked to move their right wrist as desired at three given speeds: 50, 100, and 150bpm. Finally, they were asked to perform the simple task of assembling knots for 3min. While the subject moved his right wrist, joint angles were measured simultaneously with an electronic goniometer and IMC. Joint angles in static postures were measured with a manual goniometer and used as reference values for the joint angles. The absolute values of error, MDF, 10%, 50%, and 90% APDF of joint angles, angular velocity, and angular acceleration were calculated. Analyses of variance (ANOVAs) were applied to find significant effects of equipment on wrist motion measurements.
Results: For static postures, IMC showed a lower value of absolute error than EG and the error in flexion/extension was higher than the error in deviation (p<0.05). The measurement errors showed higher values as the joint angle increased. EG showed higher errors than IMC in extension and ulnar deviation, while the errors of two equipment showed similar values in other positions. The errors of EG seemed to be related to the cross-talk effect of 2D goniometers, since the extension and ulnar deviation of wrists are closely related. For different speeds of wrist motions, it was found that two equipment showed similar values of MDFs, while the difference between two equipment increased as the motion speed increased. For simulated repetitive manual tasks, similar performances of measurement were found in the two equipment.
Conclusion: It was found that EG and IMC showed similar performances of measurement of wrist motion, while the error of measurement by EG is relatively large in severe extension and ulnar deviation of the wrist as compared to IMC. In normal working tasks, two equipment showed similar performance of measurement. For future study, it needs to measure the joint angles using other validated method, so that the frequency, angular velocity, and angular acceleration can be verified with respect to the golden values.
Application: The results of this study can be used in the studies of ergonomics to measure the human body motion for the purpose of work evaluation or product usability evaluation.
목차
1. Introduction
2. Method
3. Results
4. Discussion
5. Conclusion
References
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