title: Consistent accuracy in whole-body joint kinetics during gait using wearable inertial motion sensors and in-shoe pressure sensors.
abstract: To analyze human motion such as daily activities or sports outside of the laboratory, wearable motion analysis systems have been recently developed. In this study, the joint forces and moments in whole-body joints during gait were evaluated using a wearable motion analysis system consisting of an inertial motion measurement system and an in-shoe pressure sensor system. The magnitudes of the joint forces and the moments in nine joints (cervical, thoracic, lumbar, right shoulder, right elbow, right wrist, right hip, right knee, and right ankle) during gait were calculated using the wearable system and the conventional system, respectively, based on a standard inverse dynamics analysis. The averaged magnitudes of the joint forces and moments of five subjects were compared between the wearable and conventional systems in terms of the Pearson's correlation coefficient and the normalized root mean squared error to the maximum value from the conventional system. The results indicated that both the joint forces and joint moments in human whole body joints using wearable inertial motion sensors and in-shoe pressure sensors were feasible for normal motions with a low speed such as walking, although the lower extremity joints showed the strongest correlation and overall the joint moments were associated with relatively smaller correlation coefficients and larger normalized root mean squared errors in comparison with the joint forces. The portability and mobility of this wearable system can provide wide applicability in both clinical and sports motion analyses.
authors.affiliation: Department of Mechanical Engineering, Kyung Hee University, Yongin, Republic of Korea.
authors.forename: Tsolmonbaatar
authors.initials: T
authors.lastname: Khurelbaatar
authors.affiliation: Department of Applied Mathematics, Kyung Hee University, Yongin, Republic of Korea.
authors.forename: Kyungsoo
authors.initials: K
authors.lastname: Kim
authors.affiliation: Department of Computer Science, Yonsei University, Seoul, Republic of Korea.
authors.forename: SuKyoung
authors.initials: S
authors.lastname: Lee
authors.affiliation: Department of Mechanical Engineering, Kyung Hee University, Yongin, Republic of Korea. Electronic address: yoonhkim@khu.ac.kr.
authors.forename: Yoon Hyuk
authors.initials: YH
authors.lastname: Kim
mesh_terms: D000054:Acceleration; D000328:Adult; D053587:Arthrometry, Articular / Q000295:instrumentation*; D001696:Biomechanical Phenomena / Q000502:physiology; D004867:Equipment Design; D005240:Feasibility Studies; D005684:Gait / Q000502:physiology*; D006801:Humans; D007596:Joints / Q000502:physiology*; D007700:Kinetics; D008297:Male; D018670:Monitoring, Ambulatory / Q000295:instrumentation*; D004856:Postural Balance / Q000502:physiology*; D012815:Signal Processing, Computer-Assisted / Q000295:instrumentation; D012984:Software; D013223:Statistics as Topic; D016474:Weight-Bearing / Q000502:physiology*
keywords: Biomechanics; Gait; In-shoe pressure sensor; Inertial motion sensor; Joint kinetics