Construction of upper body motion measurement model using inertial sensors

Author(s):  
Shinya UEDA ◽  
Akihito ITO ◽  
Nobutaka TSUJIUCHI ◽  
Keisuke KITANO
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Ramon J. Boekesteijn ◽  
José M. H. Smolders ◽  
Vincent J. J. F. Busch ◽  
Alexander C. H. Geurts ◽  
Katrijn Smulders

Abstract Background Although it is well-established that osteoarthritis (OA) impairs daily-life gait, objective gait assessments are not part of routine clinical evaluation. Wearable inertial sensors provide an easily accessible and fast way to routinely evaluate gait quality in clinical settings. However, during these assessments, more complex and meaningful aspects of daily-life gait, including turning, dual-task performance, and upper body motion, are often overlooked. The aim of this study was therefore to investigate turning, dual-task performance, and upper body motion in individuals with knee or hip OA in addition to more commonly assessed spatiotemporal gait parameters using wearable sensors. Methods Gait was compared between individuals with unilateral knee (n = 25) or hip OA (n = 26) scheduled for joint replacement, and healthy controls (n = 27). For 2 min, participants walked back and forth along a 6-m trajectory making 180° turns, with and without a secondary cognitive task. Gait parameters were collected using 4 inertial measurement units on the feet and trunk. To test if dual-task gait, turning, and upper body motion had added value above spatiotemporal parameters, a factor analysis was conducted. Effect sizes were computed as standardized mean difference between OA groups and healthy controls to identify parameters from these gait domains that were sensitive to knee or hip OA. Results Four independent domains of gait were obtained: speed-spatial, speed-temporal, dual-task cost, and upper body motion. Turning parameters constituted a gait domain together with cadence. From the domains that were obtained, stride length (speed-spatial) and cadence (speed-temporal) had the strongest effect sizes for both knee and hip OA. Upper body motion (lumbar sagittal range of motion), showed a strong effect size when comparing hip OA with healthy controls. Parameters reflecting dual-task cost were not sensitive to knee or hip OA. Conclusions Besides more commonly reported spatiotemporal parameters, only upper body motion provided non-redundant and sensitive parameters representing gait adaptations in individuals with hip OA. Turning parameters were sensitive to knee and hip OA, but were not independent from speed-related gait parameters. Dual-task parameters had limited additional value for evaluating gait in knee and hip OA, although dual-task cost constituted a separate gait domain. Future steps should include testing responsiveness of these gait domains to interventions aiming to improve mobility.


Sensors ◽  
2012 ◽  
Vol 12 (5) ◽  
pp. 5791-5814 ◽  
Author(s):  
Alberto Olivares ◽  
Javier Ramírez ◽  
Juan M. Górriz ◽  
Gonzalo Olivares ◽  
Miguel Damas

Author(s):  
Pyeong-Gook Jung ◽  
Sehoon Oh ◽  
Gukchan Lim ◽  
Kyoungchul Kong

Motion capture systems play an important role in health-care and sport-training systems. In particular, there exists a great demand on a mobile motion capture system that enables people to monitor their health condition and to practice sport postures anywhere at any time. The motion capture systems with infrared or vision cameras, however, require a special setting, which hinders their application to a mobile system. In this paper, a mobile three-dimensional motion capture system is developed based on inertial sensors and smart shoes. Sensor signals are measured and processed by a mobile computer; thus, the proposed system enables the analysis and diagnosis of postures during outdoor sports, as well as indoor activities. The measured signals are transformed into quaternion to avoid the Gimbal lock effect. In order to improve the precision of the proposed motion capture system in an open and outdoor space, a frequency-adaptive sensor fusion method and a kinematic model are utilized to construct the whole body motion in real-time. The reference point is continuously updated by smart shoes that measure the ground reaction forces.


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