scholarly journals Estimation of Ground Reaction Forces and Moments During Gait Using Only Inertial Motion Capture

Sensors ◽  
2016 ◽  
Vol 17 (12) ◽  
pp. 75 ◽  
Author(s):  
Angelos Karatsidis ◽  
Giovanni Bellusci ◽  
H. Schepers ◽  
Mark de Zee ◽  
Michael Andersen ◽  
...  
Sensors ◽  
2019 ◽  
Vol 19 (9) ◽  
pp. 2011 ◽  
Author(s):  
Bessone ◽  
Petrat ◽  
Schwirtz

In the past, technological issues limited research focused on ski jump landing. Today, thanks to the development of wearable sensors, it is possible to analyze the biomechanics of athletes without interfering with their movements. The aims of this study were twofold. Firstly, the quantification of the kinetic magnitude during landing is performed using wireless force insoles while 22 athletes jumped during summer training on the hill. In the second part, the insoles were combined with inertial motion units (IMUs) to determine the possible correlation between kinematics and kinetics during landing. The maximal normal ground reaction force (GRFmax) ranged between 1.1 and 5.3 body weight per foot independently when landing using the telemark or parallel leg technique. The GRFmax and impulse were correlated with flying time (p < 0.001). The hip flexions/extensions and the knee and hip rotations of the telemark front leg correlated with GRFmax (r = 0.689, p = 0.040; r = −0.670, p = 0.048; r = 0.820, p = 0.007; respectively). The force insoles and their combination with IMUs resulted in promising setups to analyze landing biomechanics and to provide in-field feedback to the athletes, being quick to place and light, without limiting movement.


Author(s):  
Yanwei Zhang ◽  
Zhenxian Chen ◽  
Yinghu Peng ◽  
Hongmou Zhao ◽  
Xiaojun Liang ◽  
...  

The motion capture and force plates data are essential inputs for musculoskeletal multibody dynamics models to predict in vivo tibiotalar contact forces. However, it could be almost impossible to obtain valid force plates data in old patients undergoing total ankle arthroplasty under some circumstances, such as smaller gait strides and inconsistent walking speeds during gait analysis. To remove the dependence of force plates, this study has established a patient-specific musculoskeletal multibody dynamics model with total ankle arthroplasty by combining a foot-ground contact model based on elastic contact elements. And the established model could predict ground reaction forces, ground reaction moments and tibiotalar contact forces simultaneously. Three patients’ motion capture and force plates data during their normal walking were used to establish the patient-specific musculoskeletal models and evaluate the predicted ground reaction forces and ground reaction moments. Reasonable accuracies were achieved for the predicted and measured ground reaction forces and ground reaction moments. The predicted tibiotalar contact forces for all patients using the foot-ground contact model had good consistency with those using force plates data. These findings suggested that the foot-ground contact model could take the place of the force plates data for predicting the tibiotalar contact forces in other total ankle arthroplasty patients, thus providing a simplified and valid platform for further study of the patient-specific prosthetic designs and clinical problems of total ankle arthroplasty in the absence of force plates data.


Author(s):  
Brian A. Knarr ◽  
Jill S. Higginson

Subjects with significant gait impairments may require the use of external support to safely walk during motion capture collections [1]. Development of musculoskeletal simulations in the OpenSim environment, however, is complicated by external forces beyond ground reaction forces. Measured ground reaction forces and moments may be dynamically inconsistent with model kinematics due to modeling assumptions and experimental error [2]. With the addition of external forces applied using handrails, a harness support system or other loads, prediction of muscle forces and contribution to movement may be inaccurate, especially if all external forces are not able to be measured and included in the model.


2018 ◽  
Vol 56 (10) ◽  
pp. 1781-1792 ◽  
Author(s):  
William R. Johnson ◽  
Ajmal Mian ◽  
Cyril J. Donnelly ◽  
David Lloyd ◽  
Jacqueline Alderson

Author(s):  
Luca Fontanili ◽  
Massimo Milani ◽  
Luca Montorsi ◽  
Giordano Valente

The paper focuses on the gait analysis for the investigation of the typical events occurring in human movements and validate its use as a method for musculoskeletal disease evaluation and for the improvement of athletic training. In the present research the motion capture system is combined with an in-house developed prototype of uniaxial force plates for the measurement of the vertical component of ground reaction forces during movement. While similar techniques are implemented for gait, this equipment can be employed to investigate running, thus, covering a larger number of possible applications and providing a deeper insight either of the athlete performance or the disease analysis. For the prevention and the treatment of those events occurring during running, a thorough understanding of its mechanisms is critical; therefore, a method for evaluating both the kinematic behavior of the human body and the ground reaction forces combined to a model for determining the muscle forces is proposed. An infrared motion capture technique is adopted for measuring accurately the body motion and a multiple force-plate system is used to calculate the force exerted by the ground and sub-divided in the three components by an ad-hoc developed routine. Moreover, the data are used as input parameters for the OpenSim software to derive muscles forces. Finally, the potential of the proposed protocol is determined by an experimental campaign on healthy subjects and a significant database of muscle forces is constructed for different running speeds.


2020 ◽  
Vol 52 (7S) ◽  
pp. 938-939
Author(s):  
Eric M. Mosier ◽  
Andrew C. Fry ◽  
Justin X. Nicoll ◽  
Dimitrije Cabarkapa ◽  
Stephanie A. Sontag ◽  
...  

2016 ◽  
Vol 1 (1) ◽  
Author(s):  
Andrew C. Fry ◽  
Trent J. Herda ◽  
Adam J. Sterczala ◽  
Michael A. Cooper ◽  
Matthew J. Andre

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