Three dimensional analysis of joint torques and joint torque powers of the lower limbs in sprint hurdles

1997 ◽  
Vol 29 (11) ◽  
pp. 1545
Author(s):  
N. Fujii ◽  
K. Miyashita ◽  
M. &NA;
2007 ◽  
Vol 129 (6) ◽  
pp. 838-847 ◽  
Author(s):  
Joon-young Kim ◽  
James K. Mills ◽  
Albert H. Vette ◽  
Milos R. Popovic

Arm-free paraplegic standing via functional electrical stimulation (FES) has drawn much attention in the biomechanical field as it might allow a paraplegic to stand and simultaneously use both arms to perform daily activities. However, current FES systems for standing require that the individual actively regulates balance using one or both arms, thus limiting the practical use of these systems. The purpose of the present study was to show that actuating only six out of 12 degrees of freedom (12-DOFs) in the lower limbs to allow paraplegics to stand freely is theoretically feasible with respect to multibody stability and physiological torque limitations of the lower limb DOF. Specifically, the goal was to determine the optimal combination of the minimum DOF that can be realistically actuated using FES while ensuring stability and able-bodied kinematics during perturbed arm-free standing. The human body was represented by a three-dimensional dynamics model with 12-DOFs in the lower limbs. Nakamura’s method (Nakamura, Y., and Ghodoussi, U., 1989, “Dynamics Computation of Closed-Link Robot Mechanisms With Nonredundant and Redundant Actuators,” IEEE Trans. Rob. Autom., 5(3), pp. 294–302) was applied to estimate the joint torques of the system using experimental motion data from four healthy subjects. The torques were estimated by applying our previous finding that only 6 (6-DOFs) out of 12-DOFs in the lower limbs need to be actuated to facilitate stable standing. Furthermore, it was shown that six cases of 6-DOFs exist, which facilitate stable standing. In order to characterize each of these cases in terms of the torque generation patterns and to identify a potential optimal 6-DOF combination, the joint torques during perturbations in eight different directions were estimated for all six cases of 6-DOFs. The results suggest that the actuation of both ankle flexion∕extension, both knee flexion∕extension, one hip flexion∕extension, and one hip abduction∕adduction DOF will result in the minimum torque requirements to regulate balance during perturbed standing. To facilitate unsupported FES-assisted standing, it is sufficient to actuate only 6-DOFs. An optimal combination of 6-DOFs exists, for which this system can generate able-bodied kinematics while requiring lower limb joint torques that are producible using contemporary FES technology. These findings suggest that FES-assisted arm-free standing of paraplegics is theoretically feasible, even when limited by the fact that muscles actuating specific DOFs are often denervated or difficult to access.


Sensors ◽  
2020 ◽  
Vol 20 (13) ◽  
pp. 3685
Author(s):  
Jiantao Yang ◽  
Yuehong Yin

Estimating the joint torques of lower limbs in human gait is a highly challenging task and of great significance in developing high-level controllers for lower-limb exoskeletons. This paper presents a dependent Gaussian process (DGP)-based learning algorithm for joint-torque estimations with measurements from wearable smart shoes. The DGP was established to perform data fusion, and serves as the mathematical foundation to explore the correlations between joint kinematics and joint torques that are embedded deeply in the data. As joint kinematics are used in the training phase rather than the prediction process, the DGP model can realize accurate predictions in outdoor activities by using only the smart shoe, which is low-cost, nonintrusive for human gait, and comfortable to wearers. The design methodology of dynamic specific kernel functions is presented in accordance to prior knowledge of the measured signals. The designed composite kernel functions can be used to model multiple features at different scales, and cope with the temporal evolution of human gait. The statistical nature of the proposed DGP model and the composite kernel functions offer superior flexibility for time-varying gait-pattern learning, and enable accurate joint-torque estimations. Experiments were conducted with five subjects, whose results showed that it is possible to estimate joint torques under different trained and untrained speed levels. Comparisons were made between the proposed DGP and Gaussian process (GP) models. Obvious improvements were achieved when all DGP r2 values were higher than those of GP.


1999 ◽  
Vol 15 (2) ◽  
pp. 106-119 ◽  
Author(s):  
John H. Lawrence ◽  
T. Richard Nichols

Muscle actions are often defined within a single anatomical reference plane. Yet animals must control posture and movement within a three-dimensional (3-D) environment, responding to a 3-D array of perturbing forces. Based on information gained regarding the 3-D muscle mechanics at the cat ankle joint complex (companion paper), we decided to study how alterations in the 3-D AJC orientation might affect ankle joint postural control. We used a 6 degree-of-freedom force-moment sensor to assess the affect of ankle joint orientation on the 3-D isometric joint torques evoked by electrical stimulation of muscles crossing the ankle joint complex (AJC) in the deeply anesthetized cat. An orthogonal axis system was established at the designated ankle rotation center, such that pitch (flexion-extension), yaw (abduction-adduction), and roll (inversion-eversion) axis torques were calculated. Experimental results suggest that both the magnitude and sign of extra-sagittal torques from the gastrocnemius muscles are joint angle dependent. Also, the hind limb levering system stabilizes the AJC against large yaw and roll rotations away from the control position.


Sensors ◽  
2020 ◽  
Vol 20 (21) ◽  
pp. 6277
Author(s):  
Myunghyun Lee ◽  
Sukyung Park

Kinetics data such as ground reaction forces (GRFs) are commonly used as indicators for rehabilitation and sports performance; however, they are difficult to measure with convenient wearable devices. Therefore, researchers have attempted to estimate accurately unmeasured kinetics data with artificial neural networks (ANNs). Because the inputs to an ANN affect its performance, they must be carefully selected. The GRF and center of pressure (CoP) have a mechanical relationship with the center of mass (CoM) in the three dimensions (3D). This biomechanical characteristic can be used to establish an appropriate input and structure of an ANN. In this study, an ANN for estimating gait kinetics with a single inertial measurement unit (IMU) was designed; the kinematics of the IMU placed on the sacrum as a proxy for the CoM kinematics were applied based on the 3D spring mechanics. The walking data from 17 participants walking at various speeds were used to train and validate the ANN. The estimated 3D GRF, CoP trajectory, and joint torques of the lower limbs were reasonably accurate, with normalized root-mean-square errors (NRMSEs) of 6.7% to 15.6%, 8.2% to 20.0%, and 11.4% to 24.1%, respectively. This result implies that the biomechanical characteristics can be used to estimate the complete three-dimensional gait data with an ANN model and a single IMU.


Author(s):  
S. Naka ◽  
R. Penelle ◽  
R. Valle

The in situ experimentation technique in HVEM seems to be particularly suitable to clarify the processes involved in recrystallization. The material under investigation was unidirectionally cold-rolled titanium of commercial purity. The problem was approached in two different ways. The three-dimensional analysis of textures was used to describe the texture evolution during the primary recrystallization. Observations of bulk-annealed specimens or thin foils annealed in the microscope were also made in order to provide information concerning the mechanisms involved in the formation of new grains. In contrast to the already published work on titanium, this investigation takes into consideration different values of the cold-work ratio, the temperature and the annealing time.Two different models are commonly used to explain the recrystallization textures i.e. the selective grain growth model (Beck) or the oriented nucleation model (Burgers). The three-dimensional analysis of both the rolling and recrystallization textures was performed to identify the mechanismsl involved in the recrystallization of titanium.


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