scholarly journals Development and Evaluation of a Musculoskeletal Model of the Elbow Joint Complex

1996 ◽  
Vol 118 (1) ◽  
pp. 32-40 ◽  
Author(s):  
R. V. Gonzalez ◽  
E. L. Hutchins ◽  
R. E. Barr ◽  
L. D. Abraham
Keyword(s):  
Elbow Joint ◽  
Muscle Force ◽  
Elbow Flexion ◽  
Musculoskeletal Model ◽  
Joint Torque ◽  
Time Varying ◽  
Moment Arm ◽  
Flexion Extension ◽  
The Relationship ◽  
Ballistic Movements

This paper describes the development and evaluation of a musculoskeletal model that represents human elbow flexion-extension and forearm pronation-supination. The length, velocity, and moment arm for each of the eight musculotendon actuators were based on skeletal anatomy and joint position. Musculotendon parameters were determined for each actuator and verified by comparing analytical moment-angle curves with experimental joint torque data. The parameters and skeletal geometry were also utilized in the musculoskeletal model for the analysis of ballistic (rapid-directed) elbow joint complex movements. The key objective was to develop a computational model, guided by parameterized optimal control, to investigate the relationship among patterns of muscle excitation, individual muscle forces, and to determine the effects of forearm and elbow position on the recruitment of individual muscles during a variety of ballistic movements. The model was partially verified using experimental kinematic, torque, and electromyographic data from volunteer subjects performing both isometric and ballistic elbow joint complex movements. This verification lends credibility to the time-varying muscle force predictions and the recruitment of muscles that contribute to both elbow flexion-extension and forearm pronation-supination.

Kinematics and Laxity of Ulnohumeral Joint Under Valgus-Varus Stress

1998 ◽  
Vol 02 (01) ◽  
pp. 45-54 ◽  
Author(s):  
Shinji Tanaka ◽  
Kai-Nan An ◽  
Bernard F. Morrey
Keyword(s):  
Elbow Joint ◽  
Three Dimensional ◽  
Elbow Flexion ◽  
Axial Rotation ◽  
Joint Laxity ◽  
Treatment Modalities ◽  
Trochlear Groove ◽  
Flexion Extension ◽  
Varus Stress ◽  
Baseline Information

Three-dimensional kinematics of the ulnohumeral joint under simulated active elbow joint flexion-extension was obtained by using an electromagnetic tacking device. The joint motion was analyzed based on Eulerian angle description. In order to minimize the effect of "downstream cross-talk" on calculation of the three Eulerian angles, an optimal axis to best represent flexion-extension of the elbow joint was established. This axis, on average, is close to the line joining the centers of the capitellum and the trochlear groove. Furthermore, joint laxity under valgus-varus stress was also examined. With the weight of the forearm as the stress, maximums of 7.6° valgus-varus laxity and 5.3° axial rotation laxity were observed within a range of elbow flexion. The results of this study provide useful baseline information on joint laxity for the evaluation of elbow joints with implant replacements and other surgical treatment modalities.

Prediction of clothing mobility using a musculoskeletal simulator

2019 ◽  
Vol 32 (1) ◽  
pp. 132-147
Author(s):  
Yosuke Horiba ◽  
Ayumu Tokutake ◽  
S. Inui
Keyword(s):  
Human Body ◽  
Design Methodology ◽  
Elbow Flexion ◽  
Simulation Method ◽  
Musculoskeletal Model ◽  
Joint Torque ◽  
Musculoskeletal Simulation ◽  
Content Type ◽  
Clothing Design ◽  
Dressed State

Purpose Mobility is one of the important elements in clothing design. The purpose of this paper is to examine the predictability of clothing mobility via musculoskeletal simulation. Design/methodology/approach In order to carry out the musculoskeletal simulation considering the influence of clothing, simulation of the dressed state was attempted. This paper simulated the dressed state and measured the motion-related deformation of the clothing to estimate the force applied to the human body based on the material property of the clothing samples. The dressed state was simulated using an external force in the musculoskeletal model. Findings When the elbow flexion torque with an elbow supporter was calculated using the above-mentioned method of musculoskeletal simulation, it was confirmed that the lower the stretchability of the sample, the higher the elbow flexion torque. In addition, the sensory evaluation performed under the same condition as that in the simulation showed that the lower the joint torque during the motion, the higher the subjective mobility, and that the higher the joint torque, the lower the subjective mobility. Thus, it is suggested that musculoskeletal simulation of the dressed state can predict the clothing mobility. Research limitations/implications However, the method proposed in this paper requires the measurement of the deformation of the clothing to estimate the force applied to the human body. Thus, it is difficult to apply this in the measurement of general clothing that allows enough space between it and the human body, requiring further improvement of the dressed state simulation method. Originality/value Because it is difficult to estimate the force applied by the clothing to the human body, only a few studies have performed analysis on the effect of clothing by using musculoskeletal simulation. Conversely, although the force applied by the clothing to the human body needs to be estimated in advance by the measurement of the deformation, the utility of the simulation in clothing design seems to be high because the simulation can estimate clothing mobility and the effects of clothing on muscle activity.

scholarly journals Biomechanical Role and Motion Contribution of Ligaments and Bony Constraints in the Elbow Stability: A Preliminary Study

2019 ◽  
Vol 6 (3) ◽  
pp. 68 ◽  
Author(s):  
Elisa Panero ◽  
Laura Gastaldi ◽  
Mara Terzini ◽  
Cristina Bignardi ◽  
Arman Sard ◽  
...  
Keyword(s):  
Motion Capture ◽  
Elbow Joint ◽  
Large Deflection ◽  
Elbow Flexion ◽  
Elbow Instability ◽  
Joint Stability ◽  
Coronoid Fracture ◽  
Flexion Extension ◽  
Preliminary Study ◽  
Functional Investigation

In flexion–extension motion, the interaction of several ligaments and bones characterizes the elbow joint stability. The aim of this preliminary study was to quantify the relative motion of the ulna with respect to the humerus in two human upper limbs specimens and to investigate the constraints role for maintaining the elbow joint stability in different section conditions. Two clusters of four markers were fixed respectively to the ulna and humerus, and their trajectory was recorded by a motion capture system during functional orthopedic maneuver. Considering the posterior bundle of medial collateral complex (pMUCL) and the coronoid, two section sequences were executed. The orthopedic maneuver of compression, pronation and varus force was repeated at 30°, 60° and 90° flexion for the functional investigation of constraints. Ulna deflection was compared to a baseline elbow flexion condition. With respect to the intact elbow, the coronoid osteotomy influences the elbow stability at 90° (deflection = 11.49 ± 17.39 mm), while small differences occur at 30° and 60°, due to ligaments constraint. The contemporary pMUCL section and coronoid osteotomy causes elbow instability, with large deflection at 30° (deflection = 34.40 ± 9.10 mm), 60° (deflection = 45.41 ± 18.47 mm) and 90° (deflection = 52.16 ± 21.92 mm). Surgeons may consider the pMUCL reconstruction in case of unfixable coronoid fracture.

A Neural Network Approach to Electromyographic Signal Processing for a Motor Control Task

1997 ◽  
Vol 119 (2) ◽  
pp. 335-337 ◽  
Author(s):  
W. T. Lester ◽  
R. V. Gonzalez ◽  
B. Fernandez ◽  
R. E. Barr
Keyword(s):  
Neural Network ◽  
Hybrid System ◽  
Elbow Flexion ◽  
Learning System ◽  
Joint Torque ◽  
Neural Network Approach ◽  
Electromyographic Signal ◽  
Muscle Activations ◽  
Skeletal Model ◽  
Ballistic Movements

A hybrid modeling structure composed of a one degree of freedom computational musculo-skeletal model and a multilayer perceptron neural network was used to effectively map electromyography (EMG) from a human exercise trial to muscle activations in a physiologically feasible and accurate fashion. Several configurations of the complete hybrid system were used to map four muscle surface EMGs from a ballistic elbow flexion to normalized muscle activations, estimated individual muscle forces and torque about the joint. The net joint torque was used to train the neural portion of the hybrid system to minimize kinematic error. The model allowed the estimation of the nonobservable parameters: normalized muscle activations and forces which was used to penalize the learning system. With these parameters in the learning equation, our system produced muscle activations consistent with the classic triphasic response present in ballistic movements.

A SURFACE EMG DRIVEN MUSCULOSKELETAL MODEL OF THE ELBOW FLEXION-EXTENSION MOVEMENT IN NORMAL SUBJECTS AND IN SUBJECTS WITH SPASTICITY

1999 ◽  
Vol 03 (02) ◽  
pp. 109-123 ◽  
Author(s):  
Connie J. Feng ◽  
Arthur F. T. Mak ◽  
Terry K. K. Koo
Keyword(s):  
Elbow Joint ◽  
Angular Position ◽  
Surface Emg ◽  
Musculoskeletal Model ◽  
Model Parameters ◽  
Joint Movement ◽  
Electromechanical Delay ◽  
Flexion Extension ◽  
Muscle Stress ◽  
Isometric Muscle

Spasticity often interferes with function, limits independence and may cause considerable disability. Elbow joint movement is involved in many daily living activities. A surface EMG driven musculoskeletal model was developed to predict joint trajectory and to compare the differences in the model parameters between the normal and spastic subjects. Three musculotendon actuators whose EMG could be assessed by surface electrodes (biceps, brachioradialis and triceps) were included in this musculoskeletal model. The proposed model took several sets of parameters (anthropometric parameters of the skeleton and muscle parameters) as inputs. Surface EMG signals of the three muscle groups were rectified, moving-averaged, scaled and converted to active states. These active states together with the initial angular position and velocity of the joint were also used as inputs for the model. The outputs were muscle forces and the trajectory of the elbow joint. Two groups of parameters, namely, maximal isometric muscle stress and electromechanical delay were estimated using the trajectory fitting algorithm. Results indicated that the model was successful in using the surface EMG as input signals in the prediction of elbow joint trajectory. The spastic subjects showed a lower maximum isometric muscle stress and longer electromechanical delay.

ESTIMATING MUSCLE FORCES AND KNEE JOINT TORQUE USING SURFACE ELECTROMYOGRAPHY: A MUSCULOSKELETAL BIOMECHANICAL MODEL

2017 ◽  
Vol 17 (04) ◽  
pp. 1750069 ◽  
Author(s):  
JIANGCHENG CHEN ◽  
XIAODONG ZHANG ◽  
LINXIA GU ◽  
CARL NELSON
Keyword(s):  
Knee Joint ◽  
Surface Electromyography ◽  
Neural Control ◽  
Muscle Activation ◽  
Muscle Force ◽  
Dynamic Properties ◽  
Biomechanical Model ◽  
Joint Torque ◽  
Muscle Forces ◽  
Flexion Extension

Surface electromyography (sEMG) is a useful tool for revealing the underlying musculoskeletal dynamic properties in the human body movement. In this paper, a musculoskeletal biomechanical model which relates the sEMG and knee joint torque is proposed. First, the dynamic model relating sEMG to skeletal muscle activation considering frequency and amplitude is built. Second, a muscle contraction model based on sliding-filament theory is developed to reflect the physiological structure and micro mechanical properties of the muscle. The muscle force and displacement vectors are determined and the transformation from muscle force to knee joint moment is realized, and finally a genetic algorithm-based calibration method for the Newton–Euler dynamics and overall musculoskeletal biomechanical model is put forward. Following the model calibration, the flexion/extension (FE) knee joint torque of eight subjects under different walking speeds was predicted. Results show that the forward biomechanical model can capture the general shape and timing of the joint torque, with normalized mean residual error (NMRE) of [Formula: see text]10.01%, normalized root mean square error (NRMSE) of [Formula: see text]12.39% and cross-correlation coefficient of [Formula: see text]0.926. The musculoskeletal biomechanical model proposed and validated in this work could facilitate the study of neural control and how muscle forces generate and contribute to the knee joint torque during human movement.

Proximal cueing to reduce elbow extension levels in suspect spin bowlers: A case study

2018 ◽  
Vol 13 (5) ◽  
pp. 643-648 ◽  
Author(s):  
Kane J Middleton ◽  
Denny JM Wells ◽  
Daryl H Foster ◽  
Jacqueline A Alderson
Keyword(s):  
Elbow Joint ◽  
Three Dimensional ◽  
Statistical Parametric Mapping ◽  
Elbow Flexion ◽  
Joint Kinematics ◽  
Hand Position ◽  
Elbow Extension ◽  
Waveform Data ◽  
Flexion Extension

Cricket bowlers must be able to deliver the ball with less than 15° of elbow extension or face suspension. The aim of this case study was to report the findings of a technique remediation programme on the elbow joint kinematics of an international cricket bowler. The bowler underwent a three-dimensional bowling analysis to measure his elbow joint kinematics before and after a technique remediation programme. The bowler was required to bowl six deliveries of each of his off-break, quicker and doosra variations. The remediation programme focussed on modifying the bowler’s run-up, shoulder alignment and ball/hand position at back foot impact. Elbow joint waveform data were analysed using statistical parametric mapping tests and coefficient of multiple determination. Elbow flexion–extension angles at discrete events were compared pre- and post-remediation using paired-sample t-tests. Results showed that the remediation programme was effective in reducing the amount of elbow flexion, particularly in the first 60% of the delivery cycle. Elbow extension range was significantly lower post-remediation for the off-break and quicker deliveries. It was concluded that basic short-term technique remediation can be effective in reducing elbow extension range.

scholarly journals Independent control of cocontraction and reciprocal activity during goal-directed reaching in muscle space

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Atsushi Takagi ◽  
Hiroyuki Kambara ◽  
Yasuharu Koike
Keyword(s):  
Muscle Force ◽  
Joint Torque ◽  
Vertical Position ◽  
Shoulder Flexion ◽  
Control Framework ◽  
Flexion Extension ◽  
Maximal Activation ◽  
Muscle Pair ◽  
The Central Nervous System ◽  
The Difference

AbstractThe movement in a joint is facilitated by a pair of muscles that pull in opposite directions. The difference in the pair’s muscle force or reciprocal activity results in joint torque, while the overlapping muscle force or the cocontraction is related to the joint’s stiffness. Cocontraction knowingly adapts implicitly over a number of movements, but it is unclear whether the central nervous system can actively regulate cocontraction in a goal-directed manner in a short span of time. We developed a muscle interface where a cursor’s horizontal position was determined by the reciprocal activity of the shoulder flexion–extension muscle pair, while the vertical position was controlled by its cocontraction. Participants made goal-directed movements to single and via-point targets in the two-dimensional muscle space, learning to move the cursor along the shortest path. Simulations using an optimal control framework suggest that the reciprocal activity and the cocontraction may be controlled independently by the CNS, albeit at a rate orders of magnitude slower than the muscle’s maximal activation speed.

Sign in / Sign up

Export Citation Format

Share Document