scholarly journals Analysis of a Biomechanical Model for Safe Lifting Using Matlab Simulation

2012 ◽  
pp. 294-299
Author(s):  
Neeraj Saraswat ◽  
Shikhar Sharma ◽  
Rahul Jain ◽  
Deepak Pathak
Keyword(s):  
Material Handling ◽  
Geometric Model ◽  
Reaction Force ◽  
Biomechanical Model ◽  
Force Balance ◽  
Matlab Simulation ◽  
Load Shape ◽  
Moment Load ◽  
Multi Body ◽  
Biomechanical Factors

This paper describes the development of a multi-body biomechanical model that can be used to assess the risk of low back disorders. A multi-segment link model is considered in this paper which represents a human body in which links represent various limbs such as arms, leg, foot, thigh, thorax etc. Force balance and moment balance equations are formed at different joints. Equations formed are written in form of a MATLAB program to determine the relationship between load lifted and muscle moment generated due to load. This biomechanical model was employed to clarify the role of various biomechanical factors such as magnitude of load, shape, size and location of load involved in the load lifting process. To determine safe lifting postures on the basis of model such that the reaction force at the L4 / L5 joint is minimum subjected to other joints not being overstressed is carried out. Various moment-load relationships between various joints are computed along with momentmoment relationships between various joints. The model is able to suggest the safe posture in manual material handling tasks. A geometric model for simulations of postural control is obtained with Matlab/Simulink software .

scholarly journals Analysis of a Biomechanical Model for Safe Lifting using MATLAB Simulation

2013 ◽  
pp. 73-78
Author(s):  
Neeraj Saraswat ◽  
Shikhar Sharma ◽  
Rahul Jain ◽  
Deepak Pathak
Keyword(s):  
Material Handling ◽  
Geometric Model ◽  
Reaction Force ◽  
Biomechanical Model ◽  
Force Balance ◽  
Matlab Simulation ◽  
Load Shape ◽  
Moment Load ◽  
Multi Body ◽  
Biomechanical Factors

This paper describes the development of a multi-body biomechanical model that can be used to assess the risk of low back disorders. A multi-segment link model is considered in this paper which represents a human body in which links represent various limbs such as arms, leg, foot, thigh, thorax etc. Force balance and moment balance equations are formed at different joints. Equations formed are written in form of a MATLAB program to determine the relationship between load lifted and muscle moment generated due to load. This biomechanical model was employed to clarify the role of various biomechanical factors such as magnitude of load, shape, size and location of load involved in the load lifting process. To determine safe lifting postures on the basis of model such that the reaction force at the L4 / L5 joint is minimum subjected to other joints not being overstressed is carried out. Various moment-load relationships between various joints are computed along with moment-moment relationships between various joints. The model is able to suggest the safe posture in manual material handling tasks. A geometric model for simulations of postural control is obtained with Matlab/Simulink software.

Biomechanical Factors Affecting the Peak Hand Reaction Force During the Bimanual Arrest of a Moving Mass

2001 ◽  
Vol 124 (1) ◽  
pp. 107-112 ◽  
Author(s):  
Kurt M. DeGoede ◽  
James A. Ashton-Miller ◽  
Albert B. Schultz ◽  
Neil B. Alexander
Keyword(s):  
Sagittal Plane ◽  
Impact Force ◽  
Reaction Force ◽  
Biomechanical Model ◽  
Factors Affecting ◽  
Impact Forces ◽  
Ballistic Pendulum ◽  
Stiffness And Damping ◽  
Biomechanical Factors ◽  
The Impact

Fall-related wrist fractures are among the most common fractures at any age. In order to learn more about the biomechanical factors influencing the impact response of the upper extremities, we studied peak hand reaction force during the bimanual arrest of a 3.4 kg ballistic pendulum moving toward the subject in the sagittal plane at shoulder height. Twenty healthy young and 20 older adults, with equal gender representation, arrested the pendulum after impact at one of three initial speeds: 1.8, 2.3, or 3.0 m/sec. Subjects were asked to employ one of three initial elbow angles: 130, 150, or 170 deg. An analysis of variance showed that hand impact force decreased significantly as impact velocity decreased (50 percent/m/s) and as elbow angle decreased (0.9 percent/degree). A two segment sagittally-symmetric biomechanical model demonstrated that two additional factors affected impact forces: hand-impactor surface stiffness and damping properties, and arm segment mass. We conclude that hand impact force can be reduced by more than 40 percent by decreasing the amount of initial elbow extension and by decreasing the velocity of the hands and arms relative to the impacting surface.

Comparison of Biomechanical Factors between the Kicking and Stance Limbs

2004 ◽  
Vol 13 (2) ◽  
pp. 135-150 ◽  
Author(s):  
Scott Ross ◽  
Kevin Guskiewicz ◽  
William Prentice ◽  
Robert Schneider ◽  
Bing Yu
Keyword(s):  
Knee Flexion ◽  
Reaction Force ◽  
Knee Extension ◽  
Knee Kinematic ◽  
Vertical Ground Reaction Force ◽  
Time To Peak ◽  
Balance Task ◽  
Vertical Ground ◽  
Biomechanical Factors ◽  
Anterior Posterior

Objective:T o determine differences between contralateral limbs’ strength, proprio-ception, and kinetic and knee-kinematic variables during single-limb landing.Setting:Laboratory.Subjects:30.Measurements:Hip, knee, and foot isokinetic peak torques; anterior/posterior (AP) and medial/lateral (ML) sway displacements during a balance task; and stabilization times, vertical ground-reaction force (VGRF), time to peak VGRF, and knee-flexion range of motion (ROM) from initial foot contact to peak VGRF during single-limb landing.Results:The kicking limb had significantly greater values for knee-extension (P= .008) and -flexion (P= .047) peak torques, AP sway displacement (P= .010), knee-flexion ROM from initial foot contact to peak VGRF (P< .001), and time to peak VGRF (P= .004). No other dependent measures were significantly different between limbs (P> .05).Conclusion:The kicking limb had superior thigh strength, better proprioception, and greater knee-flexion ROM than the stance limb.

The Methods to Study the Influence of the Clearance in the Case of Great Speeds and Small Speeds

2013 ◽  
Vol 837 ◽  
pp. 88-92
Author(s):  
Jan Cristian Grigore
Keyword(s):  
Dynamic Behavior ◽  
Reaction Force ◽  
Accurate Method ◽  
Angular Speed ◽  
Connecting Rod ◽  
Lagrange Equations ◽  
Joint Rotation ◽  
First Case ◽  
Multi Body ◽  
General Method

In kinematic couplings, clearances are inevitable for their operation. The size of these clearances but as a consequence of use, causes a malfunction of the mechanism to which it belongs. The law of motion of driveline changes, big clearances, non-technological system causes vibration, leading to discomfort, uncertainty, and thus reach its degradation. In the paper we shall make a few of geometric and mechanical type considerations about the clearances in the linkages, linkages planes with joint rotation links. Based on mathematical algorithm developed and applied crank mechanism, the model presented in [1], this paper scientifically developed mathematical model, proposing mathematical models to study the influence of the size of the clearance in general dynamic calculation mechanisms. Mechanism considered is crank connecting rod mechanism with clearance cinematic coupling between rod and crank rotation. The paper makes a study of the influence on the dynamic behavior of the crank rod mechanism at high speeds, but also general method algorithm is developed and accurate method to assess the dynamic behavior of multi-body mechanism. The first case is considered a constant angular speed motor and thus determine the elemental expressions that establish the mechanism position, velocity and acceleration expressions in the two directions heads elements. Finally we obtain the expression of the normal reaction force, as well as position expression that defines its angle. With reaction force can specify phase (contact, flight, impact) [1], the behavior of the journal. For the case of general method - the method multi-body - the exact method are established liaison relationships between the parameters , write matrices , inertia matrix. Use Lagrange equations, if non-holonomic constraints. Matrix differential equation of motion is written and it can be solved numerically using Runge-Kutta method of order four. Of the iterative method, we obtain the parameters used in calculating the reaction force expression that can be evaluated accurately in journal bearings behaviour. Any would be their source of appearance, they usually produce unwished effects during the mechanisms functioning.

An Investigation of the Variability in Human Performance during Manual Material Handling Activities

1994 ◽  
Vol 38 (10) ◽  
pp. 578-582
Author(s):  
Gary A. Mirka ◽  
Ann Baker
Keyword(s):  
Material Handling ◽  
Human Performance ◽  
Sagittal Plane ◽  
Coupling Effect ◽  
Peak Velocity ◽  
Three Dimensional ◽  
Biomechanical Model ◽  
Manual Material Handling ◽  
Symmetric Lifting ◽  
Dependent Position

The goal of this study was to quantify the variability of the three-dimensional kinematic and kinetic parameters describing the motion of the torso during the performance of sagittally symmetric lifting tasks. Subjects performed eight repetitions of simple lifting tasks described by three levels of coupling (poor, fair and good) and seven levels of load (4.5, 9, 13.5, 18, 22.5, 27 and 31.5 kg). The three-dimensional, time dependent position, velocity and acceleration of the lumbar spine were monitored using the Lumbar Motion Monitor. These measures were then input into a dynamic biomechanical model which calculated torque about the L5/S1 joint in the sagittal plane. The results of the kinematic analysis showed significant variability in the magnitude of the peak velocity and acceleration in the sagittal plane and also showed significant motion in the transverse and coronal planes. The kinetic analysis showed an increase in the variability of the peak dynamic torque with greater levels of load but no coupling effect.

BONE BIOMECHANICAL MODELING BASED ON CELLULAR STRUCTURE: METHODS AND EVALUATION

2015 ◽  
Vol 15 (06) ◽  
pp. 1540046 ◽  
Author(s):  
MONAN WANG ◽  
SHUFENG WANG ◽  
XIANJUN AN
Keyword(s):  
Cellular Structure ◽  
Geometric Model ◽  
Three Dimensional ◽  
Biomechanical Model ◽  
Bone Modeling ◽  
Transverse Strain ◽  
Test Results ◽  
Cellular Mechanics ◽  
Compression Load ◽  
Mechanics Model

The aim of this study is to establish a biomechanical model of bone on the basis of cellular structure and then to evaluate its accuracy for the clinical application. The thighbone of swine was scanned by computed tomography (CT). The resulting sectional images were input into MIMICS10.01 to generate a three-dimensional geometric model. A biomechanical model of bone was built on the basis of cellular structure, and calculations of the model were implemented in MATLAB with the finite element method. With this cellular mechanics model, axial compression load was simulated, and load–axial and load–transverse strain at the measurement points were detected. To evaluate the model, a mechanics model derived from an empirical formula was simulated under the same conditions, and an actual biomechanical experiment was also conducted. The simulated results obtained from the two models were then compared with the test results, indicating that the simulated results for the cellular model were closer to the test results than those for the empirical mechanics model. Therefore, the proposed cellular mechanics model shows advantages in accuracy and scope of application for bone modeling.

NOT ALL OSCILLATIONS ARE RUBBISH: FORWARD SIMULATION OF QUICK-RELEASE EXPERIMENTS

2003 ◽  
Vol 03 (01) ◽  
pp. 107-122 ◽  
Author(s):  
TOBIAS SIEBERT ◽  
HEIKO WAGNER ◽  
REINHARD BLICKHAN
Keyword(s):  
Geometric Model ◽  
Biomechanical Model ◽  
Muscle Properties ◽  
Model Calculations ◽  
Quick Release ◽  
Lever System ◽  
In Series ◽  
Linear Spring ◽  
Length Data ◽  
And Control

Quick-release experiments often produce noticeable oscillations on the measured force and length data in the first few milliseconds after the force release. We measured oscillations in experiments with several species (Rattus norvegicus, Galea musteloides, Rana pipiens) and different experimental setups. These oscillations are generally ignored as artifacts. This study investigates the cause of the oscillations. A biomechanical model of the experimental setup was developed consisting of a geometric model describing the setup and a Hill-type muscle-tendon model including the force-length-velocity relation and a linear spring in series. Muscle properties of each muscle were determined by the ISOFIT method. Model calculations and forward simulations of quick-release experiments based on experimentally determined muscle properties reveal that the observed oscillations are not artifacts (instrument and control), but the result of interactions of muscle-tendon properties with the inertia of muscles, bones and lever system.

Joint Modeling and Simulation of the Spindle System of Hammer Crusher Based on Finite Element Analysis and Flexible Multi-Body Dynamics. Part1: Modeling

2012 ◽  
Vol 630 ◽  
pp. 291-296
Author(s):  
Yu Wang ◽  
En Chen ◽  
Jun Qing Gao ◽  
Yun Feng Gong
Keyword(s):  
Finite Element Analysis ◽  
Finite Element ◽  
System Simulation ◽  
Geometric Model ◽  
Body System ◽  
Element Analysis ◽  
Spindle System ◽  
Body Dynamics ◽  
Multi Body ◽  
The Impact

In the past finite element analysis (FEA) and multi-body system simulation (MBS) were two isolated methods in the field of mechanical system simulation. Both of them had their specific fields of application. In recent years, it is urgent to combine these two methods as the flexible multi-body system grows up. This paper mainly focuses on modeling of the spindle system of hammer crusher, including geometric model, finite element model and multi-body dynamics (MBD) model. For multi-body dynamics modeling, the contact force between hammer and scrap steel was discussed, which is important to obtain the impact force. This paper also proposed how to combine FEA and MBS to analyze the dynamic performance of the spindle system by using different software products of MSC.Software.

scholarly journals An Engineering Model of Human Balance Control—Part I: Biomechanical Model

2015 ◽  
Vol 138 (1) ◽  
Author(s):  
Joseph E. Barton ◽  
Anindo Roy ◽  
John D. Sorkin ◽  
Mark W. Rogers ◽  
Richard Macko
Keyword(s):  
Inverse Dynamics ◽  
Balance Control ◽  
Dimensional Space ◽  
Young Subject ◽  
Reaction Force ◽  
Three Dimensional ◽  
Balance Training ◽  
Biomechanical Model ◽  
Measurement Tool ◽  
Inverse Dynamics Analysis

We developed a balance measurement tool (the balanced reach test (BRT)) to assess standing balance while reaching and pointing to a target moving in three-dimensional space according to a sum-of-sines function. We also developed a three-dimensional, 13-segment biomechanical model to analyze performance in this task. Using kinematic and ground reaction force (GRF) data from the BRT, we performed an inverse dynamics analysis to compute the forces and torques applied at each of the joints during the course of a 90 s test. We also performed spectral analyses of each joint's force activations. We found that the joints act in a different but highly coordinated manner to accomplish the tracking task—with individual joints responding congruently to different portions of the target disk's frequency spectrum. The test and the model also identified clear differences between a young healthy subject (YHS), an older high fall risk (HFR) subject before participating in a balance training intervention; and in the older subject's performance after training (which improved to the point that his performance approached that of the young subject). This is the first phase of an effort to model the balance control system with sufficient physiological detail and complexity to accurately simulate the multisegmental control of balance during functional reach across the spectra of aging, medical, and neurological conditions that affect performance. Such a model would provide insight into the function and interaction of the biomechanical and neurophysiological elements making up this system; and system adaptations to changes in these elements' performance and capabilities.

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