Psychophysical Cost Function of Joint Movement for Arm Reach Posture Prediction

1994 ◽  
Vol 38 (10) ◽  
pp. 636-640 ◽  
Author(s):  
Eui S. Jung ◽  
Jaeho Choe ◽  
Sung H. Kim
Keyword(s):  
Prediction Model ◽  
Cost Function ◽  
Degrees Of Freedom ◽  
Human Movement ◽  
Difficult Problem ◽  
Joint Torque ◽  
Joint Movement ◽  
Human Arm ◽  
Posture Prediction ◽  
Joint Range

A man model can be used as an effective tool to design ergonomically sound products and workplaces, and subsequently evaluate them properly. For a man model to be truly useful, it must be integrated with a posture prediction model which should be capable of representing the human arm reach posture in the context of equipments and workspaces. Since the human movement possesses redundant degrees of freedom, accurate representation or prediction of human movement was known to be a difficult problem. To solve this redundancy problem, a psychophysical cost function was suggested in this study which defines a cost value for each joint movement angle. The psychophysical cost function developed integrates the psychophysical discomfort of joints and the joint range availability concept which has been used for redundant arm manipulation in robotics to predict the arm reach posture. To properly predict an arm reach posture, an arm reach posture prediction model was then developed in which a posture configuration that provides the minimum total cost is chosen. The predictivity of the psychophysical cost function was compared with that of the biomechanical cost function which is based on the minimization of joint torque. Here, the human body is regarded as a two-dimensional multi-link system which consists of four links; trunk, upper arm, lower arm and hand. Real reach postures were photographed from the subjects and were compared to the postures predicted by the model. Results showed that the postures predicted by the psychophysical cost function closely simulated human reach postures and the predictivity was more accurate than that by the biomechanical cost function.

Design Human-Robot Collaborative Lifting Task Using Optimization

2021 ◽  
Author(s):  
Asif Arefeen ◽  
Yujiang Xiang
Keyword(s):  
Degrees Of Freedom ◽  
Joint Angle ◽  
Joint Torque ◽  
Robotic Arm ◽  
Inverse Dynamic ◽  
Floating Base ◽  
Grasping Forces ◽  
Design Variables ◽  
Human Arm ◽  
Lifting Task

Abstract In this paper, an optimization-based dynamic modeling method is used for human-robot lifting motion prediction. The three-dimensional (3D) human arm model has 13 degrees of freedom (DOFs) and the 3D robotic arm (Sawyer robotic arm) has 10 DOFs. The human arm and robotic arm are built in Denavit-Hartenberg (DH) representation. In addition, the 3D box is modeled as a floating-base rigid body with 6 global DOFs. The interactions between human arm and box, and robot and box are modeled as a set of grasping forces which are treated as unknowns (design variables) in the optimization formulation. The inverse dynamic optimization is used to simulate the lifting motion where the summation of joint torque squares of human arm is minimized subjected to physical and task constraints. The design variables are control points of cubic B-splines of joint angle profiles of the human arm, robotic arm, and box, and the box grasping forces at each time point. A numerical example is simulated for huma-robot lifting with a 10 Kg box. The human and robotic arms’ joint angle, joint torque, and grasping force profiles are reported. These optimal outputs can be used as references to control the human-robot collaborative lifting task.

scholarly journals The reserve of joint torque determines movement coordination

2021 ◽  
Author(s):  
Germain Faity ◽  
Denis Mottet ◽  
Simon Pla ◽  
Jérôme Froger
Keyword(s):  
Optimal Control ◽  
Cost Function ◽  
Degrees Of Freedom ◽  
Minimum Cost ◽  
Joint Torque ◽  
Movement Coordination ◽  
Trunk Motion ◽  
Additional Load ◽  
The Cost ◽  
Healthy Participants

AbstractHumans coordinate biomechanical degrees of freedom to perform tasks at minimum cost. When reaching a target from a seated position, the trunk-arm-forearm coordination moves the hand to the well-defined spatial goal, while typically minimising hand jerk and trunk motion. However, due to fatigue or stroke, people visibly move the trunk more, and it is unclear what cost can account for this. Here we show that people recruit their trunk when the torque at the shoulder is too close to the maximum. We asked 26 healthy participants to reach a target while seated and we found that the trunk contribution to hand displacement increases from 11% to 27% when an additional load is handled. By flexing and rotating the trunk, participants spontaneously increase the reserve of anti-gravitational torque at the shoulder from 25% to 40% of maximal voluntary torque. Our findings provide hints on how to include the reserve of torque in the cost function of optimal control models of human coordination in healthy fatigued persons or in stroke victims.

Reach Posture Prediction of Upper Limb for Ergonomic Workspace Evaluation

1992 ◽  
Vol 36 (10) ◽  
pp. 702-706 ◽  
Author(s):  
Eui S. Jung ◽  
Dohyung Kee ◽  
Min K. Chung
Keyword(s):  
Upper Limb ◽  
Inverse Kinematics ◽  
Degrees Of Freedom ◽  
Local Optimality ◽  
Redundant Manipulator ◽  
Performance Function ◽  
Posture Prediction ◽  
The Subject ◽  
Analysis System ◽  
Joint Range

Proper assessment of reach posture is one of the essential functions for ergonomic workspace evaluation in CAD systems with a built-in man-model. In this study, Each upper limb is modelled as a four-link system, consisting of trunk, upper arm, lower arm, and hand, being regarded as a redundant manipulator with a total of eight degrees of freedom. Inverse kinematics is introduced in this study to predict the trajectory of multi-link segmental movement. Among several kinematic methods for solving the multi-link system, the resolved motion method was found to be effective to solve this redundant manipulator model, and the joint range availability was used as a performance function in order to guarantee local optimality. Real reach postures taken from the subject were analyzed by Motion Analysis System and showed reasonable results when compared to those obtained from the model.

scholarly journals The reserve of joint torque determines movement coordination

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Germain Faity ◽  
Denis Mottet ◽  
Simon Pla ◽  
Jérôme Froger
Keyword(s):  
Optimal Control ◽  
Cost Function ◽  
Degrees Of Freedom ◽  
Minimum Cost ◽  
Joint Torque ◽  
Movement Coordination ◽  
Trunk Motion ◽  
Additional Load ◽  
The Cost ◽  
Healthy Participants

AbstractHumans coordinate biomechanical degrees of freedom to perform tasks at minimum cost. When reaching a target from a seated position, the trunk-arm-forearm coordination moves the hand to the well-defined spatial goal, while typically minimising hand jerk and trunk motion. However, due to fatigue or stroke, people visibly move the trunk more, and it is unclear what cost can account for this. Here we show that people recruit their trunk when the torque at the shoulder is too close to the maximum. We asked 26 healthy participants to reach a target while seated and we found that the trunk contribution to hand displacement increases from 11 to 27% when an additional load is handled. By flexing and rotating the trunk, participants spontaneously increase the reserve of anti-gravitational torque at the shoulder from 25 to 40% of maximal voluntary torque. Our findings provide hints on how to include the reserve of torque in the cost function of optimal control models of human coordination in healthy fatigued persons or in stroke victims.

Three-dimensional asymmetric maximum weight lifting prediction considering dynamic joint strength

2021 ◽  
pp. 095441192098703
Author(s):  
Rahid Zaman ◽  
Yujiang Xiang ◽  
Jazmin Cruz ◽  
James Yang
Keyword(s):  
Experimental Data ◽  
Degrees Of Freedom ◽  
Inverse Dynamics ◽  
Three Dimensional ◽  
Optimization Method ◽  
Weight Lifting ◽  
Joint Torque ◽  
Maximum Weight ◽  
Angular Velocities ◽  
Asymmetric Lifting

In this study, the three-dimensional (3D) asymmetric maximum weight lifting is predicted using an inverse-dynamics-based optimization method considering dynamic joint torque limits. The dynamic joint torque limits are functions of joint angles and angular velocities, and imposed on the hip, knee, ankle, wrist, elbow, shoulder, and lumbar spine joints. The 3D model has 40 degrees of freedom (DOFs) including 34 physical revolute joints and 6 global joints. A multi-objective optimization (MOO) problem is solved by simultaneously maximizing box weight and minimizing the sum of joint torque squares. A total of 12 male subjects were recruited to conduct maximum weight box lifting using squat-lifting strategy. Finally, the predicted lifting motion, ground reaction forces, and maximum lifting weight are validated with the experimental data. The prediction results agree well with the experimental data and the model’s predictive capability is demonstrated. This is the first study that uses MOO to predict maximum lifting weight and 3D asymmetric lifting motion while considering dynamic joint torque limits. The proposed method has the potential to prevent individuals’ risk of injury for lifting.

scholarly journals BIOMIMETIC DESIGN OF LOW STIFFNESS ACTUATOR SYSTEMS FOR PROSTHETIC LIMBS

2011 ◽  
Author(s):  
D. L. Russell ◽  
M. McTavish
Keyword(s):  
Mechanical Properties ◽  
Degrees Of Freedom ◽  
Analytical Techniques ◽  
Energetic Costs ◽  
Multiple Degrees Of Freedom ◽  
Prosthetic Limbs ◽  
Limb Stiffness ◽  
Human Arm ◽  
Biomimetic Approach ◽  
Low Stiffness

The various relationships that are possible between the mechanical properties of single actuators and the overall mechanism (in this case a human arm with or without a prosthetic elbow) are discussed. Graphical and analytical techniques for describing the range of overall limb stiffnesses that are achievable and for characterizing the overall limb stiffness have been developed. Using a biomimetic approach and, considering energetic costs, stability and complexity, the implications of choosing passive or active implementations of stiffness are discussed. These techniques and approaches are particularly applicable with redundant (agonist - antagonist) actuators and multiple degrees of freedom. Finally, a novel biomimetic approach for control is proposed.

Physics-Based Seated Posture Prediction for Pregnant Women and Validation Considering Ground and Seat Pan Contacts

2012 ◽  
Vol 134 (7) ◽  
Author(s):  
Bradley Howard ◽  
Aimee Cloutier ◽  
Jingzhou (James) Yang
Keyword(s):  
Pregnant Women ◽  
Objective Function ◽  
Linear Regression Analysis ◽  
Joint Torque ◽  
Joint Torques ◽  
Design Variables ◽  
Optimization Formulation ◽  
Posture Prediction ◽  
Seated Posture ◽  
End Effectors

An understanding of human seated posture is important across many fields of scientific research. Certain demographics, such as pregnant women, have special postural limitations that need to be considered. Physics-based posture prediction is a tool in which seated postures can be quickly and thoroughly analyzed, as long the predicted postures are realistic. This paper proposes and validates an optimization formulation to predict seated posture for pregnant women considering ground and seat pan contacts. For the optimization formulation, the design variables are joint angles (posture); the cost function is dependent on joint torques. Constraints include joint limits, joint torque limits, the distances from the end-effectors to target points, and self-collision avoidance constraints. Three different joint torque cost functions have been investigated to account for the special postural characteristics of pregnant women and consider the support reaction forces (SRFs) associated with seated posture. Postures are predicted for three different reaching tasks in common reaching directions using each of the objective function formulations. The predicted postures are validated against experimental postures obtained using motion capture. A linear regression analysis was used to evaluate the validity of the predicted postures and was the criteria for comparison between the different objective functions. A 56 degree of freedom model was used for the posture prediction. Use of the objective function minimizing the maximum normalized joint torque provided an R2 value of 0.828, proving superior to either of two alternative functions.

scholarly journals Estimation of the Abduction/Adduction Movement of the Metacarpophalangeal Joint of the Thumb

2021 ◽  
Vol 11 (7) ◽  
pp. 3158
Author(s):  
Néstor J. Jarque-Bou ◽  
Margarita Vergara ◽  
Joaquín L. Sancho-Bru
Keyword(s):  
3D Modeling ◽  
Daily Living ◽  
Degrees Of Freedom ◽  
Estimation Error ◽  
Metacarpophalangeal Joint ◽  
Joint Movement ◽  
Carpometacarpal Joint ◽  
Small Space ◽  
Joint Motions

Thumb opposition is essential for grasping, and involves the flexion and abduction of the carpometacarpal and metacarpophalangeal joints of the thumb. The high number of degrees of freedom of the thumb in a fairly small space makes the in vivo recording of its kinematics a challenging task. For this reason, along with the very limited independence of the abduction movement of the metacarpophalangeal joint, many devices do not implement sensors to measure such movement, which may lead to important implications in terms of the accuracy of thumb models. The aims of this work are to examine the correlation between thumb joints and to obtain an equation that allows thumb metacarpophalangeal abduction/adduction movement to be estimated from the other joint motions of the thumb, during the commonest grasps used during activities of daily living and in free movement. The correlation analysis shows that metacarpophalangeal abduction/adduction movement can be expressed mainly from carpometacarpal joint movements. The model thus obtained presents a low estimation error (6.29°), with no significant differences between grasps. The results could benefit most fields that do not typically include this joint movement, such as virtual reality, teleoperation, 3D modeling, prostheses, and exoskeletons.

Simulated Compensatory Motion of Transradial Prostheses

2008 ◽  
Author(s):  
Derek Lura ◽  
Rajiv Dubey ◽  
Stephanie L. Carey ◽  
M. Jason Highsmith
Keyword(s):  
Range Of Motion ◽  
Shoulder Joint ◽  
Degrees Of Freedom ◽  
Biomechanical Model ◽  
Elbow Flexion ◽  
Limited Range ◽  
Joint Movement ◽  
Range Of Movement ◽  
Limited Range Of Motion ◽  
Compensatory Motion

The prostheses used by the majority of persons with hand/arm amputations today have a very limited range of motion. Transradial (below the elbow) amputees lose the three degrees of freedom provided by the wrist and forearm. Some myoeletric prostheses currently allow for forearm pronation and supination (rotation about an axis parallel to the forearm) and the operation of a powered prosthetic hand. Older body-powered prostheses, incorporating hooks and other cable driven terminal devices, have even fewer degrees of freedom. In order to perform activities of daily living (ADL), a person with amputation(s) must use a greater than normal range of movement from other body joints to compensate for the loss of movement caused by the amputation. By studying the compensatory motion of prosthetic users we can understand the mechanics of how they adapt to the loss of range of motion in a given limb for select tasks. The purpose of this study is to create a biomechanical model that can predict the compensatory motion using given subject data. The simulation can then be used to select the best prosthesis for a given user, or to design prostheses that are more effective at selected tasks, once enough data has been analyzed. Joint locations necessary to accomplish the task with a given configuration are calculated by the simulation for a set of prostheses and tasks. The simulation contains a set of prosthetic configurations that are represented by parameters that consist of the degrees of freedom provided by the selected prosthesis. The simulation also contains a set of task information that includes joint constraints, and trajectories which the hand or prosthesis follows to perform the task. The simulation allows for movement in the wrist and forearm, which is dependent on the prosthetic configuration, elbow flexion, three degrees of rotation at the shoulder joint, movement of the shoulder joint about the sternoclavicular joint, and translation and rotation of the torso. All joints have definable restrictions determined by the prosthesis, and task.

scholarly journals Computational Modeling: Human Dynamic Model

2021 ◽  
Vol 15 ◽  
Author(s):  
Lijia Liu ◽  
Joseph L. Cooper ◽  
Dana H. Ballard
Keyword(s):  
Dynamic Model ◽  
Degrees Of Freedom ◽  
Dynamic Models ◽  
Movement Analysis ◽  
Human Movement ◽  
Uncontrolled Manifold ◽  
Human In The Loop ◽  
Joint Forces ◽  
Internal Joint ◽  
Movement Function

Improvements in quantitative measurements of human physical activity are proving extraordinarily useful for studying the underlying musculoskeletal system. Dynamic models of human movement support clinical efforts to analyze, rehabilitate injuries. They are also used in biomechanics to understand and diagnose motor pathologies, find new motor strategies that decrease the risk of injury, and predict potential problems from a particular procedure. In addition, they provide valuable constraints for understanding neural circuits. This paper describes a physics-based movement analysis method for analyzing and simulating bipedal humanoid movements. The model includes the major body segments and joints to report human movements' energetic components. Its 48 degrees of freedom strike a balance between very detailed models that include muscle models and straightforward two-dimensional models. It has sufficient accuracy to analyze and synthesize movements captured in real-time interactive applications, such as psychophysics experiments using virtual reality or human-in-the-loop teleoperation of a simulated robotic system. The dynamic model is fast and robust while still providing results sufficiently accurate to be used to animate a humanoid character. It can also estimate internal joint forces used during a movement to create effort-contingent stimuli and support controlled experiments to measure the dynamics generating human behaviors systematically. The paper describes the innovative features that allow the model to integrate its dynamic equations accurately and illustrates its performance and accuracy with demonstrations. The model has a two-foot stance ability, capable of generating results comparable with an experiment done with subjects, and illustrates the uncontrolled manifold concept. Additionally, the model's facility to capture large energetic databases opens new possibilities for theorizing as to human movement function. The model is freely available.

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