scholarly journals Biomimetic Knee Design to Improve Joint Torque and Life for Bipedal Robotics

Author(s):  
Alexander G. Steele ◽  
Alexander Hunt ◽  
Appolinaire C. Etoundi
Keyword(s):  
2013 ◽  
Vol 1 (1) ◽  
pp. 42-25
Author(s):  
Nabil N. Swadi

This paper is concerned with the study of the kinematic and kinetic analysis of a slider crank linkage using D'Alembert's principle. The links of the considered mechanism are assumed to be rigid. The analytical solution to observe the motion (displacement, velocity, and acceleration), reactions at each joint, torque required to drive the mechanism and the shaking force have been computed by a computer program written in MATLAB language over one complete revolution of the crank shaft. The results are compared with a finite element simulation carried out by using ANSYS Workbench software and are found to be in good agreement. A graphical method (relative velocity and acceleration method) has been also applied for two phases of the crank shaft (q2 = 10° and 130°). The results obtained from this method (graphical) are compared with those obtained from analytical and numerical method and are found very acceptable. To make the analysis linear the friction force on the joints and sliding interface are neglected. All results, in this work, are obtained when the crank shaft turns at a uniform angular velocity (w2 = 188.5 rad/s) and time dependent gas pressure force on the slider crown.


Author(s):  
Xiang Qian Shi ◽  
Ho Lam Heung ◽  
Zhi Qiang Tang ◽  
Kai Yu Tong ◽  
Zheng Li

Stroke has been the leading cause of disability due to the induced spasticity in the upper extremity. The constant flexion of spastic fingers following stroke has not been well described. Accurate measurements for joint stiffness help clinicians have a better access to the level of impairment after stroke. Previously, we conducted a method for quantifying the passive finger joint stiffness based on the pressure-angle relationship between the spastic fingers and the soft-elastic composite actuator (SECA). However, it lacks a ground-truth to demonstrate the compatibility between the SECA-facilitated stiffness estimation and standard joint stiffness quantification procedure. In this study, we compare the passive metacarpophalangeal (MCP) joint stiffness measured using the SECA with the results from our designed standalone mechatronics device, which measures the passive metacarpophalangeal joint torque and angle during passive finger rotation. Results obtained from the fitting model that concludes the stiffness characteristic are further compared with the results obtained from SECA-Finger model, as well as the clinical score of Modified Ashworth Scale (MAS) for grading spasticity. These findings suggest the possibility of passive MCP joint stiffness quantification using the soft robotic actuator during the performance of different tasks in hand rehabilitation.


Biomechanics ◽  
2021 ◽  
Vol 1 (1) ◽  
pp. 102-117
Author(s):  
Nasser Rezzoug ◽  
Vincent Hernandez ◽  
Philippe Gorce

A force capacity evaluation for a given posture may provide better understanding of human motor abilities for applications in sport sciences, rehabilitation and ergonomics. From data on posture and maximum isometric joint torques, the upper-limb force feasible set of the hand was predicted by four models called force ellipsoid, scaled force ellipsoid, force polytope and scaled force polytope, which were compared with a measured force polytope. The volume, shape and force prediction errors were assessed. The scaled ellipsoid underestimated the maximal mean force, and the scaled polytope overestimated it. The scaled force ellipsoid underestimated the volume of the measured force distribution, whereas that of the scaled polytope was not significantly different from the measured distribution but exhibited larger variability. All the models characterized well the elongated shape of the measured force distribution. The angles between the main axes of the modelled ellipsoids and polytopes and that of the measured polytope were compared. The values ranged from 7.3° to 14.3°. Over the entire surface of the force ellipsoid, 39.7% of the points had prediction errors less than 50 N; 33.6% had errors between 50 and 100 N; and 26.8% had errors greater than 100N. For the force polytope, the percentages were 56.2%, 28.3% and 15.4%, respectively.


2021 ◽  
Vol 6 (1) ◽  
pp. 103-110
Author(s):  
Kyu Min Park ◽  
Jihwan Kim ◽  
Jinhyuk Park ◽  
Frank C. Park

2017 ◽  
Vol 37 (1) ◽  
pp. 1-12 ◽  
Author(s):  
Haluk Ay ◽  
Anthony Luscher ◽  
Carolyn Sommerich

Purpose The purpose of this study is to design and develop a testing device to simulate interaction between human hand–arm dynamics, right-angle (RA) computer-controlled power torque tools and joint-tightening task-related variables. Design/methodology/approach The testing rig can simulate a variety of tools, tasks and operator conditions. The device includes custom data-acquisition electronics and graphical user interface-based software. The simulation of the human hand–arm dynamics is based on the rig’s four-bar mechanism-based design and mechanical components that provide adjustable stiffness (via pneumatic cylinder) and mass (via plates) and non-adjustable damping. The stiffness and mass values used are based on an experimentally validated hand–arm model that includes a database of model parameters. This database is with respect to gender and working posture, corresponding to experienced tool operators from a prior study. Findings The rig measures tool handle force and displacement responses simultaneously. Peak force and displacement coefficients of determination (R2) between rig estimations and human testing measurements were 0.98 and 0.85, respectively, for the same set of tools, tasks and operator conditions. The rig also provides predicted tool operator acceptability ratings, using a data set from a prior study of discomfort in experienced operators during torque tool use. Research limitations/implications Deviations from linearity may influence handle force and displacement measurements. Stiction (Coulomb friction) in the overall rig, as well as in the air cylinder piston, is neglected. The rig’s mechanical damping is not adjustable, despite the fact that human hand–arm damping varies with respect to gender and working posture. Deviations from these assumptions may affect the correlation of the handle force and displacement measurements with those of human testing for the same tool, task and operator conditions. Practical implications This test rig will allow the rapid assessment of the ergonomic performance of DC torque tools, saving considerable time in lineside applications and reducing the risk of worker injury. DC torque tools are an extremely effective way of increasing production rate and improving torque accuracy. Being a complex dynamic system, however, the performance of DC torque tools varies in each application. Changes in worker mass, damping and stiffness, as well as joint stiffness and tool program, make each application unique. This test rig models all of these factors and allows quick assessment. Social implications The use of this tool test rig will help to identify and understand risk factors that contribute to musculoskeletal disorders (MSDs) associated with the use of torque tools. Tool operators are subjected to large impulsive handle reaction forces, as joint torque builds up while tightening a fastener. Repeated exposure to such forces is associated with muscle soreness, fatigue and physical stress which are also risk factors for upper extremity injuries (MSDs; e.g. tendinosis, myofascial pain). Eccentric exercise exertions are known to cause damage to muscle tissue in untrained individuals and affect subsequent performance. Originality/value The rig provides a novel means for quantitative, repeatable dynamic evaluation of RA powered torque tools and objective selection of tightening programs. Compared to current static tool assessment methods, dynamic testing provides a more realistic tool assessment relative to the tool operator’s experience. This may lead to improvements in tool or controller design and reduction in associated musculoskeletal discomfort in operators.


Author(s):  
Soumya K Manna ◽  
Venketesh N Dubey

Intensive and adaptive rehabilitation therapy is beneficial for post-stroke recovery. Three modes of rehabilitation are generally performed at different stages after stroke: external force-based control in the acute stage, assistive force-based rehabilitation in the midway of recovery and resistive force-based rehabilitation in the last stage. To achieve the above requirements, an innovative elbow exoskeleton has been developed to incorporate the three modes of rehabilitation in a single structure. The structure of the exoskeleton has been designed in such a way that the whole working region is divided into three where each region can provide a different mode of rehabilitation. Recovery rate can be varied for individuals since it depends on various parameters. To evaluate the rate of recovery, three joint parameters have been identified: range of angular movement, angular velocity and joint torque. These parameters are incorporated into the framework of planning a novel rehabilitation strategy, which is discussed in this article along with the structural description of the designed exoskeleton.


Author(s):  
Rahid Zaman ◽  
Yujiang Xiang ◽  
Jazmin Cruz ◽  
James Yang

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.


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