Improved haptic rendering through tuning the mechanical impedance of human arm

2011 ◽  
Author(s):  
Xiong Lu ◽  
Ai-guo Song ◽  
Yong-qiang Ye
Keyword(s):  
Mechanical Impedance ◽  
Haptic Rendering ◽  
Human Arm

A Human Arm’s Mechanical Impedance Tuning Method for Improving the Stability of Haptic Rendering

Robotica ◽  
2020 ◽  
pp. 1-13
Author(s):  
Xiong Lu ◽  
Beibei Qi ◽  
Hao Zhao ◽  
Junbin Sun
Keyword(s):  
Degrees Of Freedom ◽  
External Disturbance ◽  
Mechanical Impedance ◽  
System Stability ◽  
Tuning Method ◽  
Rigid Objects ◽  
Human Arm ◽  
Human Operators ◽  
And Performance ◽  
The Stability

SUMMARY Rendering of rigid objects with high stiffness while guaranteeing system stability remains a major and challenging issue in haptics. Being a part of the haptic system, the behavior of human operators, represented as the mechanical impedance of arm, has an inevitable influence on system performance. This paper first verified that the human arm impedance can unconsciously be modified through imposing background forces and resist unstable motions arising from external disturbance forces. Then, a reliable impedance tuning (IT) method for improving the stability and performance of haptic systems is proposed, which tunes human arm impedance by superimposing a position-based background force over the traditional haptic workspace. Moreover, an adaptive IT algorithm, adjusting the maximum background force based on the velocity of the human arm, is proposed to achieve a reasonable trade-off between system stability and transparency. Based on a three-degrees-of-freedom haptic device, maximum achievable stiffness and transparency grading experiments are carried out with 12 subjects, which verify the efficacy and advantage of the proposed method.

Regulation of 3D Human Arm Impedance Through Muscle Co-Contraction

2013 ◽  
Author(s):  
Harshil Patel ◽  
Gerald O’Neill ◽  
Panagiotis Artemiadis
Keyword(s):  
Dimensional Space ◽  
Human Subjects ◽  
Three Dimensional ◽  
Mechanical Impedance ◽  
Dominant Factor ◽  
Robot Arm ◽  
End Point ◽  
Human Arm ◽  
Arm Muscles ◽  
Experimental Trials

Humans have the inherent ability of performing highly dexterous and skillful tasks with their arms, involving maintenance of posture, movement, and interaction with the environment. The latter requires the human to control the dynamic characteristics of the upper limb musculoskeletal system. These characteristics are quantitatively represented by inertia, damping, and stiffness, which are measures of mechanical impedance. Many previous studies have shown that arm posture is a dominant factor in determining the end point impedance on a horizontal (transverse) plane. This paper presents the characterization of the end point impedance of the human arm in three-dimensional space. Moreover, it models the regulation of the arm impedance with respect to various levels of muscle co-contraction. The characterization is made by route of experimental trials where human subjects maintained arm posture while their arms were perturbed by a robot arm. Furthermore, the subjects were asked to control the level of their arm muscles’ co-contraction, using visual feedback of their muscles’ activation, in order to investigate the effect of this muscle co-contraction on the arm impedance. The results of this study show a very interesting, anisotropic increase of arm stiffness due to muscle co-contraction. These results could lead to very useful conclusions about the human’s arm biomechanics, as well as many implications for human motor control-specifically the control of arm impedance through muscle co-contraction.

Analysis of mechanical impedance in human arm movements using a virtual tennis system

2004 ◽  
Vol 91 (5) ◽  
pp. 295-305 ◽  
Author(s):  
Toshio Tsuji ◽  
Yusaku Takeda ◽  
Yoshiyuki Tanaka
Keyword(s):  
Arm Movements ◽  
Mechanical Impedance ◽  
Human Arm ◽  
Human Arm Movements

Virtual Driving Simulator for Measuring Dynamic Properties of Human Arm Movements

2006 ◽  
Vol 18 (2) ◽  
pp. 177-185 ◽  
Author(s):  
Yoshiyuki Tanaka ◽  
◽  
Ryoma Kanda ◽  
Naoki Yamada ◽  
Hitoshi Fukuba ◽  
...  
Keyword(s):  
Driving Simulator ◽  
Impedance Control ◽  
Dynamic Properties ◽  
Mechanical Impedance ◽  
Rotational Axis ◽  
Human Movements ◽  
Human Arm ◽  
Robotic Devices ◽  
Impedance Parameters ◽  
Machine Systems

This paper presents a virtual driving simulator using robotic devices as an example of human-machine systems to investigate dynamic properties of human movements in the operation of drive interfaces, such as steering wheels and transmission shifters. The simulator has virtual steering and transmission systems under variable impedance control, providing the operators with realistic operational response. Mechanical impedance parameters around the steering rotational axis were measured to demonstrate the effectiveness of the developed simulator.

scholarly journals A safe human–robot interactive control structure with human arm movement detection for an upper-limb wearable robot used during lifting tasks

2020 ◽  
Vol 17 (5) ◽  
pp. 172988142093757
Author(s):  
Lina Hao ◽  
Zhirui Zhao ◽  
Xing Li ◽  
Mingfang Liu ◽  
Hui Yang ◽  
...  
Keyword(s):  
Upper Limb ◽  
Elbow Joint ◽  
Control Structure ◽  
Biceps Brachii ◽  
Arm Movement ◽  
Mechanical Impedance ◽  
Erector Spinae ◽  
Movement Detection ◽  
Wearable Robot ◽  
Human Arm

Manual lifting tasks involve repetitive raising, holding and stacking movements with heavy objects. These arm movements are notable risk factors for muscle pain, fatigue, and musculoskeletal disorders in workers. An upper-limb wearable robot, as a 6-DOF dual-arm exoskeleton, which was designed to augment workers’ strength and minimize muscular activation in the arm during repetitive lifting tasks. To adjust the robot joint trajectory, the user needs to apply an interactive torque to operate the robot during lifting tasks when a standard virtual mechanical impedance control structure is used. To reduce overshooting of the interactive torque on the user’s joint, a three-tier hierarchical control structure was developed for the robot in this study. At the highest level, a human arm movement detection module is used to detect the user’s arm motion according to the surface electromyography signals. Then, a Hammerstein adaptive virtual mechanical impedance controller is used at the middle level to reduce overshooting and yield an acceptable value of torque for the user’s elbow joint in actual lifting tasks. At the lowest level, the actuator controller on each joint of the robot controls the robot to complete lifting tasks. Several experiments were conducted, and the results showed that the interactive torque on the user’s elbow was limited and the muscular activations of erector spinae and biceps brachii muscles were effectively decreased. The proposed scheme prevents potential harm to the user due to excessive interactive torque on the human elbow joint, such as related muscle fatigue and joint injuries.

Estimation and Kinetic Modeling of Human Arm using Wearable Robot Arm

2016 ◽  
Vol 136 (4) ◽  
pp. 254-262 ◽  
Author(s):  
Takahiro Yamazaki ◽  
Sho Sakaino ◽  
Toshiaki Tsuji
Keyword(s):  
Kinetic Modeling ◽  
Robot Arm ◽  
Wearable Robot ◽  
Human Arm
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