Accuracy of Position Recognition for Extra Robotic Prosthesis Control Based on Different Position Feedback

Author(s):  
Takayuki ITO ◽  
Yasuhisa HASEGAWA
Author(s):  
G. A. Ribeiro ◽  
M. Rastgaar

The field of control of powered lower-leg prostheses has advanced due to the improvements in sensors and computational power. Much effort has been done to improve the capabilities of prostheses, such as mimicking the stiffness, weight, and mobility of a human ankle-foot [1] and autonomously commanding the robotic prosthesis for gait [2].


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Rob Bogue

Purpose This paper aims to provide details of recent advances in robotic prostheses with the emphasis on the control and sensing technologies. Design/methodology/approach Following a short introduction, this paper first discusses the main robotic prosthesis control strategies. It then provides details of recent research and developments using non-invasive and invasive brain–computer interfaces (BCIs). These are followed by examples of studies that seek to confer robotic prostheses with sensory feedback. Finally, brief conclusions are drawn. Findings A significant body of research is underway involving electromyographic and BCI technologies, often in combination with advanced data processing and analysis schemes. This has the potential to yield robotic prostheses with advanced capabilities such as greater dexterity and sensory feedback. Originality/value This illustrates how electromyographic, BCI, signal processing and sensor technologies are being used to create robotic prostheses with enhanced functionality.


2021 ◽  
Vol 1828 (1) ◽  
pp. 012056
Author(s):  
Michael Pritchard ◽  
Abraham Itzhak Weinberg ◽  
John A R Williams ◽  
Felipe Campelo ◽  
Harry Goldingay ◽  
...  

2005 ◽  
Vol 21 (07) ◽  
Author(s):  
Hakim Said ◽  
Todd Kuiken ◽  
Robert Lipzchutz ◽  
Laura Miller ◽  
Gregory Dumanian

Processes ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 1195
Author(s):  
Jianhua Zhao ◽  
Yongqiang Wang ◽  
Xuchao Ma ◽  
Sheng Li ◽  
Dianrong Gao ◽  
...  

As a new type of suspension bearing, the magnetic liquid double suspension bearing (MLDSB) is mainly supported by electromagnetic suspension and supplemented by hydrostatic support. At present, the MLDSB adopts the regulation strategy of “electromagnetic-position feedback closed-loop, hydrostatic constant-flow supply” (referred to as CFC mode). In the equilibrium position, the external load is carried by the electromagnetic system, and the hydrostatic system produces no supporting force. Thus, the carrying capacity and supporting stiffness of the MLDSB can be reduced. To solve this problem, the double closed-loop control strategy of “electromagnetic system-force feedback inner loop and hydrostatic-position feedback outer loop” (referred to as DCL mode) was proposed to improve the bearing performance and operation stability of the MLDSB. First, the mathematical models of CFC mode and DCL mode of the single DOF supporting system were established. Second, the real-time variation laws of rotor displacement, flow/hydrostatic force, and regulating current/electromagnetic force in the two control modes were plotted, compared, and analyzed. Finally, the influence law of initial current, flow, and controller parameters on the dynamic and static characteristic index were analyzed in detail. The results show that compared with that in CFC mode, the displacement in DCL mode is smaller, and the adjustment time is shorter. The hydrostatic force is equal to the electromagnetic force in DCL mode when the rotor returns to the balance position. Moreover, the system in DCL mode has better robustness, and the initial flow has a more obvious influence on the dynamic and static characteristic indexes. This study provides a theoretical basis for stable suspension control and the safe and reliable operation of the MLDSB.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Eric J. Earley ◽  
Reva E. Johnson ◽  
Jonathon W. Sensinger ◽  
Levi J. Hargrove

AbstractAccurate control of human limbs involves both feedforward and feedback signals. For prosthetic arms, feedforward control is commonly accomplished by recording myoelectric signals from the residual limb to predict the user’s intent, but augmented feedback signals are not explicitly provided in commercial devices. Previous studies have demonstrated inconsistent results when artificial feedback was provided in the presence of vision; some studies showed benefits, while others did not. We hypothesized that negligible benefits in past studies may have been due to artificial feedback with low precision compared to vision, which results in heavy reliance on vision during reaching tasks. Furthermore, we anticipated more reliable benefits from artificial feedback when providing information that vision estimates with high uncertainty (e.g. joint speed). In this study, we test an artificial sensory feedback system providing joint speed information and how it impacts performance and adaptation during a hybrid positional-and-myoelectric ballistic reaching task. We found that overall reaching errors were reduced after perturbed control, but did not significantly improve steady-state reaches. Furthermore, we found that feedback about the joint speed of the myoelectric prosthesis control improved the adaptation rate of biological limb movements, which may have resulted from high prosthesis control noise and strategic overreaching with the positional control and underreaching with the myoelectric control. These results provide insights into the relevant factors influencing the improvements conferred by artificial sensory feedback.


Author(s):  
S. Zohar ◽  
D. J. Kissick ◽  
N. Venugopalan ◽  
C. M. Ogata ◽  
O. Makarov ◽  
...  

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