The impact of objective functions on control policies in closed-loop control of grasping force with a myoelectric prosthesis

Author(s):  
Pranav Mamidanna ◽  
Jakob Lund Dideriksen ◽  
Strahinja Dosen
2012 ◽  
Vol 220 (1) ◽  
pp. 3-9 ◽  
Author(s):  
Sandra Sülzenbrück

For the effective use of modern tools, the inherent visuo-motor transformation needs to be mastered. The successful adjustment to and learning of these transformations crucially depends on practice conditions, particularly on the type of visual feedback during practice. Here, a review about empirical research exploring the influence of continuous and terminal visual feedback during practice on the mastery of visuo-motor transformations is provided. Two studies investigating the impact of the type of visual feedback on either direction-dependent visuo-motor gains or the complex visuo-motor transformation of a virtual two-sided lever are presented in more detail. The findings of these studies indicate that the continuous availability of visual feedback supports performance when closed-loop control is possible, but impairs performance when visual input is no longer available. Different approaches to explain these performance differences due to the type of visual feedback during practice are considered. For example, these differences could reflect a process of re-optimization of motor planning in a novel environment or represent effects of the specificity of practice. Furthermore, differences in the allocation of attention during movements with terminal and continuous visual feedback could account for the observed differences.


Author(s):  
Liliana P Paredes ◽  
Strahinja Dosen ◽  
Frank Rattay ◽  
Bernhard Graimann ◽  
Dario Farina

Author(s):  
Ethan Sorrell ◽  
Michael E. Rule ◽  
Timothy O’Leary

Brain–machine interfaces (BMIs) promise to restore movement and communication in people with paralysis and ultimately allow the human brain to interact seamlessly with external devices, paving the way for a new wave of medical and consumer technology. However, neural activity can adapt and change over time, presenting a substantial challenge for reliable BMI implementation. Large-scale recordings in animal studies now allow us to study how behavioral information is distributed in multiple brain areas, and state-of-the-art interfaces now incorporate models of the brain as a feedback controller. Ongoing research aims to understand the impact of neural plasticity on BMIs and find ways to leverage learning while accommodating unexpected changes in the neural code. We review the current state of experimental and clinical BMI research, focusing on what we know about the neural code, methods for optimizing decoders for closed-loop control, and emerging strategies for addressing neural plasticity. Expected final online publication date for the Annual Review of Control, Robotics, and Autonomous Systems, Volume 4 is May 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.


2012 ◽  
Vol 253-255 ◽  
pp. 2117-2120
Author(s):  
Yu Zhuo Men ◽  
Hai Bo Yu ◽  
Xian Sheng Li ◽  
Yue Wei Li

In order to study the impact of the suspension damping system on the vehicle riding stability, the PID controlling means for suspension damped neural network is presented, implementing a closed-loop control of yaw stability for vehicles. For the two typical working conditions of single lane changing and step steering, the MATLAB software is used for simulation. The result shows that controlling over the vehicle’s lateral deviation movement through suspension damper, it can reduce significantly the load transfers of both the left wheels and right wheels, so that to effectively restrain a vehicle’s over-steering.


Author(s):  
Strahinja Dosen ◽  
Marko Markovic ◽  
Matija Strbac ◽  
Minja Belic ◽  
Vladimir Kojic ◽  
...  

2021 ◽  
Vol 15 ◽  
Author(s):  
Jian Dong ◽  
Winnie Jensen ◽  
Bo Geng ◽  
Ernest Nlandu Kamavuako ◽  
Strahinja Dosen

AimLimb loss is a dramatic event with a devastating impact on a person’s quality of life. Prostheses have been used to restore lost motor abilities and cosmetic appearance. Closing the loop between the prosthesis and the amputee by providing somatosensory feedback to the user might improve the performance, confidence of the amputee, and embodiment of the prosthesis. Recently, a minimally invasive method, in which the electrodes are placed subdermally, was presented and psychometrically evaluated. The present study aimed to assess the quality of online control with subdermal stimulation and compare it to that achieved using surface stimulation (common benchmark) as well as to investigate the impact of training on the two modalities.MethodsTen able-bodied subjects performed a PC-based compensatory tracking task. The subjects employed a joystick to track a predefined pseudorandom trajectory using feedback on the momentary tracking error, which was conveyed via surface and subdermal electrotactile stimulation. The tracking performance was evaluated using the correlation coefficient (CORR), root mean square error (RMSE), and time delay between reference and generated trajectories.ResultsBoth stimulation modalities resulted in good closed-loop control, and surface stimulation outperformed the subdermal approach. There was significant difference in CORR (86 vs 77%) and RMSE (0.23 vs 0.31) between surface and subdermal stimulation (all p < 0.05). The RMSE of the subdermal stimulation decreased significantly in the first few trials.ConclusionSubdermal stimulation is a viable method to provide tactile feedback. The quality of online control is, however, somewhat worse compared to that achieved using surface stimulation. Nevertheless, due to minimal invasiveness, compactness, and power efficiency, the subdermal interface could be an attractive solution for the functional application in sensate prostheses.


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