scholarly journals Position Control of a Soft Prosthetic Finger with Limited Feedback Information

2018 ◽  
Author(s):  
S. Kumbay Yildiz ◽  
R. Mutlu ◽  
G. Alici
Keyword(s):  
Position Control ◽  
Limited Feedback ◽  
Feedback Information ◽  
Prosthetic Finger

Teleoperation of Autonomous Mobile Robot under Limited Feedback Information

1998 ◽  
pp. 146-151 ◽  
Author(s):  
Kuniaki Kawabata ◽  
Tatsuya Ishikawa ◽  
Teruo Fujii ◽  
Takashi Noguchi ◽  
Hajime Asama ◽  
...  
Keyword(s):  
Mobile Robot ◽  
Limited Feedback ◽  
Autonomous Mobile Robot ◽  
Feedback Information

scholarly journals Effect of user adaptation on prosthetic finger control with an intuitive myoelectric decoder

2019 ◽  
Author(s):  
Agamemnon Krasoulis ◽  
Sethu Vijayakumar ◽  
Kianoush Nazarpour
Keyword(s):  
Real Time ◽  
Position Control ◽  
Myoelectric Control ◽  
Continuous Control ◽  
Activation Patterns ◽  
User Adaptation ◽  
Short Term Adaptation ◽  
Prosthesis Control ◽  
Prosthetic Finger ◽  
Finger Control

ABSTRACTMachine learning-based myoelectric control is regarded as an intuitive paradigm, because of the mapping it creates between muscle co-activation patterns and prosthesis movements that aims to simulate the physiological pathways found in the human arm. Despite that, there has been evidence that closed-loop interaction with a classification-based interface results in user adaptation, which leads to performance improvement with experience. Recently, there has been a focus shift towards continuous prosthesis control, yet little is known about whether and how user adaptation affects myoelectric control performance in dexterous, intuitive tasks. We investigate the effect of short-term adaptation with independent finger position control by conducting real-time experiments with 10 able-bodied and two transradial amputee subjects. We demonstrate that despite using an intuitive decoder, experience leads to significant improvements in performance. We argue that this is due to the lack of an utterly natural control scheme, which is mainly caused by differences in the anatomy of human and artificial hands, movement intent decoding inaccuracies, and lack of proprioception. Finally, we extend previous work in classification-based and wrist continuous control by verifying that offline analyses cannot reliably predict real-time performance, thereby reiterating the importance of validating myoelectric control algorithms with real-time experiments.

Closed-loop control of a prosthetic finger via evoked proprioceptive information

2021 ◽  
Author(s):  
Luis Vargas ◽  
He (Helen) Huang ◽  
Yong Zhu ◽  
Xiaogang Hu
Keyword(s):  
Closed Loop ◽  
Position Control ◽  
Sensory Information ◽  
Proprioceptive Feedback ◽  
Closed Loop Control ◽  
Proprioceptive Information ◽  
Continuous Control ◽  
Velocity Control ◽  
Loop Control ◽  
Prosthetic Finger

Abstract Objective. Proprioceptive information plays an important role for recognizing and coordinating our limb’s static and dynamic states relative to our body or the environment. In this study, we determined how artificially evoked proprioceptive feedback affected the continuous control of a prosthetic finger. Approach. We elicited proprioceptive information regarding the joint static position and dynamic movement of a prosthetic finger via a vibrotactor array placed around the subject’s upper arm. Myoelectric signals of the finger flexor and extensor muscles were used to control the prosthesis, with or without the evoked proprioceptive feedback. Two control modes were evaluated: the myoelectric signal amplitudes were continuously mapped to either the position or the velocity of the prosthetic joint. Main Results. Our results showed that the evoked proprioceptive information improved the control accuracy of the joint angle, with comparable performance in the position- and velocity-control conditions. However, greater angle variability was prominent during position-control than velocity-control. Without the proprioceptive feedback, the position-control tended to show a smaller angle error than the velocity-control condition. Significance. Our findings suggest that closed-loop control of a prosthetic device can potentially be achieved using non-invasive evoked proprioceptive feedback delivered to intact participants. Moreover, the evoked sensory information was integrated during myoelectric control effectively for both control strategies. The outcomes can facilitate our understanding of the sensorimotor integration process during human-machine interactions, which can potentially promote fine control of prosthetic hands.

TAS Protocols of a PASD System with Limited Feedback Information

2009 ◽  
Author(s):  
Sang Joon Kim ◽  
Saeed S. Ghassemzadeh ◽  
Robert R. Miller ◽  
Vahid Tarokh
Keyword(s):  
Limited Feedback ◽  
Feedback Information
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