scholarly journals Evaluating Internal Model Strength and Performance of Myoelectric Prosthesis Control Strategies

2018 ◽  
Vol 26 (5) ◽  
pp. 1046-1055 ◽  
Author(s):  
Ahmed W. Shehata ◽  
Erik J. Scheme ◽  
Jonathon W. Sensinger
Keyword(s):  
Internal Model ◽  
Control Strategies ◽  
Myoelectric Prosthesis ◽  
And Performance ◽  
Prosthesis Control ◽  
Model Strength

scholarly journals Evaluating Internal Model Strength and Performance of Myoelectric Prosthesis Control Strategies

2017 ◽  
Author(s):  
Ahmed W. Shehata ◽  
Erik J. Scheme ◽  
Jonathon W. Sensinger
Keyword(s):  
Internal Model ◽  
Control Strategies ◽  
Model Development ◽  
Myoelectric Control ◽  
Myoelectric Prosthesis ◽  
And Performance ◽  
Prosthesis Control ◽  
Long Term Performance ◽  
Term Performance

AbstractOngoing developments in myoelectric prosthesis control have provided prosthesis users with an assortment of control strategies that vary in reliability and performance. Many studies have focused on improving performance by providing feedback to the user, but have overlooked the effect of this feedback on internal model development, which is key to improving long-term performance. In this work, the strength of internal models developed for two commonly used myoelectric control strategies: raw control with raw feedback (using a regression-based approach), and filtered control with filtered feedback (using a classifier-based approach), were evaluated using two psychometric measures: trial-by-trial adaptation and just-noticeable-difference. The performance of both strategies was also evaluated using a Schmidt’s style target acquisition task. Results obtained from 24 able-bodied subjects showed that although filtered control with filtered feedback had better short-term performance in path efficiency (p < 0.05), raw control with raw feedback resulted in stronger internal model development (p < 0.05), which may lead to better long-term performance. Despite inherent noise in the control signals of the regression controller, these findings suggest that rich feedback associated with regression control may be used to improve human understanding of the myoelectric control system.

scholarly journals Audible Feedback Improves Internal Model Strength and Performance of Myoelectric Prosthesis Control

2018 ◽  
Author(s):  
Ahmed W. Shehata ◽  
Erik J. Scheme ◽  
Jonathon W. Sensinger
Keyword(s):  
Feedback Control ◽  
Internal Model ◽  
Control Strategies ◽  
Short Term ◽  
Augmented Feedback ◽  
Myoelectric Prosthesis ◽  
Prosthetic Devices ◽  
Long Term Performance ◽  
Term Performance

AbstractMyoelectric prosthetic devices are commonly used to help upper limb amputees perform activities of daily living, however amputees still lack the sensory feedback required to facilitate reliable and precise control. Augmented feedback may play an important role in affecting both short-term performance, through real-time regulation, and long-term performance, through the development of stronger internal models. In this work, we investigate the potential tradeoff between controllers that enable better short-term performance and those that provide sufficient feedback to develop a strong internal model. We hypothesize that augmented feedback may be used to mitigate this tradeoff, ultimately improving both short and long-term control. We used psychometric measures to assess the internal model developed while using a filtered myoelectric controller with augmented audio feedback, imitating classification-based control but with augmented regression-based feedback. In addition, we evaluated the short-term performance using a multi degree-of-freedom constrained-time target acquisition task. Results obtained from 24 able-bodied subjects show that an augmented feedback control strategy using audio cues enables the development of a stronger internal model than the filtered control with filtered feedback, and significantly better path efficiency than both raw and filtered control strategies. These results suggest that the use of augmented feedback control strategies may improve both short-term and long-term performance.

scholarly journals Improving internal model strength and performance of prosthetic hands using augmented feedback

2018 ◽  
Vol 15 (1) ◽  
Author(s):  
Ahmed W. Shehata ◽  
Leonard F. Engels ◽  
Marco Controzzi ◽  
Christian Cipriani ◽  
Erik J. Scheme ◽  
...  
Keyword(s):  
Internal Model ◽  
Augmented Feedback ◽  
Prosthetic Hands ◽  
And Performance ◽  
Model Strength

Nerve Transfers in Transhumeral Amputation: Creating Myoneurosomes for Improved Myoelectric Prosthesis Control

2005 ◽  
Vol 21 (07) ◽  
Author(s):  
Hakim Said ◽  
Todd Kuiken ◽  
Robert Lipzchutz ◽  
Laura Miller ◽  
Gregory Dumanian
Keyword(s):  
Myoelectric Prosthesis ◽  
Nerve Transfers ◽  
Prosthesis Control

Effects of control strategy on the activation of unwanted intrusive thoughts

2020 ◽  
Author(s):  
Sicong Liu ◽  
Jonathan Folstein ◽  
Lawrence Gregory Appelbaum ◽  
Gershon Tenenbaum
Keyword(s):  
Control Strategies ◽  
Working Memory Capacity ◽  
Intrusive Thoughts ◽  
Control Process ◽  
Event Related Potentials ◽  
Human Beings ◽  
Opposite Pattern ◽  
Thought Control ◽  
Related Potentials ◽  
And Performance

Although the unwanted intrusive thoughts (UITs) exist widely in human beings and show similar characteristics between clinical and nonclinical forms, its control process remains unclear. Thoughts of choking under pressure, particularly among high-achieving athletes, represent a meaningful UIT type due to their psychological and performance-related impact. Taking a dynamic view of UIT control process, this study tested the effect of thought-control strategies among sub-elite to elite athletes, applied to individualized choking thoughts. Ninety athletes recollected recent athletic choking experiences prior to being randomized into one of three thought control interventions using strategies of either acceptance, passive monitoring (control), or suppression. To control for individual differences, athletes’ working memory capacity was measured and modeled as a covariate at baseline. The activation of choking thoughts during and after the intervention was gauged through multiple measurement approaches including conscious presence in mind, priming, and event-related potentials (P3b and N400 amplitudes). Results indicated that, relative to the control, suppression led to enhanced priming and reduced conscious presence of choking thoughts, whereas acceptance resulted in an opposite pattern of reduced priming and increased conscious presence of choking thoughts. In addition, thought-related stimuli elicited less negative-going N400 amplitudes and more positive-going P3b amplitudes than control stimuli. These findings advance understandings of the control mechanism underpinning UITs, and generate applied implications regarding UIT control in high-risk populations such as those with athletic expertise.

scholarly journals Joint speed feedback improves myoelectric prosthesis adaptation after perturbed reaches in non amputees

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Eric J. Earley ◽  
Reva E. Johnson ◽  
Jonathon W. Sensinger ◽  
Levi J. Hargrove
Keyword(s):  
Sensory Feedback ◽  
Feedforward Control ◽  
Feedback System ◽  
Augmented Feedback ◽  
Myoelectric Prosthesis ◽  
Reaching Task ◽  
Prosthesis Control ◽  
High Uncertainty ◽  
Relevant Factors ◽  
Positional Control

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.

Real time ECG artifact removal for myoelectric prosthesis control

2007 ◽  
Vol 28 (4) ◽  
pp. 397-413 ◽  
Author(s):  
Ping Zhou ◽  
Blair Lock ◽  
Todd A Kuiken
Keyword(s):  
Real Time ◽  
Artifact Removal ◽  
Myoelectric Prosthesis ◽  
Prosthesis Control
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