Nussbaum-type Neural Network-based Control of Neuromuscular Electrical Stimulation with Input Saturation and Muscle Fatigue

2021 ◽  
Author(s):  
Chen Rui ◽  
Jie Li ◽  
Yinhe Chen ◽  
Qing Zhang ◽  
Ruzhou Yang ◽  
...  
Keyword(s):  
Neural Network ◽  
Electrical Stimulation ◽  
Muscle Fatigue ◽  
Input Saturation ◽  
Angular Position ◽  
Neuromuscular Electrical Stimulation ◽  
External Disturbances ◽  
Adaptation Mechanism ◽  
Loop Control ◽  
First Time

Abstract Neuromuscular electrical stimulation is a promising technique to actuate the human musculoskeletal system in the presence of neurological impairments. The closed-loop control of NMES systems is non-trivial due to their inherent uncertain nonlinearity. In this paper, we propose a Nussbaum-type neural network-based controller for the lower leg limb NMES systems. The control accounts for model uncertainties and external disturbances in the system and, for the first time, provides a solution with rigorous stability analysis to the adaptive NMES tracking problem with input saturation and muscle fatigue. The proposed controller guarantees a uniformly ultimately bounded tracking for the knee joint angular position. To evaluate the control performance, a simulation study is taken, where the adaptation mechanism of the Nussbaum-type gain and the controller's robustness to muscle fatigue and input saturation are discussed.

Interleaved neuromuscular electrical stimulation reduces muscle fatigue

2016 ◽  
Vol 55 (2) ◽  
pp. 179-189 ◽  
Author(s):  
Jenny W.H. Lou ◽  
Austin J. Bergquist ◽  
Abdulaziz Aldayel ◽  
Jennifer Czitron ◽  
David F. Collins
Keyword(s):  
Electrical Stimulation ◽  
Muscle Fatigue ◽  
Neuromuscular Electrical Stimulation

scholarly journals Fuzzy-Based Optimal Adaptive Line-of-Sight Path Following for Underactuated Unmanned Surface Vehicle with Uncertainties and Time-Varying Disturbances

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Dongdong Mu ◽  
Guofeng Wang ◽  
Yunsheng Fan ◽  
Yiming Bai ◽  
Yongsheng Zhao
Keyword(s):  
Neural Network ◽  
Path Following ◽  
Line Of Sight ◽  
Time Varying ◽  
Parameter Learning ◽  
Learning Method ◽  
External Disturbances ◽  
Unmanned Surface Vehicle ◽  
Loop Control ◽  
Nussbaum Function

This paper investigates the path following control problem for an underactuated unmanned surface vehicle (USV) in the presence of dynamical uncertainties and time-varying external disturbances. Based on fuzzy optimization algorithm, an improved adaptive line-of-sight (ALOS) guidance law is proposed, which is suitable for straight-line and curve paths. On the basis of guidance information provided by LOS, a three-degree-of-freedom (DOF) dynamic model of an underactuated USV has been used to design a practical path following controller. The controller is designed by combining backstepping method, neural shunting model, neural network minimum parameter learning method, and Nussbaum function. Neural shunting model is used to solve the problem of “explosion of complexity,” which is an inherent illness of backstepping algorithm. Meanwhile, a simpler neural network minimum parameter learning method than multilayer neural network is employed to identify the uncertainties and time-varying external disturbances. In particular, Nussbaum function is introduced into the controller design to solve the problem of unknown control gain coefficient. And much effort is made to obtain the stability for the closed-loop control system, using the Lyapunov stability theory. Simulation experiments demonstrate the effectiveness and reliability of the improved LOS guidance algorithm and the path following controller.

scholarly journals Relationship Between Intensity of Quadriceps Muscle Neuromuscular Electrical Stimulation and Strength Recovery After Total Knee Arthroplasty

2012 ◽  
Vol 92 (9) ◽  
pp. 1187-1196 ◽  
Author(s):  
Jennifer E. Stevens-Lapsley ◽  
Jaclyn E. Balter ◽  
Pamela Wolfe ◽  
Donald G. Eckhoff ◽  
Robert S. Schwartz ◽  
...  
Keyword(s):  
Total Knee Arthroplasty ◽  
Electrical Stimulation ◽  
Muscle Strength ◽  
Muscle Fatigue ◽  
Knee Arthroplasty ◽  
Neuromuscular Electrical Stimulation ◽  
Quadriceps Muscle ◽  
Training Intensity ◽  
Quadriceps Muscle Strength ◽  
Total Knee

BackgroundNeuromuscular electrical stimulation (NMES) can facilitate the recovery of quadriceps muscle strength after total knee arthroplasty (TKA), yet the optimal intensity (dosage) of NMES and its effect on strength after TKA have yet to be determined.ObjectiveThe primary objective of this study was to determine whether the intensity of NMES application was related to the recovery of quadriceps muscle strength early after TKA. A secondary objective was to quantify quadriceps muscle fatigue and activation immediately after NMES to guide decisions about the timing of NMES during rehabilitation sessions.DesignThis study was an observational experimental investigation.MethodsData were collected from 30 people who were 50 to 85 years of age and who received NMES after TKA. These people participated in a randomized controlled trial in which they received either standard rehabilitation or standard rehabilitation plus NMES to the quadriceps muscle to mitigate strength loss. For the NMES intervention group, NMES was applied 2 times per day at the maximal tolerable intensity for 15 contractions beginning 48 hours after surgery over the first 6 weeks after TKA. Neuromuscular electrical stimulation training intensity and quadriceps muscle strength and activation were assessed before surgery and 3.5 and 6.5 weeks after TKA.ResultsAt 3.5 weeks, there was a significant association between NMES training intensity and a change in quadriceps muscle strength (R2=.68) and activation (R2=.22). At 6.5 weeks, NMES training intensity was related to a change in strength (R2=.25) but not to a change in activation (R2=.00). Furthermore, quadriceps muscle fatigue occurred during NMES sessions at 3.5 and 6.5 weeks, whereas quadriceps muscle activation did not change.LimitationsSome participants reached the maximal stimulator output during at least 1 treatment session and might have tolerated more stimulation.ConclusionsHigher NMES training intensities were associated with greater quadriceps muscle strength and activation after TKA.

Identifying the knee joint angular position under neuromuscular electrical stimulation via long short-term memory neural networks

2020 ◽  
Vol 36 (4) ◽  
pp. 511-526
Author(s):  
Héber H. Arcolezi ◽  
Willian R. B. M. Nunes ◽  
Selene Cerna ◽  
Rafael A. de Araujo ◽  
Marcelo Augusto Assunção Sanches ◽  
...  
Keyword(s):  
Neural Networks ◽  
Electrical Stimulation ◽  
Knee Joint ◽  
Short Term Memory ◽  
Angular Position ◽  
Neuromuscular Electrical Stimulation ◽  
Short Term ◽  
Term Memory ◽  
Long Short Term Memory

Robust Adaptive Control of the Nonlinearly Parameterized Human Shank Dynamics for Electrical Stimulation Applications

2018 ◽  
Vol 140 (8) ◽  
Author(s):  
Ruzhou Yang ◽  
Marcio de Queiroz
Keyword(s):  
Electrical Stimulation ◽  
Motion Tracking ◽  
Angular Position ◽  
Neuromuscular Electrical Stimulation ◽  
Robust Adaptive Control ◽  
Unknown Parameters ◽  
Control Laws ◽  
Adaptive Controllers ◽  
Nonlinearly Parameterized ◽  
Robust Adaptive

In this paper, we introduce two robust adaptive controllers for the human shank motion tracking problem that is inherent in neuromuscular electrical stimulation (NMES) systems. The control laws adaptively compensate for the unknown parameters that appear nonlinearly in the musculoskeletal dynamics while providing robustness to additive disturbance torques. The adaptive schemes exploit the Lipschitzian and/or the concave/convex parameterizations of the model functions. The resulting control laws are continuous and guarantee practical tracking for the shank angular position. The performance of the two robust adaptive controllers is demonstrated via simulations.

scholarly journals Closed-loop neuromuscular electrical stimulation using feedforward-feedback control and textile electrodes to regulate grasp force in quadriplegia

2019 ◽  
Vol 5 (1) ◽  
Author(s):  
John Ciancibello ◽  
Kevin King ◽  
Milad Alizadeh Meghrazi ◽  
Subash Padmanaban ◽  
Todd Levy ◽  
...  
Keyword(s):  
Electrical Stimulation ◽  
Feedback Control ◽  
Closed Loop ◽  
Neuromuscular Electrical Stimulation ◽  
Study Participant ◽  
Loop Control ◽  
Individual Finger ◽  
Finger Flexion ◽  
Study Team ◽  
Grasp Force

Abstract Background Transcutaneous neuromuscular electrical stimulation is routinely used in physical rehabilitation and more recently in brain-computer interface applications for restoring movement in paralyzed limbs. Due to variable muscle responses to repeated or sustained stimulation, grasp force levels can change significantly over time. Here we develop and assess closed-loop methods to regulate individual finger forces to facilitate functional movement. We combined this approach with custom textile-based electrodes to form a light-weight, wearable device and evaluated in paralyzed study participants. Methods A textile-based electrode sleeve was developed by the study team and Myant, Corp. (Toronto, ON, Canada) and evaluated in a study involving three able-body participants and two participants with quadriplegia. A feedforward-feedback control structure was designed and implemented to accurately maintain finger force levels in a quadriplegic study participant. Results Individual finger flexion and extension movements, along with functional grasping, were evoked during neuromuscular electrical stimulation. Closed-loop control methods allowed accurate steady state performance (< 15% error) with a settling time of 0.67 s (SD = 0.42 s) for individual finger contact force in a participant with quadriplegia. Conclusions Textile-based electrodes were identified to be a feasible alternative to conventional electrodes and facilitated individual finger movement and functional grasping. Furthermore, closed-loop methods demonstrated accurate control of individual finger flexion force. This approach may be a viable solution for enabling grasp force regulation in quadriplegia. Trial registration NCT, NCT03385005. Registered Dec. 28, 2017

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