Expectation Maximization Method to Identify an Electrically Stimulated Musculoskeletal Model

2015 ◽  
Author(s):  
Harish Ravichandar ◽  
Ashwin Dani ◽  
Jacquelyn Khadijah-Hajdu ◽  
Nicholas Kirsch ◽  
Qiang Zhong ◽  
...  
Keyword(s):  
Dynamic Model ◽  
Expectation Maximization ◽  
Control Design ◽  
Knee Extension ◽  
Musculoskeletal Model ◽  
Effective Control ◽  
Identification Algorithm ◽  
Knee Angle ◽  
Unknown Parameters ◽  
Angle Measurements

A system identification algorithm for a musculoskeletal system using an approximate expectation maximization (E-M) is presented. Effective control design for neuroprosthesis applications necessitates a well defined muscle model. A dynamic model of the lower leg with a fixed ankle is considered. The unknown parameters of the model are estimated using an approximate E-M algorithm based on knee angle measurements collected from an able-bodied subject during stimulated knee extension. The parameters estimated from the data are compared to reference values obtained by conducting experiments that separate the parameters in the dynamics from one another. The presented results demonstrate the capability of the proposed algorithm to identify the parameters of the dynamic model from knee angle measurements.

scholarly journals Two Identification Methods for Dual-Rate Sampled-Data Nonlinear Output-Error Systems

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Jing Chen ◽  
Ruifeng Ding
Keyword(s):  
Stochastic Gradient ◽  
The Other ◽  
Identification Algorithm ◽  
Sampled Data ◽  
Unknown Parameters ◽  
Auxiliary Model ◽  
Identification Methods ◽  
Numerical Example ◽  
Output Error ◽  
Polynomial Transformation

This paper presents two methods for dual-rate sampled-data nonlinear output-error systems. One method is the missing output estimation based stochastic gradient identification algorithm and the other method is the auxiliary model based stochastic gradient identification algorithm. Different from the polynomial transformation based identification methods, the two methods in this paper can estimate the unknown parameters directly. A numerical example is provided to confirm the effectiveness of the proposed methods.

Initial phase of maximal voluntary and electrically stimulated knee extension torque development at different knee angles

2004 ◽  
Vol 97 (5) ◽  
pp. 1693-1701 ◽  
Author(s):  
C. J. de Ruiter ◽  
R. D. Kooistra ◽  
M. I. Paalman ◽  
A. de Haan
Keyword(s):  
Muscle Activation ◽  
Knee Extensor ◽  
Surface Emg ◽  
Knee Extension ◽  
Voluntary Contraction ◽  
Voluntary Activation ◽  
Knee Angle ◽  
Time Integral ◽  
Voluntary Contractions ◽  
Torque Development

We investigated the capacity for torque development and muscle activation at the onset of fast voluntary isometric knee extensions at 30, 60, and 90° knee angle. Experiments were performed in subjects ( n = 7) who had high levels (>90%) of activation at the plateau of maximal voluntary contractions. During maximal electrical nerve stimulation (8 pulses at 300 Hz), the maximal rate of torque development (MRTD) and torque time integral over the first 40 ms (TTI40) changed in proportion with torque at the different knee angles (highest values at 60°). At each knee angle, voluntary MRTD and stimulated MRTD were similar ( P < 0.05), but time to voluntary MRTD was significantly longer. Voluntary TTI40 was independent ( P > 0.05) of knee angle and on average (all subjects and angles) only 40% of stimulated TTI40. However, among subjects, the averaged (across knee angles) values ranged from 10.3 ± 3.1 to 83.3 ± 3.2% and were positively related ( r2 = 0.75, P < 0.05) to the knee-extensor surface EMG at the start of torque development. It was concluded that, although all subjects had high levels of voluntary activation at the plateau of maximal voluntary contraction, among subjects and independent of knee angle, the capacity for fast muscle activation varied substantially. Moreover, in all subjects, torque developed considerably faster during maximal electrical stimulation than during maximal voluntary effort. At different knee angles, stimulated MRTD and TTI40 changed in proportion with stimulated torque, but voluntary MRTD and TTI40 changed less than maximal voluntary torque.

On the Properties of a Dynamic Model of Flexible Robot Manipulators

1998 ◽  
Vol 120 (1) ◽  
pp. 8-14 ◽  
Author(s):  
Marco A. Arteaga
Keyword(s):  
Dynamic Model ◽  
Structural Properties ◽  
Robot Manipulators ◽  
Equations Of Motion ◽  
Mechanical Systems ◽  
Control Design ◽  
Flexible Manipulator ◽  
Robot Dynamics ◽  
Flexible Link ◽  
Flexible Robot

Control design of flexible robot manipulators can take advantage of the structural properties of the model used to describe the robot dynamics. Many of these properties are physical characteristics of mechanical systems whereas others arise from the method employed to model the flexible manipulator. In this paper, the modeling of flexible-link robot manipulators on the basis of the Lagrange’s equations of motion combined with the assumed modes method is briefly discussed. Several notable properties of the dynamic model are presented and their impact on control design is underlined.

scholarly journals Acute effect of tendon vibration applied during isometric contraction at two knee angles on maximal knee extension force production

PLoS ONE ◽  
2020 ◽  
Vol 15 (11) ◽  
pp. e0242324
Author(s):  
Jonathan Harnie ◽  
Thomas Cattagni ◽  
Christophe Cornu ◽  
Peter McNair ◽  
Marc Jubeau
Keyword(s):  
Isometric Contraction ◽  
Vastus Lateralis ◽  
Force Production ◽  
Knee Extensor ◽  
Acute Effect ◽  
Knee Extension ◽  
Voluntary Contraction ◽  
Voluntary Activation ◽  
Tendon Vibration ◽  
Knee Angle

The aim of the current study was to investigate the effect of a single session of prolonged tendon vibration combined with low submaximal isometric contraction on maximal motor performance. Thirty-two young sedentary adults were assigned into two groups that differed based on the knee angle tested: 90° or 150° (180° = full knee extension). Participants performed two fatigue-inducing exercise protocols: one with three 10 min submaximal (10% of maximal voluntary contraction) knee extensor contractions and patellar tendon vibration (80 Hz) another with submaximal knee extensor contractions only. Before and after each fatigue protocol, maximal voluntary isometric contractions (MVC), voluntary activation level (assessed by the twitch interpolation technique), peak-to-peak amplitude of maximum compound action potentials of vastus medialis and vastus lateralis (assessed by electromyography with the use of electrical nerve stimulation), peak twitch amplitude and peak doublet force were measured. The knee extensor fatigue was significantly (P<0.05) greater in the 90° knee angle group (-20.6% MVC force, P<0.05) than the 150° knee angle group (-8.3% MVC force, P = 0.062). Both peripheral and central alterations could explain the reduction in MVC force at 90° knee angle. However, tendon vibration added to isometric contraction did not exacerbate the reduction in MVC force. These results clearly demonstrate that acute infrapatellar tendon vibration using a commercial apparatus operating at optimal conditions (i.e. contracted and stretched muscle) does not appear to induce knee extensor neuromuscular fatigue in young sedentary subjects.

scholarly journals Muscles Recruited During an Isometric Knee Extension is Defined by Proprioceptive Feedback

2019 ◽  
Author(s):  
Gareth York ◽  
Hugh Osborne ◽  
Piyanee Sriya ◽  
Sarah Astill ◽  
Marc de Kamps ◽  
...  
Keyword(s):  
Spinal Cord ◽  
Conflict Of Interest ◽  
Rectus Femoris ◽  
Knee Extension ◽  
Proprioceptive Feedback ◽  
Muscle Synergy ◽  
Knee Angle ◽  
Potential Conflict ◽  
Dynamic Task ◽  
Isometric Knee Extension

AbstractProprioceptive feedback and its role in control of isometric tasks is often overlooked. In this study recordings were made from upper leg muscles during an isometric knee extension task. Internal knee angle was fixed and subjects were asked to voluntarily activate their rectus femoris muscle. Muscle synergy analysis of these recordings identified canonical temporal patterns in the data. These synergies were found to encode two separate features: one concerning the coordinated contraction of the recorded muscles and the other indicating agonistic/antagonistic interactions between these muscles. The second synergy changed with internal knee angle reflecting the influence of afferent activity. This is in contrast to previous studies of dynamic task experiments which have indicated that proprioception has a negligible effect on synergy expression. Using the MIIND neural simulation platform, we developed a spinal population model with an adjustable input representing proprioceptive feedback. The model is based on existing spinal population circuits used for dynamic tasks. When the same synergy analysis was performed on the output from the model, qualitatively similar muscle synergy patterns were observed. These results suggest proprioceptive feedback is integrated in the spinal cord to control isometric tasks via muscle synergies.Significance statementSensory feedback from muscles is a significant factor in normal motor control. It is often assumed that instantaneous muscle stretch does not influence experiments where limbs are held in a fixed position. Here, we identified patterns of muscle activity during such tasks showing that this assumption should be revisited. We also developed a computational model to propose a possible mechanism, based on a network of populations of neurons, that could explain this phenomenon. The model is based on well established neural circuits in the spinal cord and fits closely other models used to simulate more dynamic tasks like locomotion in vertebrates.Conflict of interest statementThe authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Modeling of Shape Memory Alloy Actuators Using Matlab and dSpace Platform

2010 ◽  
Vol 166-167 ◽  
pp. 149-154
Author(s):  
Ioan Adrian Cosma ◽  
Vistrian Măties ◽  
Ciprian Lapusan ◽  
Rares Ciprian Mîndru
Keyword(s):  
Shape Memory Alloy ◽  
Shape Memory ◽  
Dynamic Model ◽  
Dynamic Equations ◽  
Control Technique ◽  
Positioning System ◽  
Unknown Parameters ◽  
New Approach ◽  
Model Based Control ◽  
Input And Output

The aim of the paper is to describe an approach for modeling the dynamic behavior of a positioning system actuated by two shape memory alloy springs, placed in opposition. The mathematical analysis of the system in order to develop the dynamic model is difficult in this case because of the unknown parameters within the dynamic equations (thermodynamics, change in austenite fraction) and therefore a new approach is presented. Thus, a positioning system is considered, and its behavior is determined using Matlab Software, D-space platform and an optical sensor, which analyses the position/velocity of the moving cart. The dynamic model of the system is determined in order to develop a further model based control technique. The model is generated using system identification toolbox within Matlab and input and output (response) of the considered system.

Expectation maximization identification algorithm for time-delay two-dimensional systems

2020 ◽  
Vol 357 (14) ◽  
pp. 9992-10009
Author(s):  
Jing Chen ◽  
Qianyan Shen ◽  
Yanjun Liu ◽  
Lijuan Wan
Keyword(s):  
Time Delay ◽  
Expectation Maximization ◽  
Identification Algorithm ◽  
Two Dimensional

Robust Control of the Elastodynamic Vibrations of a Flexible Rotor System With Discontinuous Friction

2011 ◽  
Vol 133 (3) ◽  
Author(s):  
Mansour Karkoub
Keyword(s):  
Dynamic Model ◽  
Design Process ◽  
Nonlinear Models ◽  
Control Design ◽  
Rotor System ◽  
Control Technique ◽  
Flexible Rotor ◽  
Highly Nonlinear ◽  
Modeling Errors ◽  
The Difference

The work presented here deals with the control of a flexible rotor system using the μ-synthesis control technique. This technique allows for the inclusion of modeling errors in the control design process in terms of uncertainty weights. The dynamic model of the rotor system, which includes discontinuous friction, is highly nonlinear and has to be linearized around an operating point in order to use μ-synthesis. The difference between the linear and nonlinear models is characterized in terms of uncertainty weights and included in the control design process. The designed controller is robust to uncertainty in the dynamic model, spillover, actuator uncertainty, and noise. The theoretical findings of the μ-synthesis control design are validated through simulations and the results are presented and discussed here.

scholarly journals A Steering-Following Dynamic Model with Driver’s NMS Characteristic for Human-Vehicle Shared Control

2020 ◽  
Vol 10 (7) ◽  
pp. 2626 ◽  
Author(s):  
Hanbing Wei ◽  
Yanhong Wu ◽  
Xing Chen ◽  
Jin Xu
Keyword(s):  
Dynamic Model ◽  
Unscented Kalman Filter ◽  
Autonomous Vehicle ◽  
Least Square ◽  
Experimental Results ◽  
Shared Control ◽  
Dynamic State ◽  
Dynamic Mode ◽  
Identification Algorithm ◽  
Control Authority

For investigating driver characteristic as well as control authority allocation during the process of human–vehicle shared control (HVSC) for an autonomous vehicle (AV), a HVSC dynamic mode with a driver’s neuromuscular (NMS) state parameters was proposed in this paper. It takes into account the driver’s NMS characteristics such as stretch reflection and reflex stiffness. By designing a model predictive control (MPC) controller, the vehicle’s state feedback and driver’s state are incorporated to construct the HVSC dynamic model. For the validation of the model, a field experiment was conducted. The vehicle state signals are collected by V-BOX, and the driver’s state signals are obtained with the electromyography instrument. Subsequently, the hierarchical least square (HLS) parameter identification algorithm was implemented to identify the parameters of the model based on the experimental results. Moreover, the Unscented Kalman Filter (UKF) was utilized to estimate the important NMS parameters which cannot be measured directly. The experimental results showed that the model we proposed has excellent accuracy in characterizing the vehicle’s dynamic state and estimating the driver’s NMS parameter. This paper will serve as a theoretical basis for the new control strategy allocation between human and vehicle for L3 class AVs.

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