Agenor de Toledo Fleury

Biomechanical modeling and optimal control of human posture

The present work describes the biomechanical modeling of human postural mechanics in the saggital plane and the use of optimal control to generate open-loop raising-up movements from a squatting position. The biomechanical model comprises 10 equivalent musculotendon actuators, based on a 40 muscles model, and three links (shank, thigh and HAT-Head, Arms and Trunk). Optimal control solutions are achieved through algorithms based on the Consistent Approximations Theory (Schwartz and Polak, 1996), where the continuous non-linear dynamics is represented in a discrete space by means of a Runge-Kutta integration and the control signals in a spline-coefficient functional space. This leads to non-linear programming problems solved by a sequential quadratic programming (SQP) method. Due to the highly non-linear and unstable nature of the posture dynamics, numerical convergence is difficult, and specific strategies must be implemented in order to allow convergence. Results for control (muscular excitations) and angular trajectories are shown using two final simulation times, as well as specific control strategies are discussed.

Dynamic Imaging in Electrical Impedance Tomography of the Human Chest With Online Transition Matrix Identification

One of the electrical impedance tomography objectives is to estimate the electrical resistivity distribution in a domain based only on electrical potential measurements at its boundary generated by an imposed electrical current distribution into the boundary. One of the methods used in dynamic estimation is the Kalman filter. In biomedical applications, the random walk model is frequently used as evolution model and, under this conditions, poor tracking ability of the extended Kalman filter (EKF) is achieved. An analytically developed evolution model is not feasible at this moment. The paper investigates the identification of the evolution model in parallel to the EKF and updating the evolution model with certain periodicity. The evolution model transition matrix is identified using the history of the estimated resistivity distribution obtained by a sensitivity matrix based algorithm and a Newton-Raphson algorithm. To numerically identify the linear evolution model, the Ibrahim time-domain method is used. The investigation is performed by numerical simulations of a domain with time-varying resistivity and by experimental data collected from the boundary of a human chest during normal breathing. The obtained dynamic resistivity values lie within the expected values for the tissues of a human chest. The EKF results suggest that the tracking ability is significantly improved with this approach.

Kinematical modeling and optimal design of a biped robot joint parallel linkage

This paper shows the design and analysis of a parallel three-dimensional linkage, conceived to work as the ankle and hip joints of an anthropometric biped robot. This kind of mechanism architecture provides low-weight, highly stable assemblies, and allows the use of actuator synergies. On the other hand, the mechanical transmission ratio is not usually favorable, and a non-linear kinematic model has to be derived and solved. The mechanism proposed here is driven by two rotational servo-actuators, and allows the joint to follow a specified angular trajectory determined by the gait pattern. Namely, the joint linkage can generate dorsi/plantar flexion and inversion/eversion of the ankle, and hip flexion/extension and adduction/abduction movements. Several approaches to the direct and inverse kinematical modeling of the linkage are presented and compared, regarding their accuracy and computational cost, where the last performance parameter is closely related to on-line computer implementing of the controller. Strategies to fit current gait angular amplitudes into the linkage workspace, as well as singularity analysis, are discussed. An optimization method was applied to find some geometrical design parameters of the linkage that minimizes a cost function. This function is the mean transmission ratio between the motor inputs and the joint output torques over a predefined dominion. The minimization is constrained to a minimum workspace area value and to minimum and maximum values of the design parameters. Several design solutions were generated. The chosen was one where the workspace is compatible to the gait amplitude requirements and that exhibits the lowest cost function. A biped robot using the linkage geometry designed in this paper has been built and tested with real human gait data acquired in a gait lab. Keywords: Parallel linkage, mechanisms, gait analysis, biped robot, optimal design

Online transition matrix identification of the state evolution model for the extended Kalman filter in electrical impedance tomography

One of the electrical impedance tomography objectives is to estimate the electrical resistivity distribution in a domain based only on contour electrical potential measurements caused by an imposed electrical current distribution into the boundary. In biomedical applications, the random walk model is frequently used as evolution model and, under this conditions, it is observed poor tracking ability of the Extended Kalman Filter (EKF). An analytically developed evolution model is not feasible at this moment. The present work investigates the possibility of identifying the evolution model in parallel to the EKF and updating the evolution model with certain periodicity. The evolution model is identified using the history of resistivity distribution obtained by a sensitivity matrix based algorithm. To numerically identify the linear evolution model, it is used the Ibrahim Time Domain Method, normally used to identify the transition matrix on structural dynamics. The investigation was performed by numerical simulations of a time varying domain with the addition of noise. Numerical dificulties to compute the transition matrix were solved using a Tikhonov regularization. The EKF numerical simulations suggest that the tracking ability is significantly improved.

An inference model for combustion diagnostics in an experimental oil furnace

The continuous monitoring of the air/fuel ratio, oil/water/air temperatures, and gas/particulate emissions of combustion processes in oil-based furnaces allows experts to detect anomalies and act to prevent faults and critical conditions. These important but tedious tasks can be performed by an expert system designed to mimic the human abilities of recognizing relevant patterns and finding their most likely causes. In this article, we present the architecture of an expert system that uses flame images grabbed during the combustion process in an experimental oil furnace as input parameters. Computational processing of those images provides feature vectors for analysis by “artificial experts” that correlate changes in flame appearance with typical combustion states. The Dempster–Shafer method is used to build the knowledge base and the inference engine. The results of tests in which flame conditions are suddenly modified by altering the physical variables of the combustion process revealed that the method can properly combine measures from various flame image characteristics to issue diagnostics. Such diagnostics are similar to those given by human experts. This suggests that the proposed approach may fill the gap between models based on features extracted from images and real-world operating conditions. This is the intended contribution of this work.

On the Euler and Lagrange's Points of View in Rigid Body Mechanics

In this work we take Lagranges and Eulers important concepts from fluid mechanics and apply them to the movement of a rigid body. By means of two examples, namely motion around a fixed axis and around a fixed point, Lagrangian and Eulerian formulations of the problems are discussed. It is shown that Eulers approach suits better the description of rigid body kinematics, since the linearized equations of motion are simpler than the ones obtained by Lagranges formulation. This topic is rarely discussed in undergraduate courses on mechanics but it can provide students with a deeper comprehension of the movement of a rigid body and, at the same time, establish a connection with the scope of fluid mechanics.

A low-cost anthropometric walking robot for reproducing gait lab data

Human gait analysis is one of the resources that may be used in the study and treatment of pathologies of the locomotive system. This paper deals with the modelling and control aspects of the design, construction and testing of a biped walking robot conceived to, in limited extents, reproduce the human gait. Robot dimensions have been chosen in order to guarantee anthropomorphic proportions and then to help health professionals in gait studies. The robot has been assembled with low-cost components and can reproduce, in an assisted way, real-gait patterns generated from data previously acquired in gait laboratories. Part of the simulated and experimental results are addressed to demonstrate the ability of the biped robot in reproducing normal and pathological human gait.