Interpretation of the Directional Properties of Voluntarily Modulated Human Ankle Mechanical Impedance

This article presents the results of two in-vivo studies providing measurements of human static ankle mechanical impedance. Accurate measurements of ankle impedance when muscles were voluntarily activated were obtained using a therapeutic robot, Anklebot, and an electromyographic recording system. Important features of ankle impedance, and their variation with muscle activity, are discussed, including magnitude, symmetry and directions of minimum and maximum impedance. Voluntary muscle activation has a significant impact on ankle impedance, increasing it by up to a factor of three in our experiments. Furthermore, significant asymmetries and deviations from a linear two-spring model are present in many subjects, indicating that ankle impedance has a complex and individually idiosyncratic structure. We propose the use of Fourier series as a general representation, providing both insight and a precise quantitative characterization of human static ankle impedance.

Parameters and Driving Force Estimation of Cell Motility via Expectation-Maximization (EM) Approach

Motility is an important property of immune system cells. To describe cell motility, we use a continuous stochastic process and estimate its parameters and driving force based on a maximum likelihood approach. In order to improve the convergence of the maximization procedure, we use expectation-maximization (EM) iterations. The iterations include numerical maximization and the Kalman filter. To illustrate the method, we use cell tracks obtained from the intravital video microscopy of a zebrafish embryo.

Analysis and Design of Hardware Architectures and Control Algorithms for an EPAC

EPACs (Electric Pedal Assisted Cycles) represent a very efficient and fashionable mean of non-polluting transport. They are useful for bringing education, for health service and they guarantee the lowest energy cost per distance traveled. In this paper, a power kit has been designed and implemented on a real electric bicycle. In particular, hardware architectures and control algorithms are developed together, taking in account shared needs. An optimal choice of the components and an innovative overboost strategy characterize the provided system. Experimental results and comparison with a benchmark product available in the market demonstrate the efficiency of the whole system.

Life Extending Minimum-Time Path Planning for a Hexapod Robot

This paper presents a life extending minimum-time path planning algorithm for legged robots, with application for a six-legged walking robot (hexapod). The leg joint fatigue life can be extended by reducing the constraint on the dynamic radial force. The dynamic model of the hexapod is built with the Newton Euler Formula. In the normal condition, the minimum-time path planning algorithm is developed through the bisecting-plane (BP) algorithm with the constraints of maximum joint angular velocity and acceleration. According to the fatigue life model for ball bearing, its fatigue life increases while the dynamic radial force on the bearing decreases. The minimum-time path planning algorithm is thus revised by reinforcing the constraint of maximum radial force based on the expectation of life extension. A symmetric hexapod with 18 degree-of-freedom is used for simulation study. As a simplified treatment, the magnitudes of dynamic radial force on proximal joints at the pair of supporting legs are set identical to achieve similar degradation rates on each joint bearing and obtain the dynamic radial force on each joint. The simulation results validate the effectiveness of the proposed idea. This scheme can extend the operating life of robot (joint bearing fatigue life) by modifying the joint path only without affecting the primary task specifications.

A Fully Automated System for the Preparation of Samples for Cryo-Electron Microscopy

The preparation of specimens for cryo-electron microscopy is currently a labor and time intensive process, and the quality of resulting samples is highly dependent on both environmental and procedural factors. Specimens must be applied to sample grids in a high-humidity environment, frozen in liquid ethane, and stored in liquid nitrogen. The combination of cryogenic temperatures and humidity-control mandates the segregation of the humidity-controlled environment from the cryogenic environment. Several devices which automate portions of the specimen preparation process are currently in use; however, these systems still require significant human interaction in order to create viable samples. This paper describes a fully automated system for specimen preparation. The resulting system removes the need for human input during specimen preparation, improves process control, and provides similar levels of environmental control. Early testing shows that the resulting system is capable of manipulating samples in an autonomous manner while providing performance similar to existing systems.

Acquisition of Fear and Extinction in Lateral Amygdala: A Modeling Study

The lateral nucleus of amygdala (LA) is known to be a critical storage site for conditioned fear memory. Synaptic plasticity at auditory inputs to the dorsal LA (LAd) is critical for the formation and storage of auditory fear memories. Recent evidence suggests that two different cell populations (transient- and long-term plastic cells) are present in LAd and are responsible for fear learning. However, the mechanisms involved in the formation and storage of fear are not well understood. As an extension of previous work, a biologically realistic computational model of the LAd circuitry is developed to investigate these mechanisms. The network model consists of 52 LA pyramidal neurons and 13 interneurons. Auditory and somatosensory information reaches LA from both thalamic and cortical inputs. The model replicated the tone responses observed in the two LAd cell populations during conditioning and extinction. The model provides insights into the role of thalamic and cortical inputs in fear memory formation and storage.

Time-Domain Input-Output Transient Performance Validation for Modular Control Systems: Method and Examples

This paper presents results that can be used to validate input-output transient performance for modular control systems. If bounds in the time-domain are specified for inputs of an LTI SISO system, the techniques in this paper can determine the minimum set containing all possible outputs. If both input and output bounds are given, they can determine whether these specifications are met. Network delay affecting the input of the system is also considered. Finally, this paper extends the techniques for MIMO systems. The results are derived using the theory of convex sets. Several examples are presented to illustrate the results and demonstrate their application.

Model Predictive Control of a Distributed-Parameter Process Employing a Moving Radiant Actuator

Many industrial processes employ radiation-based actuators with two or more manipulated variables. Moving radiant actuators, in particular, act on a distributed parameter process where the velocity of the actuator is an additional manipulated variable with its own constraints. In this paper, a model predictive control (MPC) scheme is developed for a distributed-parameter process employing such a moving radiant actuator. The designed MPC controller uses an online optimization approach to determine both the radiant intensity and velocity of the moving actuator based on a linearized process model and a distributed state/parameter estimator. A particular source-model reduction that enables the approach is outlined. The proposed strategy is then demonstrated for a radiative curing process considering different control scenarios with the objective of achieving desired cure level uniformity and minimizing process energy use.

Responsible Eigenvalue Approach for Stability Analysis and Control Design of a Single-Delay Large-Scale System With Random Coupling Strengths

A class of linear time-invariant (LTI) consensus system with multiple agents and communication delays among the agents is studied. The delay margin of this MIMO system, that is, the largest amount of the delay that the system can withstand without loosing stability, can be studied by the authors’ Responsible Eigenvalue (RE) concept. RE is able to compress the considered stability problem into the stability problem of a single agent system, from which RE captures the delay margin of the entire MIMO system. RE is used here to design controllers for the MIMO system for the objective of increasing the delay margin. Case studies demonstrate connections between coupling strengths, graph Laplacian, the delay margin of a large-scale consensus system, and control synthesis.

Design and Evaluation of Statically Balanced Compliant Mechanisms for Haptic Interfaces

Compliant mechanisms have the potential to increase the performance of haptic interfaces by reducing the friction and inertia felt by the user. The net result is that the user feels the dynamic forces of the virtual environment, without feeling the dynamics of the haptic interface. This “transparency” typically comes at a cost — compliant mechanisms exhibit a return-to-zero behavior that must be compensated in software. This paper presents a step toward improving the situation by using statically balanced compliant mechanisms (SBCMs), which are compliant devices that do not exhibit the return-to-zero behavior typical with most compliant mechanisms. The design and construction of a prototype haptic device based on SBCMs is presented, along with its mathematical model derived using the pseudo-rigid body model (PRBM) approach. Experimental results indicate that SBCMs effectively eliminate the return-to-zero behavior and are a feasible design element in haptic interfaces.