Electrolysis-based diaphragm actuators

This work presents a new electrolysis-based microelectromechanical systems (MEMS) diaphragm actuator. Electrolysis is a technique for converting electrical energy to pneumatic energy. Theoretically electrolysis can achieve a strain of 136 000% and is capable of generating a pressure above 200 MPa. Electrolysis actuators require modest electrical power and produce minimal heat. Due to the large volume expansion obtained via electrolysis, small actuators can create a large force. Up to 100 µm of movement was achieved by a 3 mm diaphragm. The actuator operates at room temperature and has a latching and reversing capability

Modeling crustal structure through the use of converted phases in teleseismic body-wave forms

By comparing records of the radial component of motion of teleseismic P waves to records of the vertical component, it is possible to identify S phases within the P wave form. These phases are generated by the mechanism of P to S conversion at discontinuities in velocity under the receiving station. Similar phases of the S to P converted type appear as precursors to the direct SV arrival. Models for the crustal structure can be tested by generating synthetic seismograms for both components of motion of both the P and SV waves and comparing with the data. The technique has been used to model the crustal structure at WWSSN stations CAR and COR. It has also been used to check a recently proposed model for the crustal structure in eastern Canada which contains a large low-shear-velocity zone at the base of the crust. This study indicates that the crustal structure in eastern Canada is highly non-uniform with perhaps few features common to the whole region. Finally, the technique is used to identify several stations in the WWSSN which appear to be located on highly anomalous structure

On the periodic motions of simple hopping robots

Discrete dynamical systems theory is applied to the analysis of simplified hopping robot models. A one-dimensional vertical hopping model that captures both the vertical hopping dynamics and nonlinear control algorithm is reviewed. A more complicated two-dimensional model that includes both forward and vertical hopping dynamics and a foot placement algorithm is presented. These systems are analyzed using a Poincare return map and hopping behavior is investigated by constructing the return map bifurcation diagrams with respect to system parameters. The diagrams show period doubling leading to chaotic behavior. Using the vertical model results as a guide, dynamic behaviour of the planar hopping system is interpreted

Cognitive based neural prosthetics

Intense activity in neural prosthetic research has recently demonstrated the possibility of robotic interfaces that respond directly to the nervous system. The question remains of how the flow of information between the patient and the prosthetic device should be designed to provide a safe, effective system that maximizes the patient’s access to the outside world. Much recent work by other investigators has focused on using decoded neural signals as low-level commands to directly control the trajectory of screen cursors or robotic end-effectors. Here we review results that show that high-level, or cognitive, signals can be decoded from planned arm movements. These results, coupled with fundamental limitations in signal recording technology, motivate an approach in which cognitive neural signals play a larger role in the neural interface. This proposed paradigm predicates that neural signals should be used to instruct external devices, rather than control their detailed movement. This approach will reduce the effort required of the patient and will take advantage of established and on-going robotics research in intelligent systems and human-robot interfaces

Recording advances for neural prosthetics

An important challenge for neural prosthetics research is to record from populations of neurons over long periods of time, ideally for the lifetime of the patient. Two new advances toward this goal are described, the use of local field potentials (LFPs) and autonomously positioned recording electrodes. LFPs are the composite extracellular potential field from several hundreds of neurons around the electrode tip. LFP recordings can be maintained for longer periods of time than single cell recordings. We find that similar information can be decoded from LFP and spike recordings, with better performance for state decodes with LFPs and, depending on the area, equivalent or slightly less than equivalent performance for signaling the direction of planned movements. Movable electrodes in microdrives can be adjusted in the tissue to optimize recordings, but their movements must be automated to be a practical benefit to patients. We have developed automation algorithms and a meso-scale autonomous electrode testbed, and demonstrated that this system can autonomously isolate and maintain the recorded signal quality of single cells in the cortex of awake, behaving monkeys. These two advances show promise for developing very long term recording for neural prosthetic applications

In Silico Modeling of the Rheological Properties of Covalently Cross-Linked Collagen Triple Helices

Biomimetic hydrogels based on natural polymers are a promising class of biomaterial, mimicking the natural extra-cellular matrix of biological tissues and providing cues for cell attachment, proliferation, and differentiation. With a view to providing an upstream method to guide subsequent experimental design, the aim of this study was to introduce a mathematical model that described the rheological properties of a hydrogel system based on covalently cross-linked collagen triple helices. In light of their organization, such gels exhibit limited collagen bundling that cannot be described by existing fibril network models. The model presented here treats collagen triple helices as discrete semiflexible polymers, permits full access to metrics for network microstructure, and should provide a comprehensive understanding of the parameter space associated with the development of such multifunctional materials. Triple helical hydrogel networks were experimentally obtained via the reaction of type I collagen with both aromatic and aliphatic diacids. The complex modulus G* was found from rheological testing in linear shear and quantitatively compared to model predictions. In silico data from the computational model successfully described the experimental trends in hydrogel storage modulus with either (i) the concentration of collagen triple helices during the cross-linking reaction or (ii) the type of cross-linking segment introduced in resulting hydrogel networks. This approach may pave the way to a step change in the rational design of biomimetic triple helical collagen systems with controlled multifunctionality