Design of carbon nanotube fiber microelectrode for glucose biosensing

BACKGROUND: Carbon nanotube (CNT) fiber directly spun from an aerogel has a unique, well-aligned nanostructure (nano-pore and nano-brush), and thus provides high electro-catalytic activity and strong interaction with glucose oxidase enzyme. It shows great potential as a microelectrode for electrochemical biosensors. RESULTS: Cyclic voltammogram results indicate that post-synthesis treatments have great influence on the electrocatalytic activity of CNT fibers. Raman spectroscopy and electrical conductivity tests suggest that fibers annealed at 250 °C remove most of the impurities without damaging the graphite-like structure. This leads to a nano-porous morphology on the surface and the highest conductivity value (1.1 × 10 5 S m -1). Two CNT fiber microelectrode designs were applied to enhance their electron transfer behaviour, and it was found that a design using a 30 nm gold coating is able to linearly cover human physiological glucose level between 2 and 30 mmol L -1. The design also leads to a low detection limit of 25 μmol L -1. CONCLUSIONS: The high performance of CNT fibers not only offers exceptional mechanical and electrical properties, but also provides a large surface area and electron transfer pathway. They consequently make excellent bioactive microelectrodes for glucose biosensing, especially for potential use in implantable devices. © 2011 Society of Chemical Industry.

Physiological modelling for improved reliability in silhouette-driven gradient-based hand tracking

We present a gradient-based motion capture system that robustly tracks a human hand, based on abstracted visual information - silhouettes. Despite the ambiguity in the visual data and despite the vulnerability of gradient-based methods in the face of such ambiguity, we minimise problems related to misfit by using a model of the hand's physiology, which is entirely non-visual, subject-invariant, and assumed to be known a priori. By modelling seven distinct aspects of the hand's physiology we derive prior densities which are incorporated into the tracking system within a Bayesian framework. We demonstrate how the posterior is formed, and how our formulation leads to the extraction of the maximum a posteriori estimate using a gradient-based search. Our results demonstrate an enormous improvement in tracking precision and reliability, while also achieving near real-time performance. © 2009 IEEE.

A high-resolution atlas and statistical model of the human heart from multislice CT

Atlases and statistical models play important roles in the personalization and simulation of cardiac physiology. For the study of the heart, however, the construction of comprehensive atlases and spatio-temporal models is faced with a number of challenges, in particular the need to handle large and highly variable image datasets, the multi-region nature of the heart, and the presence of complex as well as small cardiovascular structures. In this paper, we present a detailed atlas and spatio-temporal statistical model of the human heart based on a large population of 3D+time multi-slice computed tomography sequences, and the framework for its construction. It uses spatial normalization based on nonrigid image registration to synthesize a population mean image and establish the spatial relationships between the mean and the subjects in the population. Temporal image registration is then applied to resolve each subject-specific cardiac motion and the resulting transformations are used to warp a surface mesh representation of the atlas to fit the images of the remaining cardiac phases in each subject. Subsequently, we demonstrate the construction of a spatio-temporal statistical model of shape such that the inter-subject and dynamic sources of variation are suitably separated. The framework is applied to a 3D+time data set of 138 subjects. The data is drawn from a variety of pathologies, which benefits its generalization to new subjects and physiological studies. The obtained level of detail and the extendability of the atlas present an advantage over most cardiac models published previously. © 1982-2012 IEEE.