Biomedical Engineering Reference
In-Depth Information
approaches to synthesize and fabricate CP NWs. They also compare the limitations of
various methods from different laboratories and attempts which have been made to
address these limitations. The functionalization and assembly of these 1-D nanostructures
is presented and their application for labelfree detection of various biological molecules at
high sensitivity and low detection limits is demonstrated. Finally, some of the challenges
in the 1-D nanostructured material design are highlighted. Multiple signal generation
using array technologies can lead to large amounts of data. In particular, real-time moni-
toring involves complex systems and environmental conditions. Pattern recognition algo-
rithms and data exploration techniques provide a method of data analysis which can be
embedded in the sensors using programmable microcontrollers or implemented off-line
on graphical workstations. In Chapter 5, George K. Knopf provides an overview of intel-
ligence and pattern recognition and how they can be linked to biosensor design. These
concepts include adaptive signal processing algorithms, adaptive control, intelligent deci-
sion making using an integrated and functional design approach. In Chapter 6, Professor
Guenter W. Gross from the Center for Network Neuroscience (CNNS), University of
North Texas and Joseph P. Pancrazio focus on neuronal network biosensors (NNBS)
formed using functional, spontaneously active neural cell based networks on substrate-
integrated microelectrode arrays. These NNBS are biosensors which respond to a diverse
array of compounds that attack neural cells. These compounds include bacterial toxins,
metabolic poisons, toxic metals, neuropharmacological compounds, hallucinatory drugs,
and epileptogenic agents. These sensors are being applied for investigations of neurotox-
icity and cytotoxicity, and for exploiting their properties for environmental toxicology,
drug development, and even in defense as broadband biosensors. This approach leads to
multisite electrophysiological data, for example action potential patterns and wave-
shapes, as well as simultaneous cytological information through high power microscopy
and fluorescence. This chapter provides a description of prototype systems developed or
under development at CNNS.
