Title :
Stochastic frequency signature for chemical sensing using noninvasive neuronelectronic interface
Author :
Yang, Mo ; Zhang, Xuan ; Zhang, Yu ; Ozkan, Cengiz S.
Author_Institution :
Dept. of Mech. Eng., Univ. of California, Riverside, CA, USA
fDate :
5/1/2005 12:00:00 AM
Abstract :
The detection of chemical agents is important in many areas including environmental pollutants, toxins, biological and chemical pollutants. As "smart" cells, with strong information encoding ability, neurons can be treated as independent sensing elements. A hybrid circuit of a semiconductor chip with dissociated neurons formed both sensors and transducers. Stochastic frequency spectrum was used to differentiate a mixture of chemical agents with effect on the opening of different ion channels. The frequency of spike trains revealed the concentration of the chemical agent, where the characteristic tuning curve revealed the identity. "Fatigue" experiment was performed to explore the "refreshing" ability and "memory" effect of neurons by cyclic and cascaded sensing. "Neuronelectronic noses" such as this should have wide potential applications, most notably in environmental and medical monitoring.
Keywords :
bioelectric phenomena; biomembrane transport; biosensors; chemical sensors; neurophysiology; patient monitoring; stochastic processes; biological pollutants; cascaded sensing; chemical agent detection; chemical pollutants; chemical sensing; cyclic sensing; environmental monitoring; environmental pollutants; ion channels; medical monitoring; memory effect; neuronelectronic noses; neurons; noninvasive neuronelectronic interface; semiconductor chip; smart cells; spike trains; stochastic frequency spectrum; toxins; transducers; Biological information theory; Biosensors; Chemical and biological sensors; Chemical elements; Circuits; Frequency; Intelligent sensors; Neurons; Pollution; Stochastic processes; Dielectrophoresis (DEP); neuron-electrode junction; stochastic frequency spectrum; Action Potentials; Algorithms; Animals; Biosensing Techniques; Cell Culture Techniques; Cells, Cultured; Dose-Response Relationship, Drug; Electronics; Equipment Design; Equipment Failure Analysis; Ethanol; Hippocampus; Hydrogen Peroxide; Microelectrodes; Models, Neurological; Models, Statistical; Neurons; Rats; Rats, Sprague-Dawley; Stochastic Processes; Transducers;
Journal_Title :
Biomedical Engineering, IEEE Transactions on
DOI :
10.1109/TBME.2005.845364