Title :
Statistical Signal processing for an implantable ethanol biosensor
Author :
Han, Jae-Joon ; Doerschuk, Peter C. ; Gelfand, Saul B. ; O´Connor, S.J.
Author_Institution :
Purdue Univ., West Lafayette, IN
fDate :
Aug. 30 2006-Sept. 3 2006
Abstract :
The understanding of drinking patterns leading to alcoholism has been hindered by an inability to unobtrusively measure ethanol consumption over periods of weeks to months in the community environment. Signal processing for an implantable ethanol MEMS bio sensor under simultaneous development is described where the sensor-signal processing system will provide a novel approach to this need. For safety and user acceptability issues, the sensor will be implanted subcutaneously and therefore measure peripheral-tissue ethanol concentration. A statistical signal processing system based on detailed models of the physiology and using extended Kalman filtering and dynamic programming tools is described which determines ethanol consumption and kinetics in other compartments from the time course of peripheral-tissue ethanol concentration
Keywords :
Kalman filters; behavioural sciences; biochemistry; biomedical measurement; biosensors; chemical variables measurement; dynamic programming; microsensors; signal processing; statistical analysis; alcoholism; drinking patterns; dynamic programming tool; extended Kalman filtering; implantable ethanol MEMS biosensor; peripheral-tissue ethanol consumption measurement; statistical sensor-signal processing; Alcoholism; Biomedical signal processing; Biosensors; Dynamic programming; Ethanol; Filtering; Kalman filters; Micromechanical devices; Physiology; Safety;
Conference_Titel :
Engineering in Medicine and Biology Society, 2006. EMBS '06. 28th Annual International Conference of the IEEE
Conference_Location :
New York, NY
Print_ISBN :
1-4244-0032-5
Electronic_ISBN :
1557-170X
DOI :
10.1109/IEMBS.2006.259572
