title: Statistical signal processing for an implantable ethanol biosensor.
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.
authors.affiliation: Purdue Univ., West Lafayette, IN 47907, USA.
authors.forename: Jae-Joon
authors.initials: JJ
authors.lastname: Han
authors.forename: Peter C
authors.initials: PC
authors.lastname: Doerschuk
authors.forename: Saul B
authors.initials: SB
authors.lastname: Gelfand
authors.forename: Sean J
authors.initials: SJ
authors.lastname: O'Connor
mesh_terms: D000428:Alcohol Drinking / Q000097:blood*; D000437:Alcoholism / Q000175:diagnosis*; D015374:Biosensing Techniques; D000431:Ethanol / Q000097:blood*; D006801:Humans; D016018:Least-Squares Analysis; D019736:Prostheses and Implants; D015203:Reproducibility of Results
chemical_list: D000431:Ethanol