Statistical Signal processing for an implantable ethanol biosensor

Jae Joon Han, Peter C. Doerschuk, Saul B. Gelfand, Sean O'Connor

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.

Original languageEnglish (US)
Title of host publicationAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Pages3704-3707
Number of pages4
DOIs
StatePublished - 2006
Externally publishedYes
Event28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'06 - New York, NY, United States
Duration: Aug 30 2006Sep 3 2006

Other

Other28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'06
CountryUnited States
CityNew York, NY
Period8/30/069/3/06

Fingerprint

Biosensors
Signal processing
Ethanol
Sensors
Tissue
Physiology
Dynamic programming
MEMS
Kinetics

ASJC Scopus subject areas

  • Bioengineering

Cite this

Han, J. J., Doerschuk, P. C., Gelfand, S. B., & O'Connor, S. (2006). Statistical Signal processing for an implantable ethanol biosensor. In Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings (pp. 3704-3707). [4029185] https://doi.org/10.1109/IEMBS.2006.259572

Statistical Signal processing for an implantable ethanol biosensor. / Han, Jae Joon; Doerschuk, Peter C.; Gelfand, Saul B.; O'Connor, Sean.

Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings. 2006. p. 3704-3707 4029185.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Han, JJ, Doerschuk, PC, Gelfand, SB & O'Connor, S 2006, Statistical Signal processing for an implantable ethanol biosensor. in Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings., 4029185, pp. 3704-3707, 28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'06, New York, NY, United States, 8/30/06. https://doi.org/10.1109/IEMBS.2006.259572
Han JJ, Doerschuk PC, Gelfand SB, O'Connor S. Statistical Signal processing for an implantable ethanol biosensor. In Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings. 2006. p. 3704-3707. 4029185 https://doi.org/10.1109/IEMBS.2006.259572
Han, Jae Joon ; Doerschuk, Peter C. ; Gelfand, Saul B. ; O'Connor, Sean. / Statistical Signal processing for an implantable ethanol biosensor. Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings. 2006. pp. 3704-3707
@inproceedings{42f32fc7e706478096d76482e824eb5e,
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.",
author = "Han, {Jae Joon} and Doerschuk, {Peter C.} and Gelfand, {Saul B.} and Sean O'Connor",
year = "2006",
doi = "10.1109/IEMBS.2006.259572",
language = "English (US)",
isbn = "1424400325",
pages = "3704--3707",
booktitle = "Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings",

}

TY - GEN

T1 - Statistical Signal processing for an implantable ethanol biosensor

AU - Han, Jae Joon

AU - Doerschuk, Peter C.

AU - Gelfand, Saul B.

AU - O'Connor, Sean

PY - 2006

Y1 - 2006

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=34047177011&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=34047177011&partnerID=8YFLogxK

U2 - 10.1109/IEMBS.2006.259572

DO - 10.1109/IEMBS.2006.259572

M3 - Conference contribution

SN - 1424400325

SN - 9781424400324

SP - 3704

EP - 3707

BT - Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings

ER -