University of Hertfordshire

By the same authors

Towards a Patient-Specific Model of Lung Volume Using Absolute Electrical Impedance Tomography (aEIT)

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)

Standard

Towards a Patient-Specific Model of Lung Volume Using Absolute Electrical Impedance Tomography (aEIT). / Mohamed-Samuri, S.; Panoutsos, G.; Mahfouf, M.; Mills, G.H.; Denai, Mouloud; Brown, B.H.

Biomedical Engineering Systems and Technologies: 4th International Joint Conference, BIOSTEC 2011, Rome, Italy, January 26-29, 2011, Revised Selected Papers. Springer, 2013. p. 191-204 (Communications in Computer and Information Science; Vol. 273).

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)

Harvard

Mohamed-Samuri, S, Panoutsos, G, Mahfouf, M, Mills, GH, Denai, M & Brown, BH 2013, Towards a Patient-Specific Model of Lung Volume Using Absolute Electrical Impedance Tomography (aEIT). in Biomedical Engineering Systems and Technologies: 4th International Joint Conference, BIOSTEC 2011, Rome, Italy, January 26-29, 2011, Revised Selected Papers. Communications in Computer and Information Science, vol. 273, Springer, pp. 191-204. https://doi.org/10.1007/978-3-642-29752-6_14

APA

Mohamed-Samuri, S., Panoutsos, G., Mahfouf, M., Mills, G. H., Denai, M., & Brown, B. H. (2013). Towards a Patient-Specific Model of Lung Volume Using Absolute Electrical Impedance Tomography (aEIT). In Biomedical Engineering Systems and Technologies: 4th International Joint Conference, BIOSTEC 2011, Rome, Italy, January 26-29, 2011, Revised Selected Papers (pp. 191-204). (Communications in Computer and Information Science; Vol. 273). Springer. https://doi.org/10.1007/978-3-642-29752-6_14

Vancouver

Mohamed-Samuri S, Panoutsos G, Mahfouf M, Mills GH, Denai M, Brown BH. Towards a Patient-Specific Model of Lung Volume Using Absolute Electrical Impedance Tomography (aEIT). In Biomedical Engineering Systems and Technologies: 4th International Joint Conference, BIOSTEC 2011, Rome, Italy, January 26-29, 2011, Revised Selected Papers. Springer. 2013. p. 191-204. (Communications in Computer and Information Science). https://doi.org/10.1007/978-3-642-29752-6_14

Author

Mohamed-Samuri, S. ; Panoutsos, G. ; Mahfouf, M. ; Mills, G.H. ; Denai, Mouloud ; Brown, B.H. / Towards a Patient-Specific Model of Lung Volume Using Absolute Electrical Impedance Tomography (aEIT). Biomedical Engineering Systems and Technologies: 4th International Joint Conference, BIOSTEC 2011, Rome, Italy, January 26-29, 2011, Revised Selected Papers. Springer, 2013. pp. 191-204 (Communications in Computer and Information Science).

Bibtex

@inbook{485f8ad163ed4167a9731b38500257e6,
title = "Towards a Patient-Specific Model of Lung Volume Using Absolute Electrical Impedance Tomography (aEIT)",
abstract = "Electrical Impedance Tomography (EIT), and in particular its application to pulmonary measurement, has been the subject of intensive research since its development in the early 1980s by Barber and Brown. One of the relatively recent advances in EIT is the development of an absolute EIT system (aEIT) which can estimate absolute values of lung resistivity and associated lung volumes. In this paper we present a new approach based on Computational Intelligence (CI) modelling to model the {\textquoteleft}Resistivity - Lung Volume{\textquoteright} relationship that will allow more accurate lung volume estimations using data from eight (8) healthy volunteers measured simultaneously via the Sheffield aEIT system and a Spirometer. The developed models show an improved accuracy in the prediction of lung volumes, as compared with the original Sheffield aEIT system. However the inter-individual differences observed in the subject-specific modelling behaviour of the {\textquoteleft}Resistivity-Lung Volume{\textquoteright} curves suggest that a model extension is needed, whereby the modelling structure auto-calibrates to account for subject (or patient-specific) inter-parameter variability",
author = "S. Mohamed-Samuri and G. Panoutsos and M. Mahfouf and G.H. Mills and Mouloud Denai and B.H. Brown",
year = "2013",
doi = "10.1007/978-3-642-29752-6_14",
language = "English",
isbn = "978-3-642-29751-9",
series = "Communications in Computer and Information Science",
publisher = "Springer",
pages = "191--204",
booktitle = "Biomedical Engineering Systems and Technologies",

}

RIS

TY - CHAP

T1 - Towards a Patient-Specific Model of Lung Volume Using Absolute Electrical Impedance Tomography (aEIT)

AU - Mohamed-Samuri, S.

AU - Panoutsos, G.

AU - Mahfouf, M.

AU - Mills, G.H.

AU - Denai, Mouloud

AU - Brown, B.H.

PY - 2013

Y1 - 2013

N2 - Electrical Impedance Tomography (EIT), and in particular its application to pulmonary measurement, has been the subject of intensive research since its development in the early 1980s by Barber and Brown. One of the relatively recent advances in EIT is the development of an absolute EIT system (aEIT) which can estimate absolute values of lung resistivity and associated lung volumes. In this paper we present a new approach based on Computational Intelligence (CI) modelling to model the ‘Resistivity - Lung Volume’ relationship that will allow more accurate lung volume estimations using data from eight (8) healthy volunteers measured simultaneously via the Sheffield aEIT system and a Spirometer. The developed models show an improved accuracy in the prediction of lung volumes, as compared with the original Sheffield aEIT system. However the inter-individual differences observed in the subject-specific modelling behaviour of the ‘Resistivity-Lung Volume’ curves suggest that a model extension is needed, whereby the modelling structure auto-calibrates to account for subject (or patient-specific) inter-parameter variability

AB - Electrical Impedance Tomography (EIT), and in particular its application to pulmonary measurement, has been the subject of intensive research since its development in the early 1980s by Barber and Brown. One of the relatively recent advances in EIT is the development of an absolute EIT system (aEIT) which can estimate absolute values of lung resistivity and associated lung volumes. In this paper we present a new approach based on Computational Intelligence (CI) modelling to model the ‘Resistivity - Lung Volume’ relationship that will allow more accurate lung volume estimations using data from eight (8) healthy volunteers measured simultaneously via the Sheffield aEIT system and a Spirometer. The developed models show an improved accuracy in the prediction of lung volumes, as compared with the original Sheffield aEIT system. However the inter-individual differences observed in the subject-specific modelling behaviour of the ‘Resistivity-Lung Volume’ curves suggest that a model extension is needed, whereby the modelling structure auto-calibrates to account for subject (or patient-specific) inter-parameter variability

U2 - 10.1007/978-3-642-29752-6_14

DO - 10.1007/978-3-642-29752-6_14

M3 - Chapter (peer-reviewed)

SN - 978-3-642-29751-9

T3 - Communications in Computer and Information Science

SP - 191

EP - 204

BT - Biomedical Engineering Systems and Technologies

PB - Springer

ER -