A multidimensional signal processing approach for classification of microwave measurements with application to stroke type diagnosis

Hamed Yousefi Mesri; Masoud Khazaeli Najafabadi; Tomas McKelvey

doi:10.1109/IEMBS.2011.6091596

A multidimensional signal processing approach for classification of microwave measurements with application to stroke type diagnosis

Hamed Yousefi Mesri, Masoud Khazaeli Najafabadi, Tomas McKelvey

Research output: Contribution to journal › Article › Academic › peer-review

Abstract

A multidimensional signal processing method is described for detection of bleeding stroke based on microwave measurements from an antenna array placed around the head of the patient. The method is data driven and the algorithm uses samples from a healthy control group to calculate the feature used for classification. The feature is derived using a tensor approach and the higher order singular value decomposition is a key component. A leave-one-out validation method is used to evaluate the properties of the method using clinical data.

Original language	English
Pages (from-to)	6465-9
Number of pages	5
Journal	Conference proceedings : IEEE Engineering in Medicine and Biology Society. Conference
Volume	2011
DOIs	https://doi.org/10.1109/IEMBS.2011.6091596
Publication status	Published - 2011

Keywords

Algorithms
Artificial Intelligence
Cerebral Hemorrhage
Decision Support Systems, Clinical
Decision Support Techniques
Electromagnetic Radiation
Equipment Design
Humans
Microwaves
Models, Statistical
Models, Theoretical
Scattering, Radiation
Signal Processing, Computer-Assisted
Stroke
Journal Article

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10.1109/IEMBS.2011.6091596

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title = "A multidimensional signal processing approach for classification of microwave measurements with application to stroke type diagnosis",

abstract = "A multidimensional signal processing method is described for detection of bleeding stroke based on microwave measurements from an antenna array placed around the head of the patient. The method is data driven and the algorithm uses samples from a healthy control group to calculate the feature used for classification. The feature is derived using a tensor approach and the higher order singular value decomposition is a key component. A leave-one-out validation method is used to evaluate the properties of the method using clinical data.",

keywords = "Algorithms, Artificial Intelligence, Cerebral Hemorrhage, Decision Support Systems, Clinical, Decision Support Techniques, Electromagnetic Radiation, Equipment Design, Humans, Microwaves, Models, Statistical, Models, Theoretical, Scattering, Radiation, Signal Processing, Computer-Assisted, Stroke, Journal Article",

author = "Mesri, {Hamed Yousefi} and Najafabadi, {Masoud Khazaeli} and Tomas McKelvey",

year = "2011",

doi = "10.1109/IEMBS.2011.6091596",

language = "English",

volume = "2011",

pages = "6465--9",

journal = "Conference proceedings : IEEE Engineering in Medicine and Biology Society. Conference",

issn = "1557-170X",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

}

A multidimensional signal processing approach for classification of microwave measurements with application to stroke type diagnosis. / Mesri, Hamed Yousefi; Najafabadi, Masoud Khazaeli; McKelvey, Tomas.
In: Conference proceedings : IEEE Engineering in Medicine and Biology Society. Conference, Vol. 2011, 2011, p. 6465-9.

Research output: Contribution to journal › Article › Academic › peer-review

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T1 - A multidimensional signal processing approach for classification of microwave measurements with application to stroke type diagnosis

AU - Mesri, Hamed Yousefi

AU - Najafabadi, Masoud Khazaeli

AU - McKelvey, Tomas

PY - 2011

Y1 - 2011

N2 - A multidimensional signal processing method is described for detection of bleeding stroke based on microwave measurements from an antenna array placed around the head of the patient. The method is data driven and the algorithm uses samples from a healthy control group to calculate the feature used for classification. The feature is derived using a tensor approach and the higher order singular value decomposition is a key component. A leave-one-out validation method is used to evaluate the properties of the method using clinical data.

AB - A multidimensional signal processing method is described for detection of bleeding stroke based on microwave measurements from an antenna array placed around the head of the patient. The method is data driven and the algorithm uses samples from a healthy control group to calculate the feature used for classification. The feature is derived using a tensor approach and the higher order singular value decomposition is a key component. A leave-one-out validation method is used to evaluate the properties of the method using clinical data.

KW - Algorithms

KW - Artificial Intelligence

KW - Cerebral Hemorrhage

KW - Decision Support Systems, Clinical

KW - Decision Support Techniques

KW - Electromagnetic Radiation

KW - Equipment Design

KW - Humans

KW - Microwaves

KW - Models, Statistical

KW - Models, Theoretical

KW - Scattering, Radiation

KW - Signal Processing, Computer-Assisted

KW - Stroke

KW - Journal Article

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DO - 10.1109/IEMBS.2011.6091596

M3 - Article

C2 - 22255819

SN - 1557-170X

VL - 2011

SP - 6465

EP - 6469

JO - Conference proceedings : IEEE Engineering in Medicine and Biology Society. Conference

JF - Conference proceedings : IEEE Engineering in Medicine and Biology Society. Conference

ER -

A multidimensional signal processing approach for classification of microwave measurements with application to stroke type diagnosis

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Keywords

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