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Detrending and denoising of impedance cytometry data

Descriptive

TitleInfo
Title
Detrending and denoising of impedance cytometry data
Name (type = personal)
NamePart (type = family)
Cao
NamePart (type = given)
Xinnan
NamePart (type = date)
1994-
DisplayForm
Xinnan Cao
Role
RoleTerm (authority = RULIB)
author
Name (type = personal)
NamePart (type = family)
Javanmard
NamePart (type = given)
Mehdi
DisplayForm
Mehdi Javanmard
Affiliation
Advisory Committee
Role
RoleTerm (authority = RULIB)
chair
Name (type = personal)
NamePart (type = family)
Bajwa
NamePart (type = given)
Waheed
DisplayForm
Waheed Bajwa
Affiliation
Advisory Committee
Role
RoleTerm (authority = RULIB)
internal member
Name (type = personal)
NamePart (type = family)
Najafizadeh
NamePart (type = given)
Laleh
DisplayForm
Laleh Najafizadeh
Affiliation
Advisory Committee
Role
RoleTerm (authority = RULIB)
internal member
Name (type = corporate)
NamePart
Rutgers University
Role
RoleTerm (authority = RULIB)
degree grantor
Name (type = corporate)
NamePart
Graduate School - New Brunswick
Role
RoleTerm (authority = RULIB)
school
TypeOfResource
Text
Genre (authority = marcgt)
theses
OriginInfo
DateCreated (encoding = w3cdtf); (qualifier = exact)
2015
DateOther (qualifier = exact); (type = degree)
2015-10
CopyrightDate (encoding = w3cdtf); (qualifier = exact)
2015
Place
PlaceTerm (type = code)
xx
Language
LanguageTerm (authority = ISO639-2b); (type = code)
eng
Abstract (type = abstract)
Bioelectrical signals such as electrocardiogram (ECG) and flow cytometry signals are often affected by both low-frequency and high frequency perturbations during data acquisition. It is necessary to remove these interferences from the acquired data so that the pertinent information needed from these signals can be obtained. Methods for detrending and denoising in ECG are well established, but in the context of impedance cytometry data, there lacks a body of literature available that provides guidance as to a robust methodology for processing the data. For the first time in the context of impedance cytometry, to the best of our knowledge, in this work we systematically studied and compared the performance of different algorithms for detrending and denoising, and developed a procedure to analyze impedance cytometry data with minimal error. This work can serve as guidance to select the optimal algorithm based on the following parameters: Standard Deviation, Correlation Coefficient, Power Spectral Density (PSD), Root Mean Square Error (RMSE) and Root Mean Square Difference (RMSD). The approaches discussed conventional filtering techniques such as: Butterworth Filtering, Chebyshev Filtering, as well as the thresholding techniques in the Discrete Wavelet Transform (DWT). The procedure of selecting the mother wavelet basis functions and the four different thresholding methods are discussed and compared. The performance of the optimized algorithm is compared with the pClamp10 commercially available cytometry analysis software resulting in 19.2% improvement in amplitude preservation, 18.4% improvement in area preservation and more than 50% improvement in the peak-search error rate.
Subject (authority = RUETD)
Topic
Electrical and Computer Engineering
RelatedItem (type = host)
TitleInfo
Title
Rutgers University Electronic Theses and Dissertations
Identifier (type = RULIB)
ETD
Identifier
ETD_6827
PhysicalDescription
Form (authority = gmd)
electronic resource
InternetMediaType
application/pdf
InternetMediaType
text/xml
Extent
1 online resource (viii, 37 p. : ill.)
Note (type = degree)
M.S.
Note (type = bibliography)
Includes bibliographical references
Subject (authority = ETD-LCSH)
Topic
Cytometry
Subject (authority = ETD-LCSH)
Topic
Electrocardiography
Note (type = statement of responsibility)
by Xinnan Cao
RelatedItem (type = host)
TitleInfo
Title
Graduate School - New Brunswick Electronic Theses and Dissertations
Identifier (type = local)
rucore19991600001
Location
PhysicalLocation (authority = marcorg); (displayLabel = Rutgers, The State University of New Jersey)
NjNbRU
Identifier (type = doi)
doi:10.7282/T3CV4KQ3
Genre (authority = ExL-Esploro)
ETD graduate
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Rights

RightsDeclaration (ID = rulibRdec0006)
The author owns the copyright to this work.
RightsHolder (type = personal)
Name
FamilyName
Cao
GivenName
Xinnan
Role
Copyright Holder
RightsEvent
Type
Permission or license
DateTime (encoding = w3cdtf); (qualifier = exact); (point = start)
2015-09-29 17:49:20
AssociatedEntity
Name
Xinnan Cao
Role
Copyright holder
Affiliation
Rutgers University. Graduate School - New Brunswick
AssociatedObject
Type
License
Name
Author Agreement License
Detail
I hereby grant to the Rutgers University Libraries and to my school the non-exclusive right to archive, reproduce and distribute my thesis or dissertation, in whole or in part, and/or my abstract, in whole or in part, in and from an electronic format, subject to the release date subsequently stipulated in this submittal form and approved by my school. I represent and stipulate that the thesis or dissertation and its abstract are my original work, that they do not infringe or violate any rights of others, and that I make these grants as the sole owner of the rights to my thesis or dissertation and its abstract. I represent that I have obtained written permissions, when necessary, from the owner(s) of each third party copyrighted matter to be included in my thesis or dissertation and will supply copies of such upon request by my school. I acknowledge that RU ETD and my school will not distribute my thesis or dissertation or its abstract if, in their reasonable judgment, they believe all such rights have not been secured. I acknowledge that I retain ownership rights to the copyright of my work. I also retain the right to use all or part of this thesis or dissertation in future works, such as articles or books.
Copyright
Status
Copyright protected
Availability
Status
Open
Reason
Permission or license
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Technical

RULTechMD (ID = TECHNICAL1)
ContentModel
ETD
OperatingSystem (VERSION = 5.1)
windows xp
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