Link to the University of Pittsburgh Homepage
Link to the University Library System Homepage Link to the Contact Us Form

Estimation of Cerebral Physiology and Hemodynamics via Near-Infrared Spectroscopy

Barker, Jeffrey (2015) Estimation of Cerebral Physiology and Hemodynamics via Near-Infrared Spectroscopy. Doctoral Dissertation, University of Pittsburgh. (Unpublished)

[img]
Preview
PDF
Primary Text

Download (3MB)

Abstract

Near-infrared spectroscopy (NIRS) is a non-invasive optical imaging technique that has rapidly been gaining popularity for study of the brain. Near-infrared spectroscopy measures absorption of light, primarily due to hemoglobin, through an array of light sources and detectors that are coupled to the scalp. Measurements can generally be divided into measurements of baseline physiology (related to total absorption) and measurements of hemodynamic time-series data (related to relative absorption changes). Because light intensity drops off rapidly with depth, NIRS measurements are highly sensitive to extracerebral tissues. Attempts to recover baseline physiology measurements of the brain can be confounded by high sensitivity to the scalp and skull. Time-series measurements contain high contributions of systemic physiology signals, including cardiac, respiratory, and blood pressure waves. Furthermore, measurements over time inevitably introduce artifacts due to subject motion.

The aim of this thesis was to develop improved analysis methods in the context of these NIRS specific confounding factors. The thesis consists of four articles that address specific issues in NIRS data analysis: (i) assessment of common data analysis procedures used to estimate oxygen saturation and hemoglobin content that assume a semi-infinite, homogeneous medium, (ii) testing the feasibility of improving oxygen saturation and hemoglobin measurements using multi-layered models, (iii) development of methods to estimate the general linear model for functional brain imaging that are robust to systemic physiology signals and motion artifacts, and (iv) the extension of (iii) to an adaptive method that is suitable for real-time analysis. Overall, this thesis helps to validate and advance analysis methods for NIRS.


Share

Citation/Export:
Social Networking:
Share |

Details

Item Type: University of Pittsburgh ETD
Status: Unpublished
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Barker, Jeffreyjwb52@pitt.eduJWB52
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairHuppert, Theodorehuppertt@upmc.eduHUPPERT1
Committee MemberLoughlin, Patrickloughlin@pitt.eduLOUGHLIN
Committee MemberIbrahim, Tameribrahimts@upmc.eduTSI2
Committee MemberPanigrahy, AshokAshok.Panigrahy@chp.eduASP55
Committee MemberVazquez, Albertoalv15@pitt.eduALV15
Date: 9 June 2015
Date Type: Publication
Defense Date: 25 November 2014
Approval Date: 9 June 2015
Submission Date: 2 December 2014
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Number of Pages: 150
Institution: University of Pittsburgh
Schools and Programs: Swanson School of Engineering > Bioengineering
Degree: PhD - Doctor of Philosophy
Thesis Type: Doctoral Dissertation
Refereed: Yes
Uncontrolled Keywords: near-infrared spectroscopy, NIRS, fNIRS, brain, physiology, light propagation,
Date Deposited: 09 Jun 2015 13:21
Last Modified: 19 Dec 2016 14:42
URI: http://d-scholarship.pitt.edu/id/eprint/23711

Metrics

Monthly Views for the past 3 years

Plum Analytics


Actions (login required)

View Item View Item