One breath at a time : a feasibility study
department or school: Applied Science, Faculty of
department or school: Electrical and Computer Engineering, Department of
data provider: DSpace
degree campus: UBCV
creator: Verma, Shreya
issued: 2024-05-15T21:33:17Z
issued: 2024
related degree: Master of Applied Science - MASc
degree grantor: University of British Columbia
description: Measuring vital signs is crucial in healthcare as they provide essential information about a human body's physiological state. Particularly, the initial months following birth are crucial for the survival and well-being of newborns. Existing methods face challenges such as estimating incorrect respiratory rate values in low-light conditions, the inability to detect shallow breathing, overestimating respiratory values in darker skin tones and the need for contact sensors that may disturb sensitive infants. In this study, we propose a novel video-based respiratory rate estimation method for infants in the Neonatal Intensive Care Unit. Our method overcomes challenges by utilizing non-contact depth-sensing camera technology, which mitigates the impact of skin pigmentation on measurement accuracy. We conducted a study with 13 infants, recording uninterrupted 4-hour video sessions. We evaluated the algorithm's performance and robustness in various light conditions by analyzing randomly selected videos. We compared the respiratory rate estimated by our depth-sensing camera method with both a nurse practitioner's manually annotated reference respiratory rate and the respiratory rate estimated from red-green-blue (RGB) videos of the infants recorded during the same period as the depth videos. Our results record a bias of 0.125 bpm and a root mean squared difference accuracy of 1.058 bpm. Moreover, our proposed method exhibits a 26% increase in accuracy compared to the RGB camera-based method for respiratory rate estimation in infants. The Pearson correlation coefficient of 0.87 (p < 0.001) indicates a strong correlation, and the intraclass correlation coefficient of 0.77 (95%CI: 0.68 - 0.84 ) demonstrates good reliability. The Bland-Altman analysis of the proposed algorithm shows higher agreement between the values estimated by our developed method and the visually counted respiratory rate than the agreement between the respiratory rate obtained from the impedance sensors an…
aggregated CHO: https://circle.library.ubc.ca/rest/handle/2429/88291
note: One Breath at a TimeA Feasibility StudybyShreya VermaB.Tech, Vellore Institute of Technology, 2020A THESIS SUBMITTED IN PARTIAL FULFILLMENT OFTHE REQUIREMENTS FOR THE DEGREE OFMASTER OF APPLIED SCIENCEinThe Faculty of Graduate and Postdoctoral Studies(Electrical and Computer Engineering)THE UNIVERSITY OF BRITISH COLUMBIA(Vancouver)May 2024© Shreya Verma 2024The following individuals certify that they have read, and recommend tothe Faculty of Graduate and Postdoctoral Studies for acceptance, the thesisentitled:One Breath at a Time: A Feasibility Studysubmitted by Shreya Verma in partial fulfillment of the requirements forthe degree of Master of Applied Science in Electrical and ComputerEngineering.Examining Committee:Guy Dumont, Professor, Electrical and Computer Engineering, UBCSupervisorLiisa Holsti, Professor, Faculty of Medicine, UBCSupervisory Committee MemberPeyman Servati, Professor, Electrical and Computer Engineering, UBCSupervisory Committee MemberiiAbstractMeasuring vital signs is crucial in healthcare as they provide essential infor-mation about a human body’s physiological state. Particularly, the initialmonths following birth are crucial for the survival and well-being of new-borns. Existing methods face challenges such as estimating incorrect res-piratory rate values in low-light conditions, the inability to detect shallowbreathing, overestimating respiratory values in darker skin tones and theneed for contact sensors that may disturb sensitive infants. In this study,we propose a novel video-based respiratory rate estimation method for in-fants in the Neonatal Intensive Care Unit. Our method overcomes challengesby utilizing non-contact depth-sensing camera technology, which mitigatesthe impact of skin pigmentation on measurement accuracy. We conducteda study with 13 infants, recording uninterrupted 4-hour video sessions. Weevaluated the algorithm’s performance and robustness in various light condi-tions by analyzing randomly selected videos. We compare…
has type: Thesis/Dissertation
date issued: 2024-11
is shown at: 10.14288/1.0443335
language: eng
degree discipline: Electrical and Computer Engineering
provider: Vancouver : University of British Columbia Library
publisher: University of British Columbia
rights: Attribution-NonCommercial-NoDerivatives 4.0 International
rights URI: http://creativecommons.org/licenses/by-nc-nd/4.0/
scholar level: Graduate
contributor: Dumont, G. (Guy), 1951-
type: Text
identifier URI: http://hdl.handle.net/2429/88291