UTHM Institutional Repository

Quantitative analysis of spectroscopy data for skin oximetry

Huong, Audrey and Ngu, Xavier (2016) Quantitative analysis of spectroscopy data for skin oximetry. In: ICBBE '16 Proceedings of the 3rd International Conference on Biomedical and Bioinformatics Engineering, November 12 - 14, 2016, Taipei, Taiwan.

Full text not available from this repository.

Abstract

This work presented the use of Modified Lambert Beer law (MLBL), Extended Modified Lambert Beer model (EMLB) and cumulant based forward model (CM) for the estimation of mean blood oxygen saturation (SmO2) in skin of healthy individuals via an iterative fitting routine. The proposed strategy required a priori knowledge of extinction coefficients of hemoglobin components in the wavelength range of 520-600 nm to give the best estimation of SmO2. This study conducted spectroscopy measurement on left index finger of four Asians at rest condition. Quantitative analysis of the collected data using the employed strategy revealed SmO2 with mean value of 71.5 ± 1.15 %, 95.1 ± 3 % and 96.3 ± 3.8 % given by MLBL, EMLB and CM, respectively. The consistent and high SmO2 value estimated by EMLB and CM agreed considerably well with the value reported in the literature. The underestimation of SmO2 given by the MLBL could be a result of insufficiency of the model at describing light propagation in skin. This work concluded that both EMLB and CM, and the proposed strategy can suitably be used in clinical setting for skin oximetry.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Skin oximetry; extended modified Lambert Beer model; cumulant based forward model; point spectroscopy
Subjects: Q Science > QC Physics
Divisions: Faculty of Electrical and Electronic Engineering > Department of Electronic Engineering
Depositing User: Mr. Mohammad Shaifulrip Ithnin
Date Deposited: 13 Aug 2018 03:22
Last Modified: 13 Aug 2018 03:22
URI: http://eprints.uthm.edu.my/id/eprint/9608
Statistic Details: View Download Statistic

Actions (login required)

View Item View Item