Measuring Peripheral Signal Complexity Values by Applying Non-linear Method to Medical Laser Contrast Images

1Adil I. Khalil, Waleed A. Hassen, Ahmed K. Abas, Anne Humeau-Hurtier, Mareb N. Al-Khalidi

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Abstract:

The physiological signals are considered as a sensitive measure for describing human state. The evaluation of such signals could be accomplished by monitoring peripheral blood flow in the skin. Laser speckle contrast imaging (LSCI) is an optical-based imaging device produces high quality images of microvascular blood flow. In this article, a research study is presented to measure signal complexity values of leg microvascular blood flow into two age healthy groups. Microvascular blood flow of leg skin was acquired using LSCI. The research sample consisted of 18 healthy individuals, divided into two groups according to the age: young group (20 to 30 years old, n=10) and aged group (50 to 70 years old, n=10). Signal complexity values of microvascular blood flow were computed by applying nonlinear algorithm to LSCI data of leg. The use of nonlinear methods to compute leg signal complexity values by processing LSCI data revealed higher entropy values obtained from young group than the ones obtained from aged group. However, the differences on signal complexity values between young and aged groups were not significant (p=0.65). Furthermore, applying nonlinear methods to LSCI data of leg could be used to estimate the deterioration of blood flow in peripheral vessels. Further studies with more subjects are needed to confirm the results presented in this paper. In addition, a comparative study with another body part may give new insight on the peripheral vessels dysfunction associated with aging.

Keywords:

ALaser contrast images, Image processing, Information theory, Entropy, Microcirculation.

Paper Details
Month4
Year2020
Volume24
IssueIssue 6
Pages5529-5535