Modeling and Analysis of Monitored vs. Self-reported Postsurgical Acute Pain in a Clinical Trial

Abstract

This work aims to study postsurgical trauma modeling to characterize the physiological process in postoperative pain assessment in an observational trial. The skin impedance data is proposed to be fitted by derived-Cole models, i.e., single and double dispersion models and a distributed model with an inductive term related to sweat glands. These models are motivated by the biological characteristics of the skin, its physiological stratification and the current intra-and extra-cellular pathways. The correlation between the identified parameters with the patient's pain reported using the numerical rating scale (NRS) is analyzed for one patient for all three models. Following the trial, a statistically significant positive linear relationship was observed between the Anspec-Pro index and NRS (r(2) = 0.16, p=0.00), driving the further study of the relationship between the estimated dielectric parameters. The paper focuses to analyze the changes of the coefficients related to the particular clinical data, successfully identified using the non-linear least square procedure. The clinical significance of the results may be related to the individual model parameters for postoperative pain detection, validated on patients. Copyright (C) 2021 The Authors.