A Model-Based Framework for Assessing the Physiologic Structure of Electrodermal Activity.

ABSTRACT:

Objective

We present a statistical model for extracting physiologic characteristics from electrodermal activity (EDA) data in observational settings.

Methods

We based our model on the integrate-and-fire physiology of sweat gland bursts, which predicts inverse Gaussian (IG) inter-pulse interval structure. At the core of our model-based paradigm is a subject-specific amplitude threshold selection process for EDA pulses based on the statistical properties of four right-skewed models including the IG. By performing a sensitivity analysis across thresholds and fitting all four models, we selected for IG-like structure and verified the pulse selection with a goodness-of-fit analysis, maximizing capture of physiology at the time scale of EDA responses.

Results

We tested the

SUBMITTER: Subramanian S 

PROVIDER: S-EPMC8425954 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature