Machinery Failure Approach and Spectral Analysis to study the Reaction Time Dynamics over Consecutive Visual Stimuli

TL;DR

This study applies spectral analysis and failure machinery models to analyze reaction time dynamics over consecutive visual stimuli, revealing correlated response patterns and failure-like behaviors among individuals.

Contribution

It introduces a novel application of spectral entropy and failure machinery concepts to reaction time analysis in cognitive experiments.

Findings

Reaction times are correlated among individuals.

Spectral features show similarity in response patterns.

Participants' mistakes follow a failure behavior modeled by MTBF.

Abstract

The reaction times of individuals over consecutive visual stimuli have been studied using spectral analysis and a failure machinery approach. The used tools include the fast Fourier transform and a spectral entropy analysis. The results indicate that the reaction times produced by the independently responding individuals to visual stimuli appear to be correlated. The spectral analysis and the entropy of the spectrum yield that there are features of similarity in the response times of each participant and among them. Furthermore, the analysis of the mistakes made by the participants during the reaction time experiments concluded that they follow a behavior which is consistent with the MTBF (Mean Time Between Failures) model, widely used in industry for the predictive diagnosis of electrical machines and equipment.