Bio-Signals-based Situation Comparison Approach to Predict Pain

TL;DR

This paper introduces a novel time-series classification method that compares biomedical situations by analyzing bio-signals, regardless of their type, length, or quantity, to predict pain.

Contribution

It presents a new approach for biomedical situation comparison using time-series classification that is flexible to different data formats and sizes.

Findings

Effective classification of biomedical situations based on bio-signals.

Ability to compare situations regardless of time-series type or length.

Potential application in pain prediction and medical diagnostics.

Abstract

This paper describes a time-series-based classification approach to identify similarities between bio-medical-based situations. The proposed approach allows classifying collections of time-series representing bio-medical measurements, i.e., situations, regardless of the type, the length and the quantity of the time-series a situation comprised of.