Explainable fNIRS-based pain decoding under pharmacological conditions via deep transfer learning approach.

ABSTRACT:

Significance

Assessment of pain and its clinical diagnosis rely on subjective methods which become even more complicated under analgesic drug administrations.

Aim

We aim to propose a deep learning (DL)-based transfer learning (TL) methodology for objective classification of functional near-infrared spectroscopy (fNIRS)-derived cortical oxygenated hemoglobin responses to painful and non-painful stimuli presented under different timings post-analgesic and placebo drug administration.

Approach

A publicly available fNIRS dataset obtained during painful/non-painful stimuli was used. Separate fNIRS scans were taken under the same protocol before drug (morphine and placebo) administration and at three different timings (30, 60, and 90 min) post-administration. Data from pre-

SUBMITTER: Eken A 

PROVIDER: S-EPMC11651663 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature