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Visual System

Visual System

Light enters the eye through the cornea, a transparent, dome-shaped surface covering the surface of the eyeball that helps to direct and focus incoming light. This light is then channeled toward the pupil, an adjustable opening whose size is controlled by the iris. The iris, a pigmented muscle, regulates the amount of light entering the eye by contracting or dilating the pupil, thereby ensuring optimal light levels for clear vision.
Once through the pupil, the light passes through the lens, a...

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Electrophysiological Measurements and Analysis of Nociception in Human Infants

Electrophysiological Measurements and Analysis of Nociception in Human Infants

Published on: December 20, 2011

Evaluating neonatal pain via fusing vision transformer and concept-cognitive computing.

Jing Lin¹, Liang Zhang², Jianhua Xia²

¹School of Computer and Artificial Intelligence, Huaihua University, Huaihua, 418000, China. linjing@hhtc.edu.cn.

Scientific Reports

|November 1, 2024

Summary

A new method, the pain concept-cognitive computing model (PainC3M), accurately assesses neonatal pain using facial expressions. This innovation helps reduce adverse effects from painful procedures in newborns.

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Area of Science:

Neonatal care
Computational intelligence
Medical image analysis

Background:

Neonatal pain assessment is critical for development but challenging in clinical nursing.
Repetitive painful treatments can adversely affect newborns during hospitalization.

Purpose of the Study:

To propose a novel method, the pain concept-cognitive computing model (PainC3M), for evaluating facial pain in newborns.
To reduce the negative impacts of painful medical procedures on neonatal development.

Main Methods:

Improved vision transformer attention mechanism with revised node encoding (spatial structure, edge, centrality) for feature extraction.
Utilized a concept-cognitive computing model as a classifier for pain level evaluation.
Integrated these components into the PainC3M fusion system.

Main Results:

PainC3M demonstrated high effectiveness in dynamic pain classification.
The model outperformed comparative models on various open datasets and a real clinical data stream.
Experimental results validate the efficacy of the proposed PainC3M.

Conclusions:

PainC3M offers a superior approach to neonatal facial pain assessment.
The method shows promise for assessing pain in individuals with communication impairments like aphasia or dementia.