相关实验视频

Updated: Jun 24, 2025

Author Spotlight: Deciphering Electrical Networks Behind Complex Brain Activities and Disorders

Author Spotlight: Deciphering Electrical Networks Behind Complex Brain Activities and Disorders

Published on: November 1, 2024

使用深度学习进行疼痛评估的自动面部识别系统,用于大脑麻的成年人疼痛评估

Álvaro Sabater-Gárriz^1,2,3,4, F Xavier Gaya-Morey⁵, José María Buades-Rubio^3,5

¹Department of Research and Training, Balearic ASPACE Foundation, Marratxí, Spain.

|June 7, 2024

概括

自动面部识别显示,它有望评估脑 (CP) 患者的疼痛. 深度学习模型的准确度超过60%,为那些有沟通障碍的人提供了一个新的工具.

科学领域:

神经学神经学
计算机科学计算机科学
人工智能的人工智能

背景情况:

在脑 (CP) 中疼痛评估是困难的,因为沟通障碍.
现有的疼痛评估方法对于这一群体缺乏足够的敏感性和特异性.

研究的目的:

为患有CP的人开发面部疼痛表达数据集.
为CP患者的疼痛评估创建一个自动化的深度学习系统.

主要方法:

在现有疼痛数据库和新的CP-PAIN数据集 (109张图像) 上训练了10个神经网络.
使用专家分类与面部动作编码系统进行数据集注释.

主要成果:

在CP-PAIN数据集上,InceptionV3模型实现了62.67%的准确性和61.12%的F1得分.
可解释的AI证实了跨模型的一致疼痛识别特征.

结论:

深度学习和面部识别为神经通讯障碍患者的疼痛检测提供了潜在的解决方案.
扩大数据集可以提高CP患者和其他神经系统疾病的模型灵敏度.

关键词:

疼痛评估疼痛评估疼痛评估自动面部识别自动化面部识别脑性麻脑性麻是一种深度学习是一种深度学习.疼痛表达图像数据集数据集

更多相关视频

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

Multi-Modal Signals for Analyzing Pain Responses to Thermal and Electrical Stimuli

Multi-Modal Signals for Analyzing Pain Responses to Thermal and Electrical Stimuli

Published on: April 5, 2019

相关概念视频

Prosopagnosia

Prosopagnosia

Prosopagnosia, also known as face blindness, is the inability to recognize faces. In severe cases, individuals with prosopagnosia may not recognize close family members, including parents and spouses, by their faces. For instance, someone with prosopagnosia might walk past their child in a crowd, only realizing their mistake upon noticing their child's distinctive backpack or favorite jacket. Prosopagnosia specifically impairs facial recognition, while the recognition of other objects or...