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基于脑电图(EEG)和面部肌电图(EMG)联合分析的个体疼痛感知、脑电活动与面部表情之间关系的研究

The Investigation of the Relationship Between Individual Pain Perception, Brain Electrical Activity, and Facial Expression Based on Combined EEG and Facial EMG Analysis.

作者信息

Ma Chaozong, Wang Chenxi, Zhu Dan, Chen Mingfang, Zhang Ming, He Juan

机构信息

Department of Rehabilitation Medicine, First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, People's Republic of China.

Military Medical Psychology School, Fourth Military Medical University, Xi'an, People's Republic of China.

出版信息

J Pain Res. 2025 Jan 3;18:21-32. doi: 10.2147/JPR.S477658. eCollection 2025.

Abstract

PURPOSE

Pain is a multidimensional, unpleasant emotional and sensory experience, and accurately assessing its intensity is crucial for effective management. However, individuals with cognitive impairments or language deficits may struggle to accurately report their pain. EEG provides insight into the neurological aspects of pain, while facial EMG captures the sensory and peripheral muscle responses. Our objective is to explore the relationship between individual pain perception, brain activity, and facial expressions through a combined analysis of EEG and facial EMG, aiming to provide an objective and multidimensional approach to pain assessment.

METHODS

We investigated pain perception in response to electrical stimulation of the middle finger in 26 healthy subjects. The 32-channel EEG and 3-channel facial EMG signals were simultaneously recorded during a pain rating task. Group difference and correlation analysis were employed to investigate the relationship between individual pain perception, EEG, and facial EMG. The general linear model (GLM) was used for multidimensional pain assessment.

RESULTS

The EEG analysis revealed that painful stimuli induced N2-P2 complex waveforms and gamma oscillations, with substantial variability in response to different stimuli. The facial EMG signals also demonstrated significant differences and variability correlated with subjective pain ratings. A combined analysis of EEG and facial EMG data using a general linear model indicated that both N2-P2 complex waveforms and the zygomatic muscle responses significantly contributed to pain assessment.

CONCLUSION

Facial EMG signals provide pain descriptions which are not sufficiently captured by EEG signals, and integrating both signals offers a more comprehensive understanding of pain perception. Our study underscores the potential of multimodal neurophysiological measurements in pain perception, offering a more comprehensive framework for evaluating pain.

摘要

目的

疼痛是一种多维度的、令人不适的情绪和感觉体验,准确评估其强度对于有效管理至关重要。然而,认知障碍或语言缺陷的个体可能难以准确报告他们的疼痛。脑电图(EEG)能深入了解疼痛的神经学方面,而面部肌电图(EMG)则能捕捉感觉和外周肌肉反应。我们的目标是通过对EEG和面部EMG的联合分析,探索个体疼痛感知、大脑活动和面部表情之间的关系,旨在提供一种客观且多维度的疼痛评估方法。

方法

我们调查了26名健康受试者在中指受到电刺激时的疼痛感知。在疼痛评分任务期间,同时记录32通道的EEG和3通道的面部EMG信号。采用组间差异和相关性分析来研究个体疼痛感知、EEG和面部EMG之间的关系。使用一般线性模型(GLM)进行多维度疼痛评估。

结果

EEG分析表明,疼痛刺激诱发了N2 - P2复合波形和伽马振荡,对不同刺激的反应存在显著差异。面部EMG信号也显示出与主观疼痛评分相关的显著差异和变异性。使用一般线性模型对EEG和面部EMG数据进行联合分析表明,N2 - P2复合波形和颧肌反应均对疼痛评估有显著贡献。

结论

面部EMG信号提供了EEG信号未充分捕捉到的疼痛描述,整合这两种信号能更全面地理解疼痛感知。我们的研究强调了多模态神经生理学测量在疼痛感知中的潜力,为评估疼痛提供了一个更全面的框架。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3d0c/11705972/2eeca38d7797/JPR-18-21-g0001.jpg

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