A Personalized Spatial-Temporal Cold Pain Intensity Estimation Model Based on Facial Expression.
A Personalized Spatial-Temporal Cold Pain Intensity Estimation Model Based on Facial Expression.
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DOI：
10.1109/jtehm.2021.3116867
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发表时间：
2021
影响因子：
3.4
通讯作者：
Lin Y
中科院分区：
文献类型：
--
作者：
Guo Y;Wang L;Xiao Y;Lin Y
目的：疼痛评估在临床研究和患者护理中具有重要意义。面部表情分析因其方便、自动和实时的特点，正成为疼痛检测的关键部分。本研究的目的是提出一个冷痛强度估计实验，调查的时空信息的重要性，基于面部表情的冷痛，并研究个性化模型和广义模型的性能。方法：采用冷痛实验，提取29名被试的面部表情。三种不同的架构（Inception V3、VGG-LSTM和卷积LSTM）被用来估计冷痛的三种强度：无痛、中度疼痛和重度疼痛。将具有顺序信息的架构与单帧架构进行了比较，显示了时空信息对疼痛估计的重要性。并对个性化模型和广义模型的性能进行了比较。结果：使用基于个性化模型的卷积LSTM，平均F1得分为79.48%。结论：这项研究证明了从面部表情分析中估计冷痛强度的潜力，并表明个性化的时空框架在冷痛强度估计中具有更好的性能。重要性：这种冷疼痛强度估计器可以允许方便、自动和实时使用，以提供受试者和患者的连续客观疼痛强度估计。
Objective: Pain assessment is of great importance in both clinical research and patient care. Facial expression analysis is becoming a key part of pain detection because it is convenient, automatic, and real-time. The aim of this study is to present a cold pain intensity estimation experiment, investigate the importance of the spatial-temporal information on facial expression based cold pain, and study the performance of the personalized model as well as the generalized model. Methods: A cold pain experiment was carried out and facial expressions from 29 subjects were extracted. Three different architectures (Inception V3, VGG-LSTM, and Convolutional LSTM) were used to estimate three intensities of cold pain: No pain, Moderate pain, and Severe Pain. Architectures with Sequential information were compared with single-frame architecture, showing the importance of spatial-temporal information on pain estimation. The performances of the personalized model and the generalized model were also compared. Results: A mean F1 score of 79.48% was achieved using Convolutional LSTM based on the personalized model. Conclusion: This study demonstrates the potential for the estimation of cold pain intensity from facial expression analysis and shows that the personalized spatial-temporal framework has better performance in cold pain intensity estimation. Significance: This cold pain intensity estimator could allow convenient, automatic, and real-time use to provide continuous objective pain intensity estimations of subjects and patients.