发表机构
University of Connecticut（康涅狄格大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文提出一种多模态自主感知框架，融合ECG-SKNA、RRI和EDA信号，用于客观评估牙髓冷刺激反应，在二分类中达到80.2%平衡准确率，验证了非侵入性客观评估的可行性。
AI 中文摘要
患者对牙髓测试的反应，从无感觉到剧烈疼痛，为牙髓病诊断中评估牙髓状态提供了重要信息。然而，疼痛是一种主观的感觉和情感体验，在不同个体间差异显著，且难以沟通。我们研究了互补的自主神经信号是否能够支持牙科检查期间反应的客观评估。四十九名患者接受了冷牙髓测试，产生了无反应、轻度反应和剧烈反应三种条件。该框架整合了ECG衍生的皮肤神经活动（SKNA）和R-R间期（RRI），以及皮肤电活动（EDA），使用带有基于注意力的中期融合的时间卷积网络编码器。个体基线信号和受试者水平的协变量，包括焦虑评分和生物学性别，也被纳入。该框架在无反应与轻度或剧烈反应的二分类中实现了80.2%的平衡准确率、75.2%的灵敏度和85.2%的特异性。在三分类中，它实现了60.0%的平衡准确率和58.8%的宏平均F1分数。消融和注意力权重分析表明，EDA对模型性能的贡献最大，其次是RRI，而SKNA将平衡准确率提高了约五个百分点。年龄与模型性能显著相关。这些发现支持了多模态自主感知用于客观、非侵入性评估牙髓刺激反应的可行性。
英文摘要
Patient responses to dental pulp testing, ranging from no sensation to intense pain, provide important information for assessing pulp status in endodontic diagnosis. However, pain is a subjective sensory and emotional experience that varies considerably across individuals and can be difficult to communicate. We investigated whether complementary autonomic signals could support objective assessment of responses during dental examination. Forty-nine patients underwent cold pulp testing, yielding no-response, mild-response, and intense-response conditions. The framework integrated ECG-derived skin nerve activity (SKNA) and R-R intervals (RRI), together with electrodermal activity (EDA), using temporal convolutional network encoders with attention-based mid-level fusion. Individual baseline signals and subject-level covariates, including anxiety scores and biological sex, were also incorporated. The framework achieved 80.2% balanced accuracy, 75.2% sensitivity, and 85.2% specificity for binary classification of no response versus mild or intense response. For three-class classification, it achieved 60.0% balanced accuracy and a 58.8% macro-averaged F1 score. Ablation and attention-weight analyses indicated that EDA contributed most strongly to model performance, followed by RRI, while SKNA improved balanced accuracy by approximately five percentage points. Age was significantly associated with model performance. These findings support the feasibility of multimodal autonomic sensing for objective, non-invasive assessment of responses to dental pulp stimulation.
Comments14 pages, 9 figures
