Autonomous Sensory Meridian Response (ASMR) is a somatosensory phenomenon characterized by pleasant tingling sensations and cardiovascular slowing. However, ASMR research has been hindered by a dearth of standardized, open-access multimodal datasets. To address this limitation, we present REST-ASMR (Response to Environmental & Sensory Triggers), a synchronized multimodal dataset designed to capture behavioral reports and physiological dynamics during ASMR, with nature-relaxation videos as control stimuli. The dataset includes high-resolution photoplethysmography (PPG), time-aligned audiovisual stimuli, and continuous subjective annotations from 34 participants. Technical validation showed high stimulus efficacy (97% responder rate), significant stimulus-specific inter-subject agreement (p < 0.05), and a robust PPG-derived ASMR-specific cardiovascular deceleration. Additionally, a Bidirectional Long-Short Term Memory model successfully predicted subjective ASMR tingle states, achieving video-level ASMR vs. Nature classification with perfect accuracy and a frame-level global mean accuracy of 75.51%, macro F1-score of 71.86%, and 100% Nature-baseline specificity, under a strict, leakage-free subject-video double-independent 4-fold cross-validation. REST-ASMR constitutes a dense temporal foundation for affective computing, multimodal research, and the development of personalized models of relaxation-related responses.

翻译：自主感官经络反应（ASMR）是一种以愉悦针刺感和心血管减慢为特征的体感现象。然而，ASMR研究因缺乏标准化、开放获取的多模态数据集而受到阻碍。为解决这一局限，我们提出了REST-ASMR（环境与感官触发反应），这是一个同步的多模态数据集，旨在捕捉ASMR期间的行为报告和生理动态，并以自然放松视频作为对照刺激。该数据集包括来自34名参与者的高分辨率光电容积描记法（PPG）、时间对齐的视听刺激以及连续主观标注。技术验证显示刺激有效性高（响应率为97%）、显著的刺激特异性主体间一致性（p < 0.05），以及稳健的基于PPG的ASMR特异性心血管减速。此外，一个双向长短期记忆模型成功预测了主观ASMR刺痛状态，在严格、无泄漏的主视频双独立4折交叉验证下，实现了视频级ASMR与自然分类的完美准确率，以及帧级全局平均准确率75.51%、宏F1分数71.86%和100%自然基线特异性。REST-ASMR为情感计算、多模态研究以及开发放松相关反应的个性化模型奠定了密集的时间基础。