标题： 意识-心电图变换器用于具有实时监测的意识状态估计系统 显示英文标题

标题： Consciousness-ECG Transformer for Conscious State Estimation System with Real-Time Monitoring

摘要： 意识状态估计在各种医疗环境中非常重要，包括睡眠分期和麻醉管理，以确保患者安全并优化健康结果。 传统方法主要利用脑电图（EEG），这面临着对噪声高度敏感和需要受控环境等挑战。 在本研究中，我们提出了意识-心电图变换器，利用心电图（ECG）信号进行非侵入性和可靠的意识状态估计。 我们的方法采用解耦查询注意力的变换器，以有效捕捉区分清醒和无意识状态的心率变异性特征。 我们实现了具有实时监测的意识状态估计系统，并在涉及睡眠分期和手术期间麻醉水平监测的数据集上验证了我们的系统。 实验结果表明，我们的模型优于基线模型，在睡眠分期上的准确率为0.877，在麻醉水平监测上的准确率为0.880。 此外，我们的模型在睡眠分期和麻醉水平监测上的曲线下面积分别达到0.786和0.895。 所提出的系统为基于EEG的方法提供了一个实用且稳健的替代方案，特别适合动态临床环境。 我们的结果突显了基于ECG的意识监测在提高患者安全性和推进对意识状态理解方面的潜力。 显示英文摘要

摘要： Conscious state estimation is important in various medical settings, including sleep staging and anesthesia management, to ensure patient safety and optimize health outcomes. Traditional methods predominantly utilize electroencephalography (EEG), which faces challenges such as high sensitivity to noise and the requirement for controlled environments. In this study, we propose the consciousness-ECG transformer that leverages electrocardiography (ECG) signals for non-invasive and reliable conscious state estimation. Our approach employs a transformer with decoupled query attention to effectively capture heart rate variability features that distinguish between conscious and unconscious states. We implemented the conscious state estimation system with real-time monitoring and validated our system on datasets involving sleep staging and anesthesia level monitoring during surgeries. Experimental results demonstrate that our model outperforms baseline models, achieving accuracies of 0.877 on sleep staging and 0.880 on anesthesia level monitoring. Moreover, our model achieves the highest area under curve values of 0.786 and 0.895 on sleep staging and anesthesia level monitoring, respectively. The proposed system offers a practical and robust alternative to EEG-based methods, particularly suited for dynamic clinical environments. Our results highlight the potential of ECG-based consciousness monitoring to enhance patient safety and advance our understanding of conscious states.