Method for sensing risk events in multi-mode human physiological signals based on clinical anesthesia

The invention discloses a method for sensing risk events in a multi-modal human body physiological signal based on clinical anesthesia, and the method is characterized in that the method comprises the steps: 1, obtaining the time sequence data of the multi-modal human body physiological signal; 2, converting the time sequence data from a time domain to a frequency domain based on Fourier transform; step 3, performing characterization alignment by using a comparative learning method; and step 4, analyzing the data after characterization alignment and outputting a classification result. According to the sensing method, accurate sensing and timely early warning of risk events in the anesthesia process of the patient can be realized, and the safety and efficiency of the anesthesia process are greatly improved. 本发明公开了一种基于临床麻醉多模态人体生理信号中风险事件感知方法，其特征在于，所述感知方法包括：步骤1、获取多模态人体生理信号时序数据；步骤2、基于傅立叶变换将时序数据从时域转换到频域；步骤3、利用对比学习方法进行表征对齐；步骤4、对表征对齐后的数据进行分析并输出分类结果。该感知方法能够实现对患者麻醉过程中风险事件的准确感知和及时预警，大大提高了麻醉过程的安全性和效率。