减压性气泡多普勒评级

Doppler grading for decompression bubbles

超声气泡探测法在预测减压病发生风险和减压程序效率及安全性评估中得到广泛应用。目前运用较为广泛的SPENCER气泡评级通过使用多普勒超声监测被检测者心前区气泡信号进行评级;KM评级是基于多普勒超声的适用于计算机处理的评级系统,该评级分数可转化为SPENCER气泡评级的分数,对气泡的分级更精细且适用于运动状态。在上述两种方法的基础上建立的KISMAN综合严重度分值、扩展SPENCER气泡评级和多普勒气泡简化评级系统,不仅将多普勒超声气泡探测结果与其他减压病风险因素协同分析,还便于利用计算机对探测结果进行处理。随着傅里叶技术、经验模式分解等在多普勒音频气泡信号检测中的深入应用,三参量模糊分析和能量算子法等方法在气泡自动分析中仍发挥重要作用。优化检测技术、提高自动分析灵敏度和准确性仍是减压性气泡多普勒评级技术领域发展的重要方向。

Ultrasonic bubble detection has been widely used in predicting the risk of decompression sickness and evaluating the efficiency and safety of decompression procedures. Currently, the widely used SPENCER scale is conducted by using Doppler ultrasound to monitor the bubble signal in the precordial region of subjects. KM grading system is a computerized system based on Doppler ultrasound. The grading score can be converted into SPENCER bubble grading scale score and the bubble grading is precise and suitable for the motion status. On the basis of the above two methods, the KISMAN integrated severity score, extended SPENCER bubble grading and simplified Doppler bubble grading system were established. They not only coordinated analysis of Doppler ultrasound bubble detection results with other risk factors of decompression disease, but also convenient to use computer for processing detection results. With the in-depth application of Fourier technique and empirical mode decomposition in Doppler audio bubble signal detection, methods such as three-parameter fuzzy analysis and energy operator method are playing an important role in automatic bubble analysis. Optimization of detection technology and improvement of sensitivity and accuracy of automatic analysis are important development directions in the field of decompression bubble Doppler grating technology.