Shafqat K, Pal S K, Kumari S, Kyriacou P A
Engineering and Mathematical Sciences (SEMS), City University, London, UK.
Annu Int Conf IEEE Eng Med Biol Soc. 2009;2009:2244-7. doi: 10.1109/IEMBS.2009.5335000.
Spectral analysis of Heart Rate Variability (HRV) is used for the assessment of cardiovascular autonomic control. In this study data driven adaptive technique Empirical Mode Decomposition (EMD) and the associated Hilbert spectrum has been used to evaluate the effect of local anesthesia on HRV parameters in a group of fourteen patients undergoing brachial plexus block (local anesthesia) using transarterial technique. The confidence limit for the stopping criteria was establish and the S value that gave the smallest squared deviation from the mean was considered optimal. The normalized amplitude Hilbert spectrum was used to calculate the error index associated with the instantaneous frequency. The amplitude and the frequency values were corrected in the region where the error was higher than twice the standard deviation. The Intrinsic Mode Function (IMF) components were assigned to the Low Frequency (LF) and the High Frequency (HF) part of the signal by making use of the center frequency and the standard deviation spectral extension estimated from the marginal spectrum of the IMF components. The analysis procedure was validated with the help of a simulated signal which consisted of two components in the LF and the HF region of the HRV signal with varying amplitude and frequency. The optimal range of the stopping criterion was found to be between 4 and 9 for the HRV data. The statistical analysis showed that the LF/HF amplitude ratio decreased within an hour of the application of the brachial plexus block compared to the values at the start of the procedure. These changes were observed in thirteen of the fourteen patients included in this study.
心率变异性（HRV）的频谱分析用于评估心血管自主神经控制。在本研究中，数据驱动的自适应技术经验模态分解（EMD）及相关的希尔伯特频谱被用于评估局部麻醉对一组14例采用经动脉技术进行臂丛神经阻滞（局部麻醉）患者HRV参数的影响。确定了停止准则的置信限，与均值的平方偏差最小的S值被认为是最优的。归一化幅度希尔伯特频谱用于计算与瞬时频率相关的误差指数。在误差高于两倍标准差的区域对幅度和频率值进行校正。通过利用从IMF分量的边际频谱估计的中心频率和标准差频谱扩展，将本征模态函数（IMF）分量分配到信号的低频（LF）和高频（HF）部分。借助由HRV信号的LF和HF区域中两个幅度和频率不同的分量组成的模拟信号对分析过程进行了验证。发现HRV数据的停止准则的最佳范围在4到9之间。统计分析表明，与手术开始时的值相比，臂丛神经阻滞后一小时内LF/HF幅度比降低。在本研究纳入的14例患者中有13例观察到了这些变化。
