Department of Anesthesiology, Changhua Christian Hospital, Changhua 50051, Taiwan.
Ph.D. Program of Electrical and Communications Engineering, Feng Chia University, Taichung 40724, Taiwan.
Sensors (Basel). 2022 Jun 18;22(12):4618. doi: 10.3390/s22124618.
The evaluation of baroreflex sensitivity (BRS) has proven to be critical for medical applications. The use of indices by spectral methods has been the most popular approach to BRS estimation. Recently, an algorithm termed Gaussian average filtering decomposition (GAFD) has been proposed to serve the same purpose. GAFD adopts a three-layer tree structure similar to wavelet decomposition but is only constructed by Gaussian windows in different cutoff frequency. Its computation is more efficient than that of conventional spectral methods, and there is no need to specify any parameter. This research presents a novel approach, referred to as modulated Gaussian filter (modGauss) for BRS estimation. It has a more simplified structure than GAFD using only two bandpass filters of dedicated passbands, so that the three-level structure in GAFD is avoided. This strategy makes modGauss more efficient than GAFD in computation, while the advantages of GAFD are preserved. Both GAFD and modGauss are conducted extensively in the time domain, yet can achieve similar results to conventional spectral methods. In computational simulations, the EuroBavar dataset was used to assess the performance of the novel algorithm. The BRS values were calculated by four other methods (three spectral approaches and GAFD) for performance comparison. From a comparison using the Wilcoxon rank sum test, it was found that there was no statistically significant dissimilarity; instead, very good agreement using the intraclass correlation coefficient (ICC) was observed. The modGauss algorithm was also found to be the fastest in computation time and suitable for the long-term estimation of BRS. The novel algorithm, as described in this report, can be applied in medical equipment for real-time estimation of BRS in clinical settings.
血压反射敏感性（BRS）的评估已被证明对医学应用至关重要。谱方法的指标已成为 BRS 估计最流行的方法。最近，提出了一种称为高斯平均滤波分解（GAFD）的算法来达到相同的目的。GAFD 采用类似于小波分解的三层树结构，但仅由不同截止频率的高斯窗口构建。其计算效率高于传统的谱方法，并且无需指定任何参数。本研究提出了一种新的方法，称为调制高斯滤波器（modGauss）用于 BRS 估计。它的结构比 GAFD 更简单，仅使用两个专用通带的带通滤波器，因此避免了 GAFD 的三级结构。这种策略使 modGauss 在计算上比 GAFD 更有效，同时保留了 GAFD 的优势。GAFD 和 modGauss 都在时域中广泛进行，但可以获得与传统谱方法相似的结果。在计算模拟中，使用 EuroBavar 数据集评估新算法的性能。通过另外四种方法（三种谱方法和 GAFD）计算 BRS 值进行性能比较。通过 Wilcoxon 秩和检验进行比较，发现没有统计学上的显着差异；相反，使用组内相关系数（ICC）观察到非常好的一致性。还发现 modGauss 算法在计算时间方面最快，适用于 BRS 的长期估计。本报告中描述的新算法可应用于医疗设备，用于在临床环境中实时估计 BRS。
