Cortés Juan P, Alzamendi Gabriel A, Weinstein Alejandro J, Yuz Juan I, Espinoza Víctor M, Mehta Daryush D, Hillman Robert E, Zañartu Matías
Department of Electronic Engineering, Universidad Técnica Federico Santa María, Valparaiso 2390123, Chile.
Institute for Research and Development on Bioengineering and Bioinformatics, Consejo Nacional de Investigaciones Científicas y Técnicas-Universidad Nacional de Entre Ríos, Oro Verde 3100, Argentina.
Appl Sci (Basel). 2022 Jan;12(1). doi: 10.3390/app12010401. Epub 2021 Dec 31.
Subglottal Impedance-Based Inverse Filtering (IBIF) allows for the continuous, non-invasive estimation of glottal airflow from a surface accelerometer placed over the anterior neck skin below the larynx. It has been shown to be advantageous for the ambulatory monitoring of vocal function, specifically in the use of high-order statistics to understand long-term vocal behavior. However, during long-term ambulatory recordings over several days, conditions may drift from the laboratory environment where the IBIF parameters were initially estimated due to sensor positioning, skin attachment, or temperature, among other factors. Observation uncertainties and model mismatch may result in significant deviations in the glottal airflow estimates; unfortunately, they are very difficult to quantify in ambulatory conditions due to a lack of a reference signal. To address this issue, we propose a Kalman filter implementation of the IBIF filter, which allows for both estimating the model uncertainty and adapting the airflow estimates to correct for signal deviations. One-way analysis of variance (ANOVA) results from laboratory experiments using the Rainbow Passage indicate an improvement using the modified Kalman filter on amplitude-based measures for phonotraumatic vocal hyperfunction (PVH) subjects compared to the standard IBIF; the latter showing a statistically difference (-value = 0.02, = 4.1) with respect to a reference glottal volume velocity signal estimated from a single notch filter used here as ground-truth in this work. In contrast, maximum flow declination rates from subjects with vocal phonotrauma exhibit a small but statistically difference between the ground-truth signal and the modified Kalman filter when using one-way ANOVA (-value = 0.04, = 3.3). Other measures did not have significant differences with either the modified Kalman filter or IBIF compared to ground-truth, with the exception of H1-H2, whose performance deteriorates for both methods. Overall, both methods (modified Kalman filter and IBIF) show similar glottal airflow measures, with the advantage of the modified Kalman filter to improve amplitude estimation. Moreover, Kalman filter deviations from the IBIF output airflow might suggest a better representation of some fine details in the ground-truth glottal airflow signal. Other applications may take more advantage from the adaptation offered by the modified Kalman filter implementation.
基于声门下阻抗的逆滤波（IBIF）能够通过放置在喉部下前方颈部皮肤表面的加速度计，对声门气流进行连续、非侵入性的估计。研究表明，这对于动态监测嗓音功能具有优势，特别是在利用高阶统计量来理解长期嗓音行为方面。然而，在持续数天的长期动态记录过程中，由于传感器位置、皮肤贴合度或温度等因素，记录条件可能会偏离最初估计IBIF参数时的实验室环境。观测不确定性和模型失配可能导致声门气流估计出现显著偏差；不幸的是，由于缺乏参考信号，在动态条件下很难对这些偏差进行量化。为了解决这个问题，我们提出了一种IBIF滤波器的卡尔曼滤波器实现方法，它既能估计模型不确定性，又能调整气流估计值以校正信号偏差。使用彩虹段落进行的实验室实验的单向方差分析（ANOVA）结果表明，与标准IBIF相比，对于发声创伤性嗓音功能亢进（PVH）受试者，使用改进的卡尔曼滤波器在基于幅度的测量方面有改进；与这里用作本研究真值的单个陷波滤波器估计的参考声门体积速度信号相比，后者显示出统计学差异（p值 = 0.02，F = 4.1）。相比之下，当使用单向方差分析时，发声创伤受试者的最大流量下降率在真值信号和改进的卡尔曼滤波器之间显示出微小但具有统计学意义的差异（p值 = 0.04，F = 3.3）。与真值相比，其他测量指标在改进的卡尔曼滤波器或IBIF与真值之间均无显著差异，但H1 - H2除外，两种方法的H1 - H2性能均有所下降。总体而言，两种方法（改进的卡尔曼滤波器和IBIF）显示出相似的声门气流测量结果，改进的卡尔曼滤波器的优势在于能改善幅度估计。此外，卡尔曼滤波器与IBIF输出气流的偏差可能表明在真值声门气流信号中能更好地呈现一些细节。其他应用可能会从改进的卡尔曼滤波器实现所提供的适应性中获得更多优势。
