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Bayesian estimation of vocal function measures using laryngeal high-speed videoendoscopy and glottal airflow estimates: An in vivo case study.
The Journal of the Acoustical Society of America ( IF 2.4 ) Pub Date : 2020-05-20 , DOI: 10.1121/10.0001276
Gabriel A Alzamendi 1 , Rodrigo Manríquez 1 , Paul J Hadwin 2 , Jonathan J Deng 2 , Sean D Peterson 2 , Byron D Erath 3 , Daryush D Mehta 4 , Robert E Hillman 4 , Matías Zañartu 1
Affiliation  

This study introduces the in vivo application of a Bayesian framework to estimate subglottal pressure, laryngeal muscle activation, and vocal fold contact pressure from calibrated transnasal high-speed videoendoscopy and oral airflow data. A subject-specific, lumped-element vocal fold model is estimated using an extended Kalman filter and two observation models involving glottal area and glottal airflow. Model-based inferences using data from a vocally healthy male individual are compared with empirical estimates of subglottal pressure and reference values for muscle activation and contact pressure in the literature, thus providing baseline error metrics for future clinical investigations.

中文翻译:

使用喉部高速视频内窥镜和声门气流估计的声音功能测量的贝叶斯估计:体内案例研究。

本研究介绍了贝叶斯框架的体内应用,通过校准的经鼻高速视频内窥镜和口腔气流数据估计声门下压力、喉肌激活和声带接触压力。使用扩展卡尔曼滤波器和两个涉及声门面积和声门气流的观察模型来估计特定于主题的集总元素声带模型。使用来自声音健康男性个体的数据的基于模型的推论与文献中声门下压力的经验估计和肌肉激活和接触压力的参考值进行比较,从而为未来的临床研究提供基线误差指标。
更新日期:2020-05-20
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