Bandini Andrea, Green Jordan R, Wang Jun, Campbell Thomas F, Zinman Lorne, Yunusova Yana
University Health Network, Toronto Rehabilitation Institute, Ontario, Canada.
Department of Communication Sciences and Disorders, MGH Institute of Health Professions, Boston, MA.
J Speech Lang Hear Res. 2018 May 17;61(5):1118-1129. doi: 10.1044/2018_JSLHR-S-17-0262.
The goals of this study were to (a) classify speech movements of patients with amyotrophic lateral sclerosis (ALS) in presymptomatic and symptomatic phases of bulbar function decline relying solely on kinematic features of lips and jaw and (b) identify the most important measures that detect the transition between early and late bulbar changes.
One hundred ninety-two recordings obtained from 64 patients with ALS were considered for the analysis. Feature selection and classification algorithms were used to analyze lip and jaw movements recorded with Optotrak Certus (Northern Digital Inc.) during a sentence task. A feature set, which included 35 measures of movement range, velocity, acceleration, jerk, and area measures of lips and jaw, was used to classify sessions according to the speaking rate into presymptomatic (> 160 words per minute) and symptomatic (< 160 words per minute) groups.
Presymptomatic and symptomatic phases of bulbar decline were distinguished with high accuracy (87%), relying only on lip and jaw movements. The best features that allowed detecting the differences between early and later bulbar stages included cumulative path of lower lip and jaw, peak values of velocity, acceleration, and jerk of lower lip and jaw.
The results established a relationship between facial kinematics and bulbar function decline in ALS. Considering that facial movements can be recorded by means of novel inexpensive and easy-to-use, video-based methods, this work supports the development of an automatic system for facial movement analysis to help clinicians in tracking the disease progression in ALS.
本研究的目标是：(a) 仅依靠嘴唇和下颌的运动学特征，对肌萎缩侧索硬化症（ALS）患者在球部功能衰退的症状前期和症状期的言语运动进行分类；(b) 确定检测球部早期和晚期变化之间转变的最重要指标。
分析从64例ALS患者获得的192份记录。使用特征选择和分类算法来分析在句子任务期间用Optotrak Certus（北方数字公司）记录的嘴唇和下颌运动。一个特征集，包括35项运动范围、速度、加速度、急动度的测量指标以及嘴唇和下颌的面积测量指标，用于根据说话速度将各时段分为症状前期（每分钟>160个单词）和症状期（每分钟<160个单词）组。
仅依靠嘴唇和下颌运动，球部衰退的症状前期和症状期能够以较高的准确率（87%）区分开来。能够检测球部早期和晚期阶段差异的最佳特征包括下唇和下颌的累积路径、下唇和下颌速度、加速度和急动度的峰值。
研究结果确立了ALS患者面部运动学与球部功能衰退之间的关系。鉴于面部运动可以通过新型廉价且易于使用的基于视频的方法进行记录，本研究支持开发一种面部运动分析自动系统，以帮助临床医生跟踪ALS的疾病进展。
