Hypokinetic dysarthria (HD) and freezing of gait (FOG) are both axial symptoms that occur in patients with Parkinson’s disease (PD). It is assumed they have some common pathophysiological mechanisms and therefore that speech disorders in PD can predict FOG deficits within the horizon of some years. The aim of this study is to employ a complex quantitative analysis of the phonation, articulation and prosody in PD patients in order to identify the relationship between HD and FOG, and establish a mathematical model that would predict FOG deficits using acoustic analysis at baseline. We enrolled 75 PD patients who were assessed by 6 clinical scales including the Freezing of Gait Questionnaire (FOG–Q). We subsequently extracted 19 acoustic measures quantifying speech disorders in the fields of phonation, articulation and prosody. To identify the relationship between HD and FOG, we performed a partial correlation analysis. Finally, based on the selected acoustic measures, we trained regression models to predict the change in FOG during a 2-year follow-up. We identified significant correlations between FOG–Q scores and the acoustic measures based on formant frequencies (quantifying the movement of the tongue and jaw) and speech rate. Using the regression models, we were able to predict a change in particular FOG–Q scores with an error of between 7.4 and 17.0 %. This study is suggesting that FOG in patients with PD is mainly linked to improper articulation, a disturbed speech rate and to intelligibility. We have also proved that the acoustic analysis of HD at the baseline can be used as a predictor of the FOG deficit during 2 years of follow-up. This knowledge enables researchers to introduce new cognitive systems that predict gait difficulties in PD patients.

中文翻译：

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运动减退性构音障碍与帕金森病冻结步态关系的定量分析。

运动减退性构音障碍 (HD) 和冻结步态 (FOG) 都是帕金森病 (PD) 患者出现的中轴症状。据推测，它们具有一些共同的病理生理学机制，因此 PD 中的言语障碍可以预测几年内的 FOG 缺陷。本研究的目的是对 PD 患者的发声、发音和韵律进行复杂的定量分析，以确定 HD 和 FOG 之间的关系，并建立一个数学模型，使用基线声学分析来预测 FOG 缺陷。我们招募了 75 名 PD 患者，并通过包括冻结步态问卷 (FOG-Q) 在内的 6 种临床量表进行评估。随后，我们提取了 19 种声学测量值，用于量化发声、发音和韵律领域的言语障碍。为了确定 HD 和 FOG 之间的关系，我们进行了偏相关分析。最后，根据选定的声学测量，我们训练回归模型来预测 2 年随访期间 FOG 的变化。我们确定了 FOG-Q 分数与基于共振峰频率（量化舌头和下巴的运动）和语速的声学测量之间的显着相关性。使用回归模型，我们能够预测特定 FOG–Q 分数的变化，误差在 7.4% 到 17.0% 之间。这项研究表明 PD 患者的 FOG 主要与发音不当、语速紊乱和清晰度有关。我们还证明，基线处 HD 的声学分析可以用作 2 年随访期间 FOG 缺陷的预测指标。这些知识使研究人员能够引入新的认知系统来预测帕金森病患者的步态困难。