Amyotrophic lateral sclerosis is a fatal disease that not only affects movement, speech, and breath but also cognition. Recent studies have focused on the use of language analysis techniques to detect ALS and infer scales for monitoring functional progression. In this paper, we focused on another important aspect, cognitive impairment, which affects 35-50% of the ALS population. In an effort to reach the ALS population, which frequently exhibits mobility limitations, we implemented the digital version of the Edinburgh Cognitive and Behavioral ALS Screen (ECAS) test for the first time. This test which is designed to measure cognitive impairment was remotely performed by 56 participants from the EverythingALS Speech Study. As part of the study, participants (ALS and non-ALS) were asked to describe weekly one picture from a pool of many pictures with complex scenes displayed on their computer at home. We analyze the descriptions performed within +/- 60 days from the day the ECAS test was administered and extract different types of linguistic and acoustic features. We input those features into linear regression models to infer 5 ECAS sub-scores and the total score. Speech samples from the picture description are reliable enough to predict the ECAS subs-scores, achieving statistically significant Spearman correlation values between 0.32 and 0.51 for the model's performance using 10-fold cross-validation.

翻译：肌萎缩侧索硬化症是一种致命性疾病，不仅影响运动、言语和呼吸功能，还会损害认知能力。近年研究聚焦于利用语言分析技术检测ALS并推断功能进展评估量表。本文重点关注另一个重要方面——认知障碍，约35-50%的ALS患者存在该症状。为覆盖常伴有行动障碍的ALS人群，我们首次实现了爱丁堡认知与行为ALS筛查量表（ECAS）的数字版本。该量表专为评估认知障碍设计，由来自EverythingALS言语研究的56名参与者远程完成。研究要求参与者（包括ALS患者与非患者）每周描述家中电脑屏幕上显示的复杂场景图片池中的一幅图片。我们分析ECAS测试实施前后±60天内完成的描述文本，提取多种语言与声学特征，将其输入线性回归模型以推断5项ECAS分量表得分及总分。基于图片描述的语音样本足以可靠预测ECAS分量表得分，通过10折交叉验证，模型性能的斯皮尔曼相关系数达到0.32至0.51的统计显著性水平。