Stegmann Gabriela M, Hahn Shira, Liss Julie, Shefner Jeremy, Rutkove Seward, Shelton Kerisa, Duncan Cayla Jessica, Berisha Visar
Arizona State University, Phoenix, AZ USA.
Aural Analytics, Scottsdale, AZ USA.
NPJ Digit Med. 2020 Oct 13;3:132. doi: 10.1038/s41746-020-00335-x. eCollection 2020.
Bulbar deterioration in amyotrophic lateral sclerosis (ALS) is a devastating characteristic that impairs patients' ability to communicate, and is linked to shorter survival. The existing clinical instruments for assessing bulbar function lack sensitivity to early changes. In this paper, using a cohort of = 65 ALS patients who provided regular speech samples for 3-9 months, we demonstrated that it is possible to remotely detect early speech changes and track speech progression in ALS via automated algorithmic assessment of speech collected digitally.
肌萎缩侧索硬化症（ALS）中的延髓功能衰退是一个极具破坏性的特征，它会损害患者的沟通能力，并与较短的生存期相关。现有的评估延髓功能的临床工具对早期变化缺乏敏感性。在本文中，我们对65名ALS患者进行了为期3至9个月的定期语音样本采集，结果表明，通过对数字采集的语音进行自动算法评估，可以远程检测ALS患者早期的语音变化并追踪语音进展情况。
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