Rankine Jacquelin, Li Erin, Lurie Stacey, Rieger Hillary, Fourie Emily, Siper Paige M, Wang A Ting, Buxbaum Joseph D, Kolevzon Alexander
Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, Box 1668, One Gustave L. Levy Place, New York, NY, 10029, USA.
Ferkauf Graduate School of Psychology, Yeshiva University, Bronx, NY, USA.
J Autism Dev Disord. 2017 Jun;47(6):1605-1617. doi: 10.1007/s10803-017-3082-8.
Phelan-McDermid syndrome (PMS) is a single-locus cause of developmental delay, autism spectrum disorder, and minimal verbal abilities. There is an urgent need to identify objective outcome measures of expressive language for use in this and other minimally verbal populations. One potential tool is an automated language processor called Language ENvironment Analysis (LENA). LENA was used to obtain over 542 h of audio in 18 children with PMS. LENA performance was adequate in a subset of children with PMS, specifically younger children and those with fewer stereotypic vocalizations. One LENA-derived language measure, Vocalization Ratio, had improved accuracy in this sample and may represent a novel expressive language measure for use in severely affected populations.
费伦-麦克德米德综合征(PMS)是导致发育迟缓、自闭症谱系障碍和语言能力极低的单基因病因。迫切需要确定用于该群体及其他语言能力极低人群的表达性语言客观评估指标。一种潜在工具是名为语言环境分析(LENA)的自动语言处理器。LENA用于获取18名PMS患儿超过542小时的音频。在部分PMS患儿中,LENA表现良好,特别是年龄较小且刻板发声较少的患儿。LENA得出的一项语言指标——发声率,在该样本中的准确性有所提高,可能代表一种用于严重受影响人群的新型表达性语言评估指标。