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A preliminary application of principal components and cluster analysis to internal tongue deformation patterns

机译:主成分和聚类分析在舌内变形模式中的初步应用

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Complex patterns of muscle contractions create gross tongue motion during speech. It is of scientific and medical importance to better understand speech motor strategies and variations due to language or disorders. Dense patterns of tongue motion can be imaged using tagged magnetic resonance imaging, but characterisation of motion strategies is difficult using visualisation alone. This paper explores the use of principal component analysis for dimensionality reduction and cluster analysis for tongue motion categorisation. Velocity fields were acquired and analysed from midsagittal tongue slices during motion from lil to /u/ for eight datasets containing multiple languages and a glossectomy patient. The analyses were carried out on the tongue-only and tongue-plus-floor of the mouth regions. The results showed that both the analyses were sensitive to region size and that cluster analysis was harder to interpret. Both the analyses grouped the Japanese speaker with the glossectomy patient, which although explicable with biologically plausible reasons, highlights the limitations of extensive data reduction.
机译:复杂的肌肉收缩模式会在说话时产生粗大的舌头运动。更好地理解由于语言或障碍导致的言语运动策略和变异性具有科学和医学意义。可以使用标记的磁共振成像对舌头运动的密集模式进行成像,但是仅通过可视化就很难表征运动策略。本文探讨了将主成分分析用于降维和将聚类分析用于舌头运动分类的方法。在从lil到/ u /的运动过程中,从矢状舌中段获取并分析了速度场,得到了包含多种语言的8个数据集和一名切除术的患者。分析是在仅舌头和舌头在地板上方的区域进行的。结果表明,这两种分析均对区域大小敏感,并且聚类分析更难以解释。两种分析都将日语使用者与舌切除术患者分组,尽管可以用生物学上合理的理由进行解释,但它们突出了大量数据缩减的局限性。

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