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

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  • Maureen Stone
  • Xiaofeng Liu
  • Hegang Chen
  • Jerry L. Prince

Abstract

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 /i/ 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.

Suggested Citation

  • Maureen Stone & Xiaofeng Liu & Hegang Chen & Jerry L. Prince, 2010. "A preliminary application of principal components and cluster analysis to internal tongue deformation patterns," Computer Methods in Biomechanics and Biomedical Engineering, Taylor & Francis Journals, vol. 13(4), pages 493-503.
    • Handle: RePEc:taf:gcmbxx:v:13:y:2010:i:4:p:493-503
    DOI: 10.1080/10255842.2010.484809
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    1. P. Loslever & J. Schiro & F. Gabrielli & P. Pudlo, 2017. "Comparing multiple correspondence and principal component analyses with biomechanical signals. Example with turning the steering wheel," Computer Methods in Biomechanics and Biomedical Engineering, Taylor & Francis Journals, vol. 20(10), pages 1038-1047, July.

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