Analysis of surfaces using constrained regression models

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Abstract

We present a study of the relationship between the changes in the shape of the human ear due to jaw movement and acoustical feedback (AF) in hearing aids. In particular, we analyze the deformation field of the outer ear associated with the movement of the mandible (jaw bone) to understand its effect on AF and identify local regions that play a significant role. Our data contains ear impressions of 42 hearing aid users, in two different positions: open and closed mouth, and survey data including information about experienced discomfort due to AF. We use weighted support vector machines (WSVM) to investigate the separation between the presence and lack of AF and achieve classification accuracy of 80% based on the deformation field. To robustly localize the regions of the deformation field that significantly contribute to AF we employ logistic regression penalized with elastic net (EN). By visualizing the selected variables on the mean surface, we provide clinical interpretations of the results. © 2008 Springer-Verlag Berlin Heidelberg.

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APA

Darkner, S., Sabuncu, M. R., Golland, P., Paulsen, R. R., & Larsen, R. (2008). Analysis of surfaces using constrained regression models. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5241 LNCS, pp. 842–849). https://doi.org/10.1007/978-3-540-85988-8_100

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