A training algorithm for optimal margin classifiers
COLT '92 Proceedings of the fifth annual workshop on Computational learning theory
Building and Testing a Statistical Shape Model of the Human Ear Canal
MICCAI '02 Proceedings of the 5th International Conference on Medical Image Computing and Computer-Assisted Intervention-Part II
Analysis of deformation of the human ear and canal caused by mandibular movement
MICCAI'07 Proceedings of the 10th international conference on Medical image computing and computer-assisted intervention
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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.