Abstract: A method is provided for automatically determining the position of and placing a faceplate assembly on a hearing instrument shell that takes into account patient anatomical features. These anatomical features of the shell are used as landmarks for ensuring that the final position of the faceplate on the hearing instrument is optimized both in terms of esthetics and increased comfort. The protocols defined herein take advantage of the intrinsic features of the human ear anatomy and the geometry of the electronic components to ensure that design and manufacturing of ITEs are optimized for efficiency and the process can be completely automated to ensure consistence and practice reproducibility.

Abstract: A method and appertaining system determine and output parameters associated with an ear canal according to a particular taxonomy. The output can then be input to various other systems associated with hearing aid design. An intelligent computational approach is utilized that models the physiology of the human ear canal as reconcilable with a conic or quadric section. The canal segment of the impression is sliced, and various parameters are determined according to each slice. Then, these parameters are analyzed in order to create a basic classification of the canal morphology.

Abstract: A method is provided for automatically determining the position of and placing a faceplate assembly on a hearing instrument shell that takes into account patient anatomical features. These anatomical features of the shell are used as landmarks for ensuring that the final position of the faceplate on the hearing instrument is optimized both in terms of esthetics and increased comfort. The protocols defined herein take advantage of the intrinsic features of the human ear anatomy and the geometry of the electronic components to ensure that design and manufacturing of ITEs are optimized for efficiency and the process can be completely automated to ensure consistence and practice reproducibility.

Abstract: A method and appertaining system determine and output parameters associated with an ear canal according to a particular taxonomy. The output can then be input to various other systems associated with hearing aid design. An intelligent computational approach is utilized that models the physiology of the human ear canal as reconcilable with a conic or quadric section. The canal segment of the impression is sliced, and various parameters are determined according to each slice. Then, these parameters are analyzed in order to create a basic classification of the canal morphology.