Toward automation in hearing aid design

In the manufacturing of customized medical prostheses, such as in-the-ear hearing aids, the design process often is dictated by a source template representing the anatomy of a patient and a set of work instructions representing the description of surface modifications. Instead of carrying out the work instructions by hand with knife, file or drilling tools, the state-of-the-art relies on modern software tools, such as computer-aided-design and computer-aided-manufacturing. Work instructions are usually defined in terms of anatomical landmarks of a given template. Following the design phase, the virtual model of the customized prosthesis is produced by a rapid prototyping system, like selective laser sintering or stereolithography. An outstanding problem in prostheses design is that the work instructions are often vaguely defined, and a suitable outcome largely depends on the knowledge, experience and skill of the designer. In this paper, we present a solution to minimize the influence of human interaction. Our approach involves the abstraction of the work instructions into expert system rules that exploit a robustly identified canonical set of anatomic features. The versatility of our approach lies in a priori defining an entire design workflow through a rule set, thereby yielding a high degree of automation that is flexible, customizable, consistent, and reproducible. The proposed solution is extensively evaluated in a real world application, and is shown to yield significant improvement in manufacturing. For instance, the consistency of the outcome was improved by about 10% and the design time was reduced by about 8.4%.

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► Novel approach for automatic customized prostheses design.
► Automation of computer-aided-design environment for rapid manufacturing.
► Smart combination of surface-based anatomical feature detection and expert system technology.
► Successful evaluation in real world scenario.
► Improvement in design consistency/repeatability and reduction of design time.