Abstract:
A wide variety of signal processing circuitry is available from hearing aid manufacturers for use in custom hearing aids. Whether the type of circuit used is specified by the clinician or by the manufacturer, the selection process is often speculative because of the lack of understanding about how different types of signal processing interact with pathological auditory systems. An empirical approach to signal processing selection is proposed based on the circuit that is most likely to minimize field returns for a particular audiometric configuration, degree of loss, and hearing aid model. Several thousand ITE and ITC hearing aid fittings made by one hearing aid manufacturer were monitored via a computerized field tracking data base for incidence of repairs and returns for credit. Circuits included four types of signal processing having class D output stage: linear, input compression, TILL, and BILL. Audiograms were divided into seven configurations: flat, gradually sloping, steeply sloping, precipitous, rising, cookie bite, and inverted cookie bite. The database was entered into the IDIS artificial intelligence program, and design rules were formulated to maximize fitting success. From these rules, signal processing type(s) were identified for each audiometric configuration that would minimize field returns.