Using Objective Metrics to Measure Hearing Aid Performance

Objectives: The performance of hearing aids is generally characterized by a small set of standardized measurements. The primary goals of these procedures are to measure basic aspects of the hearing aid performance and to ascertain that the device is operating properly. A more general need exists for objective metrics that can predict hearing aid outcomes. Such metrics must consider the interaction of all the signal processing operating in the hearing aid and must do so while also accounting for the hearing loss for which the hearing aid has been prescribed. This article represents a first step in determining the clinical applicability of the hearing aid speech perception index (HASPI) intelligibility and hearing aid speech quality index (HASQI) speech quality metrics. The goals of this article are to demonstrate the feasibility of applying these metrics to commercial hearing aids and to illustrate the anticipated range of measured values and identify implementation concerns that may not be present for conventional measurements. Design: This article uses the HASPI intelligibility and HASQI speech quality metrics to measure the performance of commercial hearing aids. These metrics measure several aspects of the processed signal, including envelope fidelity, modifications of the temporal fine structure, and changes in the long-term frequency response, all in the context of an auditory model that reproduces the salient aspects of the peripheral hearing loss. The metrics are used to measure the performance of basic and premium hearing aids from three different manufacturers. Test conditions include the environmental factors of signal to noise ratio and presentation level, and the fitting configurations were varied to provide different degrees of processing from linear to aggressive nonlinear processing for two different audiograms. Results: The results show that the metrics are capable of measuring statistically significant differences across devices and processing settings. HASPI and HASQI measure both audibility and nonlinear distortion in the devices, and conditions are identified where predicted intelligibility is high but predicted speech quality is substantially reduced. The external signal properties of signal to noise ratio and presentation level are both statistically significant. Hearing loss is significant for HASPI but not for HASQI, and degree of processing is significant for both metrics. A quadratic model for manufacturer showed large effect sizes for HASPI and HASQI, but basic versus premium hearing aid model is not significant. Conclusions: The results presented in this article represent a first step in applying the HASPI and HASQI metrics to commercial hearing aids. Modern hearing aids often use several different processing strategies operating simultaneously. The proposed metrics provide a way to predict the total effect of this processing, including algorithm interactions that may be missed by conventional measurement procedures. The measurements in this article show significant differences between manufacturers, processing settings, and adjustment for different hearing losses. No significant differences were found between basic and premium hearing aid models. Further research will be needed to determine the clinical relevance of these measurements and to provide target values appropriate for successful fittings. Acknowledgments: Portions of this work were supported by a grant to the University of Colorado from GN ReSound and by a grant from the National Institutes of Health (1 R01 DC012289). The authors have no conflicts of interest to disclose. Address for correspondence: James M. Kates, University of Colorado, 409 UCB, Boulder, Colorado 80309, USA. E-mail: James.Kates@colorado.edu Received March 30, 2017; accepted January 31, 2018. Copyright © 2018 Wolters Kluwer Health, Inc. All rights reserved.

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