Using Objective Metrics to Measure Hearing Aid Performance

Abstract

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.

Understanding Variability in Individual Response to Hearing Aid Signal Processing in Wearable Hearing Aids

“…Indeed, the range of signal modification created (ranging from approximately 0.3 to 0.7, depending on the signal processing and the input SNR) was similar to that seen in clinically-fit hearing aids. For example, a signal modification range of approximately 0.2 to 0.8 has been reported for user settings of clinically-fit hearing aids for adults (Kates et al, 2018;Rallapalli, Anderson, Kates,, Sirow, Arehart, & Souza, 2018) and children (Anderson, Mowery, & Uhler, 2018), using a similar metric approach.…”

“…A smoothed version of the log magnitude spectrum produced by the auditory model was then computed at each time sample. The cross-correlation of the smoothed spectra from the reference and processed signals was computed to produce the cepstral correlation (Kates et al, 2018), which measures the degree to which the time-frequency envelope modulation of the processed signal matches that of the reference. The cepstral correlation values are related to the time-frequency modulation patterns of speech that are used in speech recognition (Zahorian & Rothenberg, 1981).…”

Classification of Hearing Aids Into Feature Profiles Using Hierarchical Latent Class Analysis Applied to a Large Dataset of Hearing Aids

“…To our knowledge, a comparable mixture of several objectively defined hearing aid features, across a wide selection of brands and types of hearing aids, has to date not been examined. Attempts have been made to assess differences between hearing aids ( Cox et al 2014 , 2016 ; Kates et al 2018 ; Wu et al 2018 ), but these are rather limited and do not focus on the interplay between different features.…”

Influence of Audibility and Distortion on Recognition of Reverberant Speech for Children and Adults with Hearing Aid Amplification

“…Unlike the SII, HASPI does not account for the reduction in speech recognition associated with excessively high presentation levels (i.e., level distortion factor). Consequently, regardless of the output level or degree of hearing loss, the HASPI predicts 100% recognition of speech once a sufficient SNR is achieved (Kates et al 2018).…”