Computational Audiology
Published April 14, 2020 | Version 1.1
Dataset Open

Data and materials from: "Towards Auditory Profile-based Hearing-aid Fitting: Fitting Rationale and Pilot Evaluation"

Creators

  • 1. Technical University of Denmark
  • 2. University of Southern Denmark

Description

This repository contains materials and data used and described in:

Sanchez-Lopez, R., Fereczkowski, M., Santurette, S., Dau, T., Neher, T. (2021). Towards Auditory Profile-based Hearing-aid Fitting: Fitting Rationale and Pilot Evaluation. Audiol. Res. 11, no. 1: 10-21. https://doi.org/10.3390/audiolres11010002 

 

Abstract

Background - The clinical characterization of hearing deficits for hearing-aid fitting purposes is typically based on the pure-tone audiogram only. In a previous study, a group of hearing-impaired listeners completed a comprehensive test battery designed to tap into different dimensions of hearing abilities. A data-driven analysis of the data yielded four clinically relevant patient subpopulations or “auditory profiles”. The purpose of the current study was to propose and pilot-test profile-based hearing-aid settings to explore their potential for providing more targeted hearing-aid treatment.
Methods -  Four candidate hearing-aid settings were developed and evaluated by a subset of the participants tested previously. The evaluation consisted of multi-comparison preference ratings carried out in realistic sound scenarios.
Results -  Listeners belonging to the different auditory profiles showed different patterns of preference for the tested hearing-aid settings that were largely consistent with the expectations.
Conclusion -  The results of this pilot evaluation support further investigations into stratified, profile-based hearing-aid fitting with wearable hearing aids.

Please cite this article when using the data

 

Description of the files:

  • APBHAF_Audiofiles.zip: Audio files used in the SenseLabOnline environment. Each folder corresponds to one participant.
  • APBHAF_MUSHA.xlsx: Raw Data of the MUSHA experiment.
  • APBHAF_MUSHA_Analysis.R: R code for the data analysis.
  • MUS_SoundScenes.mat: Mat file with a structure 1x9 MUS with the raw acoustic signals before processing with the hearing-aid simulator.
    • CurrentMixture: matrix consisting of the simulated acoustic signal recorded by the 4 microphones of the hearing-aid satellites: 1) front-left, 2) back-left, 3) front-right, 4) back-right.
    • CurrentAnchor: matrix consisting of the simulated acoustic signal recorded by the 4 microphones of the hearing-aid satellites: 1) front-left, 2) back-left, 3) front-right, 4) back-right. The Anchor is -6 dB SNR.
    • SampleLabel: Either "Kantine", "Traffic" or "Quiet"
    • ConditionLabel: Either "Cond1", "Cond2" or "Cond3"
    • fsmix: sampling frequency. For all signals must be 32000Hz
  • MUSHA_Instruction: Instructions used for explaining the task and the environment.

* The participant IDs in each of the files has been assigned randomly to ensure the anonymization of the data. The pseudo-anonymized data might be shared under request by direct correspondence with the authors.

Files

APBHAF_Audiofiles.zip

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Additional details

References

  • SenseLab dept. (2017). SenseLabOnline (version 4.0.2). Listening test software. Hørsholm, Denmark: FORCE Technology.
  • Baker, R., & Hazan, V. (2011). DiapixUK: task materials for the elicitation of multiple spontaneous speech dialogs. Behavior Research Methods, 43(3), 761–770. https://doi.org/10.3758/s13428-011-0075-y
  • Sørensen, A. J., Fereczkowski, M., & MacDonald, E. N. (2018, March 21). Task dialog by native-Danish talkers in Danish and English in both quiet and noise. Zenodo. https://doi.org/10.5281/zenodo.1204951
  • Sanchez-Lopez, R., Fereczkowski, M., Bianchi, F., Piechowiak, T., Hau, O., Pedersen, M. S., … Santurette, S. (2018). Technical evaluation of hearing-aid fitting parameters for different auditory profiles. Euronoise 2018, 381–388. Retrieved from http://www.euronoise2018.eu/docs/papers/66_Euronoise2018.pdf
  • Sanchez-Lopez, R., Fereczkowski, M., Neher, T., Santurette, S., & Dau, T. (2020). Robust data-driven auditory profiling for precision audiology. MedRxiv. https://doi.org/10.1101/2020.04.05.20036442