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Published April 14, 2020 | Version 1.0
Dataset Open

Data and materials from: "Auditory Profile-based Hearing-aid Fitting: A Proof-Of-Concept Study"

  • 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. (2020). Auditory Profile-based Hearing-aid Fitting: A Proof-of-concept study. [under review].
[Preprint available in medRxiv: https://doi.org/10.1101/2020.04.14.20036459]

 

Abstract

Objective: 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 were tested using a comprehensive test battery designed to tap into different aspects of hearing. A data-driven analysis of the data yielded four clinically relevant patient subpopulations or “auditory profiles”. In the current study, profile-based hearing-aid settings were proposed and evaluated to explore their potential with respect to providing more targeted hearing-aid treatment.

Design: Four candidate hearing-aid settings were implemented 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 different auditory profiles differed in terms of preference and favoured the targeted hearing-aid setting. 

Conclusion: The results of this proof-of-concept study support further investigations into a 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.
  • 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

Files (1.2 GB)

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md5:ef7cff5fbfcd994054657ff1199e96b6
825.9 MB Preview Download
md5:99684a8557f04bfc0c173f95bcd577b5
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md5:465669a075f7d5b562eff96a6701ea25
355.3 MB Download
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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