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The future of hearing aid technology

Can technology turn us into superheroes?

Die Zukunft der Hörgerätetechnologie

Kann die Technologie uns in Superhelden verwandeln?

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Abstract

Background

Hearing aid technology has proven to be successful in the rehabilitation of hearing loss, but its performance is still limited in difficult everyday conditions characterized by noise and reverberation.

Objective

Introduction to the current state of hearing aid technology and presentation of the current state of research and future developments.

Methods

The current literature was analyzed and several specific new developments are presented.

Results

Both objective and subjective data from empirical studies show the limitations of the current technology. Examples of current research show the potential of machine learning-based algorithms and multimodal signal processing for improving speech processing and perception, of using virtual reality for improving hearing device fitting and of mobile health technology for improving hearing health services.

Conclusion

Hearing device technology will remain a key factor in the rehabilitation of hearing impairments. New technology, such as machine learning and multimodal signal processing, virtual reality and mobile health technology, will improve speech enhancement, individual fitting and communication training, thus providing better support for all hearing-impaired patients, including older patients with disabilities or declining cognitive skills.

Zusammenfassung

Hintergrund

Die Hörgerätetechnologie hat sich bei der Rehabilitation von Hörverlusten als erfolgreich erwiesen, aber ihre Leistung ist unter schwierigen Alltagsbedingungen, die durch Lärm und Nachhall gekennzeichnet sind, immer noch begrenzt.

Zielsetzung

Einführung in den aktuellen Stand der Hörgerätetechnologie und Darstellung des aktuellen Forschungsstandes und der zukünftigen Entwicklung.

Methoden

Die aktuelle Literatur wird analysiert und mehrere spezifische Neuentwicklungen werden vorgestellt.

Ergebnisse

Sowohl objektive als auch subjektive Daten aus empirischen Studien zeigen die Grenzen der derzeitigen Technologie auf. Beispiele aus der aktuellen Forschung belegen das Potenzial von auf maschinellem Lernen basierenden Algorithmen und multimodaler Signalverarbeitung zur Verbesserung der Sprachverarbeitung und -wahrnehmung, der Nutzung von virtueller Realität zur Verbesserung der Hörgeräteanpassung und von mobiler Gesundheitstechnologie zur Verbesserung der Hörgesundheitsdienste.

Schlussfolgerung

Die Hörgerätetechnologie wird ein Schlüsselfaktor bei der Rehabilitation von Hörschäden bleiben. Neue Technologien wie maschinelles Lernen und multimodale Signalverarbeitung, virtuelle Realität und mobile Gesundheitstechnologien werden die Sprachverbesserung, die individuelle Anpassung und das Kommunikationstraining verbessern.

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References

  1. Fan K, Zhao Y (2022) Mobile health technology: a novel tool in chronic disease management. Intell Med 2(1):41–47

    Article  Google Scholar 

  2. Slaney M, Lyon RF, Garcia R, Kemler B, Gnegy C, Wilson K, Cerf VG et al (2020) Auditory measures for the next billion users. Ear Hear 41:131S–139S

    Article  PubMed  Google Scholar 

  3. Frisby C, Eikelboom R, Mahomed-Asmail F, Kuper H, Swanepoel DW (2022) m‑health applications for hearing loss: a scoping review. Telemed J E Health 28(8):1090–1099

    Article  PubMed  Google Scholar 

  4. Picou EM (2020) MarkeTrak 10 (MT10) survey results demonstrate high satisfaction with and benefits from hearing aids. Semin Hear 41(1):21–36

    Article  PubMed  PubMed Central  Google Scholar 

  5. Dillon H (2012) Hearing aids. Thieme, Stuttgart

    Google Scholar 

  6. Kayser H, Herzke T, Maanen P, Zimmermann M, Grimm G, Hohmann V (2022) Open community platform for hearing aid algorithm research: open Master Hearing Aid (openMHA). SoftwareX 17:100953

    Article  PubMed  Google Scholar 

  7. Pavlovic C, Kassayan R, Prakash SR, Kayser H, Hohmann V, Atamaniuk A (2019) A high-fidelity multi-channel portable platform for development of novel algorithms for assistive listening wearables. J Acoust Soc Am 146(4):2878–2878

    Article  Google Scholar 

  8. Wu YH, Stangl E, Chipara O, Hasan SS, DeVries S, Oleson J (2019) Efficacy and effectiveness of advanced hearing aid directional and noise reduction technologies for older adults with mild to moderate hearing loss. Ear Hear 40(4):805

    Article  PubMed  PubMed Central  Google Scholar 

  9. Hendrikse MM, Grimm G, Hohmann V (2020) Evaluation of the influence of head movement on hearing aid algorithm performance using acoustic simulations. Trends Hear 24:2331216520916682

    PubMed  PubMed Central  Google Scholar 

  10. McCormack A, Fortnum H (2013) Why do people fitted with hearing aids not wear them? Int J Audiol 52(5):360–368

    Article  PubMed  PubMed Central  Google Scholar 

  11. Fontan L, Le Coz M, Azzopardi C, Stone MA, Füllgrabe C (2020) Improving hearing-aid gains based on automatic speech recognition. J Acoust Soc Am 148(3):EL227–EL233

    Article  Google Scholar 

  12. Oetting D, Bach JH, Krueger M, Vormann M, Schulte M, Meis M (2019) Subjective loudness ratings of vehicle noise with the hearing aid fitting methods NAL-NL2 and trueLOUDNESS. Proc Int Symp Auditory Audiol Res 7:289–296

    Google Scholar 

  13. Gomez R, Ferguson M (2020) Improving self-efficacy for hearing aid self-management: the early delivery of a multimedia-based education programme in first-time hearing aid users. Int J Audiol 59(4):272–281

    Article  PubMed  Google Scholar 

  14. Gogate M, Dashtipour K, Adeel A, Hussain A (2020) CochleaNet: A robust language-independent audio-visual model for real-time speech enhancement. Inf Fusion 63:273–285

    Article  Google Scholar 

  15. Tammen M, Doclo S (2022) Deep Multi-Frame MVDR Filtering for Binaural Noise Reduction. arXiv. https://doi.org/10.48550/arXiv.2205.08983 (arXiv:2205.08983)

    Article  Google Scholar 

  16. Nustede EJ, Anemüller J (2021) Towards speech enhancement using a variational U‑Net architecture. In: 29th European Signal Processing Conference (EUSIPCO). IEEE, pp 481–485

    Chapter  Google Scholar 

  17. Grimm G, Kayser H, Hendrikse M, Hohmann V (2018) A gaze-based attention model for spatially-aware hearing aids. In: Speech Communication; 13th ITG-Symposium. VDE, pp 1–5

    Google Scholar 

  18. Dasenbrock S, Blum S, Debener S, Hohmann V, Kayser H (2021) A step towards neuro-steered hearing aids: Integrated portable setup for time-synchronized acoustic stimuli presentation and EEG recording. Curr Dir Biomed Eng 7(2):855–858

    Article  Google Scholar 

  19. Dasenbrock S, Blum S, Maanen P, Debener S, Hohmann V, Kayser H (2022) Synchronization of ear-EEG and audio streams in a portable research hearing device. Front Neurosci 16. https://doi.org/10.3389/fnins.2022.904003

  20. Hohmann V, Paluch R, Krueger M, Meis M, Grimm G (2020) The virtual reality lab: realization and application of virtual sound environments. Ear Hear 41(Suppl 1):31S

    Article  PubMed  PubMed Central  Google Scholar 

  21. Mehra R, Brimijoin O, Robinson P, Lunner T (2020) Potential of augmented reality platforms to improve individual hearing aids and to support more ecologically valid research. Ear Hear 41(Suppl 1):140S

    Article  PubMed  PubMed Central  Google Scholar 

  22. Grimm G, Luberadzka J, Hohmann V (2019) A toolbox for rendering virtual acoustic environments in the context of audiology. Acta Acust United Acust 105(3):566–578. https://doi.org/10.3813/AAA.919337

    Article  Google Scholar 

  23. Eastgate R, Picinali L, Patel H, D’Cruz M (2016) 3D games for tuning and learning about hearing aids. Hear J 69(4):30–32

    Article  Google Scholar 

  24. Appel L, Appel E, Bogler O, Wiseman M, Cohen L, Ein N, Campos JL et al (2020) Older adults with cognitive and/or physical impairments can benefit from immersive virtual reality experiences: a feasibility study. Front Med 6:329

    Article  Google Scholar 

  25. Steadman MA, Kim C, Lestang JH, Goodman DF, Picinali L (2019) Short-term effects of sound localization training in virtual reality. Sci Rep 9(1):1–17

    Article  Google Scholar 

  26. Rennies J (2023) Better hearing for all: smart solutions for the clinical, subclinical, and normal-hearing population. In: Techniques of Hearing. Routledge, London, pp 77–89

    Google Scholar 

  27. Blustein J, Weinstein BE, Chodosh J (2022) Over-the-counter hearing aids: what will it mean for older americans? J Am Geriatr Soc. https://doi.org/10.1111/jgs.17781

  28. Edwards B (2020) Emerging technologies, market segments, and MarkeTrak 10 insights in hearing health technology. Semin Hear 41(01):37–54

    Article  Google Scholar 

  29. Ross F (2020) Hearing aid accompanying smartphone apps in hearing healthcare. A systematic review. Appl Med Inform 42(4):189–199

    Google Scholar 

  30. Rahme M, Folkeard P, Scollie S (2021) Evaluating the accuracy of step tracking and fall detection in the Starkey Livio artificial intelligence hearing aids: A pilot study. Am J Audiol 30(1):182–189

    Article  PubMed  Google Scholar 

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Acknowledgements

Many thanks to G. Grimm, H. Kayser and all other members of the Auditory Signal Processing group at Oldenburg University.

Funding

Funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation)—Project-ID 352015383 – SFB 1330 – project B1.

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Authors and Affiliations

  1. Department of Medical Physics and Acoustics, University of Oldenburg, 26111, Oldenburg, Germany

    Volker Hohmann

  2. Hörzentrum Oldenburg gGmbH, Oldenburg, Germany

    Volker Hohmann

  3. Cluster of Excellence Hearing4all, Oldenburg, Germany

    Volker Hohmann

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  1. Volker Hohmann
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Correspondence to Volker Hohmann.

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Conflict of interest

V. Hohmann declares that he has no competing interests.

For this article no studies with human participants or animals were performed by any of the authors. All studies mentioned were in accordance with the ethical standards indicated in each case.

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Hohmann, V. The future of hearing aid technology. Z Gerontol Geriat 56, 283–289 (2023). https://doi.org/10.1007/s00391-023-02179-y

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  • DOI: https://doi.org/10.1007/s00391-023-02179-y

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