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A strategy scheme of self-fitting based on gain adjustment for digital hearing aids

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Abstract

The widespread use of traditional digital hearing aids is limited to a certain extent due to the shortage of professionals, and the cumbersome fitting process required for high-performance hearing aids. Against this background, we propose a strategy scheme of self-fitting based on the gain adjustment for digital hearing aids in this paper. First, the scheme combines a multi-channel wide dynamic range compression algorithm and prescription formula to achieve personalized gain compensation for patients with hearing loss. Second, the proposed problem-based guided gain adjustment scheme is used to realize individualized gain adjustment for hearing loss patients. In the gain adjustment scheme, the daily environment factors of patients are considered, and the historical adjustment parameter groups similar to patients are accurately matched by combining the optimized acoustic discrimination algorithm with the similarity matching algorithm. The experimental simulation shows that the proposed scheme can effectively improve patients’ speech recognition rate, speech intelligibility, and speech quality compared with traditional algorithms from both subjective and objective experiments.

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References

  1. Li Y, Fang X, Zhao WG et al (2017) A risk factor analysis of cognitive impairment in elderly patients with chronic diseases in a Chinese population. Med Sci Monit 23:4549–4558

    Article  Google Scholar 

  2. Kenna MA (2015) Acquired Hearing Loss in Children. Otolaryngol Clin North Am 48:933–953

    Article  Google Scholar 

  3. Li L, Simonsick EM, Ferrucci L, Lin FR (2013) Hearing loss and gait speed among older adults in the United States. Gait Posture 38:25–29

    Article  Google Scholar 

  4. Abu-Ghanem S, Handzel O, Ness L et al (2016) Smartphone-based audiometric test for screening hearing loss in the elderly. Eur Arch Oto-Rhino-Laryngology. 273:333–339

    Article  Google Scholar 

  5. Choi JS, Betz J, Deal J et al (2016) A Comparison of Self-Report and Audiometric Measures of Hearing and Their Associations with Functional Outcomes in Older Adults. J Aging Health 28:890–910

    Article  Google Scholar 

  6. Nicholas JG, Geers AE (2006) Effects of early auditory experience on the spoken language of deaf children at 3 years of age. Ear Hear 27:286–298

    Article  Google Scholar 

  7. Arndt S, Aschendorff A, Laszig R et al (2011) Comparison of pseudobinaural hearing to real binaural hearing rehabilitation after cochlear implantation in patients with unilateral deafness and tinnitus. Otol Neurotol 32:39–47

    Article  Google Scholar 

  8. Contrera KJ, Betz J, Li L et al (2016) Quality of life after intervention with a cochlear implant or hearing aid. Laryngoscope. 126:2110–2115

    Article  Google Scholar 

  9. Keidser G, Dillon H, Carter L, O’Brien A (2012) NAL-NL2 Empirical Adjustments. Trends Amplif 16:211–223

    Article  Google Scholar 

  10. Stelmachowicz PG, Dalzell S, Peterson D et al (1998) A comparison of threshold-based fitting strategies for nonlinear hearing aids. Ear Hear 19:131–138

    Article  Google Scholar 

  11. Ricketts TA (1996) Fitting hearing aids to individual loudness-perception measures. Ear Hear 17:124–132

    Article  Google Scholar 

  12. Haile LM, Kamenov K, Briant PS et al (2021) Hearing loss prevalence and years lived with disability, 1990–2019: Findings from the Global Burden of Disease Study 2019. Lancet 397:996–1009

    Article  Google Scholar 

  13. Keidser G, Convery E (2016) Self-Fitting Hearing Aids: Status Quo and Future Predictions. Trends Hear 20:1–15

    Google Scholar 

  14. Chen J, Baer T, Moore BCJ (2013) Effect of spectral change enhancement for the hearing impaired using parameter values selected with a genetic algorithm. J Acoust Soc Am 133:2910–2920

    Article  Google Scholar 

  15. Takagi H, Ohsaki M (2007) Interactive evolutionary computation-based hearing aid fitting. IEEE Trans Evol Comput 11:414–427

    Article  Google Scholar 

  16. Nielsen JBB, Nielsen J, Larsen J (2015) Perception-based personalization of hearing aids using gaussian processes and active learning. IEEE/ACM Trans Audio Speech Lang Process. 23:162–173

    Google Scholar 

  17. Liang R, Guo R, Xi J et al (2017) Self-fitting algorithm for digital hearing aid based on interactive evolutionary computation and expert system. Appl Sci. 7

  18. Xi J, Liang R, Fei X (2017) An algorithm of improving speech emotional perception for hearing aid. Mod Phys Lett B 31:1–7

    Article  Google Scholar 

  19. Convery E, Keidser G, Hickson L, Meyer C (2019) Factors associated with successful setup of a self-fitting hearing aid and the need for personalized support. Ear Hear 40:794–804

    Article  Google Scholar 

  20. Keidser G, Dillon H, Zhou D, Carter L (2011) Threshold Measurements by Self-Fitting Hearing Aids: Feasibility and Challenges. Trends Amplif 15:167–174

    Article  Google Scholar 

  21. Madsen SMK, Stone MA, McKinney MF et al (2015) Effects of wide dynamic-range compression on the perceived clarity of individual musical instruments. J Acoust Soc Am 137:1867–1876

    Article  Google Scholar 

  22. Liang R, Xi J, Bao Y (2017) Multichannel loudness compensation method based on segmented sound pressure level for digital hearing AIDS. Mod Phys Lett B 31:1–6

    Article  Google Scholar 

  23. Killion MC (1995) Loudness-data basis for “‘FIG6"’ hearing-aid fitting targets. J Acoust Soc Am 98:2927

    Article  Google Scholar 

  24. Furuki S, Sano H, Kurioka T et al (2021) Comparison of real-ear insertion gains in Japanese-speaking individuals wearing hearing aids with DSLv5 and NAL-NL2. Auris Nasus Larynx 48:75–81

    Article  Google Scholar 

  25. Prathosh AP, Ramakrishnan AG, Ananthapadmanabha TV (2014) Estimation of voice-onset time in continuous speech using temporal measures. J Acoust Soc Am. 136:EL122-El128

    Article  Google Scholar 

  26. Kates JM, Arehart KH (2021) The Hearing-Aid Speech Perception Index (HASPI) Version 2. Speech Commun 131:35–46

    Article  Google Scholar 

  27. Kates JM, Arehart KH (2014) The hearing-aid speech quality index (HASQI) version 2. AES J Audio Eng Soc. 62:99–117

    Article  Google Scholar 

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Acknowledgements

This work was supported in part by the National Key Research and Development Program of China under Grant No. 2020YFC2004002 and 2020YFC2004003, the National Natural Science Foundation of China under Grant No. 62001215.

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Author notes

  1. Ruxue Guo, Cairong Zou and Ruiyu Liang contributed equally to this work.

Authors and Affiliations

  1. School of Information Science and Engineering, Southeast University, Nanjing, 210096, Jiangsu, China

    Yang Yang, Ruxue Guo & Cairong Zou

  2. School of Information and Communication Engineering, Institute of Nanjing Technology, Nanjing, 211167, Jiangsu, China

    Ruiyu Liang

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  1. Yang Yang
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  2. Ruxue Guo
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  3. Cairong Zou
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  4. Ruiyu Liang
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Correspondence to Yang Yang.

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Yang, Y., Guo, R., Zou, C. et al. A strategy scheme of self-fitting based on gain adjustment for digital hearing aids. Multimed Tools Appl 83, 54367–54389 (2024). https://doi.org/10.1007/s11042-023-17705-8

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  • DOI: https://doi.org/10.1007/s11042-023-17705-8

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