Three-alternative forced-choice method (3AFC) for tinnitus matching and digital frequency customized relieving sound (DFCRS) generation strategy for tinnitus management

Dongmei  Tang; Kunkun  Wang; Shan  Sun

doi:10.59400/sv1928

Three-alternative forced-choice method (3AFC) for tinnitus matching and digital frequency customized relieving sound (DFCRS) generation strategy for tinnitus management

Dongmei Tang ENT Institute and Otorhinolaryngology Department of Eye & ENT Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, NHC Key Laboratory of Hearing Medicine, Fudan University, Shanghai 200031, China
Kunkun Wang ENT Institute and Otorhinolaryngology Department of Eye & ENT Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, NHC Key Laboratory of Hearing Medicine, Fudan University, Shanghai 200031, China
Shan Sun ENT Institute and Otorhinolaryngology Department of Eye & ENT Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, NHC Key Laboratory of Hearing Medicine, Fudan University, Shanghai 200031, China

Article ID: 1928

DOI: https://doi.org/10.59400/sv1928

Keywords: tinnitus; pitch matching; loudness matching; three-alternative forced-choice method (3AFC); digital frequency customized relieving sound (DFCRS)

Abstract

Tinnitus is the perception of sounds without any corresponding external stimulus exists, and it is one of the most common hearing disorders. Currently, there are no objective tests for tinnitus, and thus its detection relies on the subjective reports of patients. Here, we introduce a novel three-alternative forced-choice method (3AFC) for tinnitus pitch and loudness matching. Then, we modulate the soothing music by increasing the sound intensity of two 1/3 octave bands above and below the tinnitus frequency according to a specific algorithm to generate digital frequency customized relieving sound (DFCRS) for tinnitus management. Due to the relatively large frequency interval and more frequency characteristics, the 3AFC method can significantly shorten the time required for psychoacoustic measures of tinnitus and improve the efficiency and satisfaction of subjective tinnitus tests. Based on the matched tinnitus frequency, we created a personalized treatment plan for tinnitus patients using real-time modulation of soft music. We recruited total 32 participants who listened to the modulated music (DFCRS) or the unmodulated music (served as control) for at least 2 h a day for three months, following brief instructions from audiologists. Of these, the participants who received DFCRS experienced more reduced negative impacts of tinnitus and an improved quality of life compared to those in the control group, as measured by various scales. Our patented system seamlessly integrates tinnitus assessment and treatment, offering substantial savings in medical and audiological expenses.

References

[1]Elgoyhen AB, Langguth B, De Ridder D, et al. Tinnitus: perspectives from human neuroimaging. Nat Rev Neurosci 2015; 16: 632-642. 2015/09/17. DOI: 10.1038/nrn4003.

[2]Roberts LE, Eggermont JJ, Caspary DM, et al. Ringing ears: the neuroscience of tinnitus. J Neurosci 2010; 30: 14972-14979. 2010/11/12. DOI: 10.1523/jneurosci.4028-10.2010.

[3]Mühlnickel W, Elbert T, Taub E, et al. Reorganization of auditory cortex in tinnitus. Proc Natl Acad Sci U S A 1998; 95: 10340-10343. 1998/08/26. DOI: 10.1073/pnas.95.17.10340.

[4]Langguth B, Kreuzer PM, Kleinjung T, et al. Tinnitus: causes and clinical management. Lancet Neurol 2013; 12: 920-930. 2013/08/21. DOI: 10.1016/S1474-4422(13)70160-1.

[5]Baguley D, McFerran D and Hall D. Tinnitus. Lancet 2013; 382: 1600-1607. 2013/07/06. DOI: 10.1016/s0140-6736(13)60142-7.

[6]Noreña AJ and Eggermont JJ. Changes in spontaneous neural activity immediately after an acoustic trauma: implications for neural correlates of tinnitus. Hear Res 2003; 183: 137-153. 2003/09/19. DOI: 10.1016/s0378-5955(03)00225-9.

[7]Henry JA. “Measurement” of Tinnitus. Otol Neurotol 2016; 37: e276-285. 2016/08/16. DOI: 10.1097/mao.0000000000001070.

[8]Henry JA, Roberts LE, Ellingson RM, et al. Computer-automated tinnitus assessment: noise-band matching, maskability, and residual inhibition. J Am Acad Audiol 2013; 24: 486-504. 2013/07/28. DOI: 10.3766/jaaa.24.6.5.

[9]Henry JA and Meikle MB. Psychoacoustic measures of tinnitus. J Am Acad Audiol 2000; 11: 138-155. 2001/02/07.

[10]Norena A, Micheyl C, Chéry-Croze S, et al. Psychoacoustic characterization of the tinnitus spectrum: implications for the underlying mechanisms of tinnitus. Audiol Neurootol 2002; 7: 358-369. 2002/10/29. DOI: 10.1159/000066156.

[11]Roberts LE, Moffat G and Bosnyak DJ. Residual inhibition functions in relation to tinnitus spectra and auditory threshold shift. Acta Otolaryngol Suppl 2006: 27-33. 2006/11/23. DOI: 10.1080/03655230600895358.

[12]Hébert S. Individual Reliability of the Standard Clinical Method vs Patient-Centered Tinnitus Likeness Rating for Assessment of Tinnitus Pitch and Loudness Matching. JAMA Otolaryngol Head Neck Surg 2018; 144: 1136-1144. 2018/09/30. DOI: 10.1001/jamaoto.2018.2416.

[13]Henry JA, Flick CL, Gilbert A, et al. Comparison of two computer-automated procedures for tinnitus pitch matching. J Rehabil Res Dev 2001; 38: 557-566. 2001/12/06.

[14]Henry JA and Meikle MB. Pulsed versus continuous tones for evaluating the loudness of tinnitus. J Am Acad Audiol 1999; 10: 261-272. 1999/05/20.

[15]Neff P, Langguth B, Schecklmann M, et al. Comparing Three Established Methods for Tinnitus Pitch Matching With Respect to Reliability, Matching Duration, and Subjective Satisfaction. Trends Hear 2019; 23: 2331216519887247. 2019/12/07. DOI: 10.1177/2331216519887247.

[16]ISO 226. Acoustics — Normal equal-loudnesslevel contours. 2023.

[17]Schleuning AJ, Johnson RM and Vernon JA. Evaluation of a tinnitus masking program: a follow-up study of 598 patients. Ear Hear 1980; 1: 71-74. 1980/03/01. DOI: 10.1097/00003446-198003000-00004.

[18]Fuller T, Cima R, Langguth B, et al. Cognitive behavioural therapy for tinnitus. Cochrane Database Syst Rev 2020; 1: Cd012614. 2020/01/09. DOI: 10.1002/14651858.CD012614.pub2.

[19]Tyler RS, Gogel SA and Gehringer AK. Tinnitus activities treatment. Prog Brain Res 2007; 166: 425-434. 2007/10/25. DOI: 10.1016/s0079-6123(07)66041-5.

[20]Tyler RS, Gehringer AK, Noble W, et al. Tinnitus Activities Treatment. In: Tyler RS (ed) Tinnitus Treatment: Clinical Protocols. New York: Thieme, 2006, pp.116-132.

[21]Tyler RS, Stocking C, Ji H, et al. Tinnitus Activities Treatment with Total and Partial Masking. J Am Acad Audiol 2021; 32: 501-509. 2021/12/30. DOI: 10.1055/s-0041-1731698.

[22]Tang D, Li H and Chen L. Advances in Understanding, Diagnosis, and Treatment of Tinnitus. Adv Exp Med Biol 2019; 1130: 109-128. 2019/03/28. DOI: 10.1007/978-981-13-6123-4_7.

[23]Tyler RS, Perreau A, Powers T, et al. Tinnitus Sound Therapy Trial Shows Effectiveness for Those with Tinnitus. J Am Acad Audiol 2020; 31: 6-16. 2019/06/19. DOI: 10.3766/jaaa.18027.

[24]Jastreboff PJ and Jastreboff MM. Tinnitus retraining therapy: a different view on tinnitus. ORL J Otorhinolaryngol Relat Spec 2006; 68: 23-29; discussion 29-30. 2006/03/04. DOI: 10.1159/000090487.

[25]Tyler RS, Noble W, Coelho CB, et al. Tinnitus retraining therapy: mixing point and total masking are equally effective. Ear Hear 2012; 33: 588-594. 2012/05/23. DOI: 10.1097/AUD.0b013e31824f2a6e.

[26]Bauer CA and Brozoski TJ. Effect of tinnitus retraining therapy on the loudness and annoyance of tinnitus: a controlled trial. Ear Hear 2011; 32: 145-155. 2010/10/05. DOI: 10.1097/AUD.0b013e3181f5374f.

[27]Bentler RA and Tyler RS. Tinnitus management. Asha 1987; 29: 27-32. 1987/05/01.

[28]Tyler RS, Stouffer JL and Schum R. Audiological rehabilitation of the tinnitus client. Journal of the Academy of Rehabilitative Audiology 1989.

[29]Okamoto H, Stracke H, Stoll W, et al. Listening to tailor-made notched music reduces tinnitus loudness and tinnitus-related auditory cortex activity. Proceedings of the National Academy of Sciences of the United States of America 2010; 107: 1207-1210. 2010/01/19. DOI: 10.1073/pnas.0911268107.

[30]Tavanai E, Rahimi V, Bandad M, et al. Efficacy of tailor-made notched music training (TMNMT) in the treatment of tinnitus: a systematic review and meta-analysis. Eur Arch Otorhinolaryngol 2024; 281: 5033-5049. 2024/06/07. DOI: 10.1007/s00405-024-08732-8.

[31]Davis PB, Paki B and Hanley PJ. Neuromonics Tinnitus Treatment: third clinical trial. Ear Hear 2007; 28: 242-259. 2007/05/15. DOI: 10.1097/AUD.0b013e3180312619.

[32]Gupta J and Gupta R. A Scoping New Revolution for Tinnitus Management: A Neuromonics Narrative Review. Curr Drug Targets 2023; 24: 274-286. 2022/12/23. DOI: 10.2174/1389450124666221220165137.

[33]Tass PA, Adamchic I, Freund HJ, et al. Counteracting tinnitus by acoustic coordinated reset neuromodulation. Restor Neurol Neurosci 2012; 30: 137-159. 2012/03/15. DOI: 10.3233/rnn-2012-110218.

[34]Adamchic I, Toth T, Hauptmann C, et al. Acute effects and after-effects of acoustic coordinated reset neuromodulation in patients with chronic subjective tinnitus. Neuroimage Clin 2017; 15: 541-558. 2017/06/28. DOI: 10.1016/j.nicl.2017.05.017.

[36]Jacquemin L, Gilles A and Shekhawat GS. Hearing more to hear less: a scoping review of hearing aids for tinnitus relief. Int J Audiol 2022; 61: 887-895. 2021/12/07. DOI: 10.1080/14992027.2021.2007423.

[37]Tyler RS, Rubinstein J, Pan T, et al. Electrical stimulation of the cochlea to reduce tinnitus. In: Seminars in hearing 2008, pp.326-332. © Thieme Medical Publishers.

[38]Sarac ET, Ozbal Batuk M, Batuk IT, et al. Effects of Cochlear Implantation on Tinnitus and Depression. ORL J Otorhinolaryngol Relat Spec 2020; 82: 209-215. 2020/07/01. DOI: 10.1159/000508137.

[39]Tyler RS, Aran J-M and Dauman R. Recent advances in tinnitus. American journal of audiology 1992; 1: 36-44.

[40]Dauman R and Tyler R. Some considerations on the classification of tinnitus. In: Proceedings of the fourth international tinnitus seminar, Bordeaux, France 1992, pp.225-229. Kugler Amsterdam, the Netherlands.

[41]Tyler RS. Neurophysiological models, psychological models, and treatments for tinnitus. Tinnitus treatment: Clinical protocols 2006: 1-22.

[42]Preece JP, Tyler RS and Noble W. The management of tinnitus. Geriatrics and Aging 2003; 6: 22.

[43]Yakunina N and Nam EC. Does the tinnitus pitch correlate with the frequency of hearing loss? Acta Otolaryngol 2021; 141: 163-170. 2020/11/05. DOI: 10.1080/00016489.2020.1837394.

[44]Moore BC, Vinay and Sandhya. The relationship between tinnitus pitch and the edge frequency of the audiogram in individuals with hearing impairment and tonal tinnitus. Hear Res 2010; 261: 51-56. 2010/01/28. DOI: 10.1016/j.heares.2010.01.003.

[45]Schecklmann M, Vielsmeier V, Steffens T, et al. Relationship between Audiometric slope and tinnitus pitch in tinnitus patients: insights into the mechanisms of tinnitus generation. PLoS One 2012; 7: e34878. 2012/04/25. DOI: 10.1371/journal.pone.0034878.

[46]Tyler R. The psychoacoustical measurement of tinnitus. Tinnitus handbook 2000: 149-179.

[47]Tyler RS, Oleson J, Noble W, et al. Clinical trials for tinnitus: study populations, designs, measurement variables, and data analysis. Progress in brain research 2007; 166: 499-509.

[48]Henry JA, McMillan GP, Thielman EJ, et al. Evaluating psychoacoustic measures for establishing presence of tinnitus. J Rehabil Res Dev 2013; 50: 573-584. 2013/08/13. DOI: 10.1682/jrrd.2012.05.0090.

[49]Henry JA, Zaugg TL and Schechter MA. Clinical guide for audiologic tinnitus management I: Assessment. Am J Audiol 2005; 14: 21-48. 2005/09/27. DOI: 10.1044/1059-0889(2005/004).

[50]Tyler R, Perreauf A, Mohr A-M, et al. An exploratory step toward measuring the “meaning of life” in patients with tinnitus and in cochlear implant users. Journal of the American Academy of Audiology 2020; 31: 277-285.

Published

2025-01-21

How to Cite

Tang, D., Wang, K., & Sun, S. (2025). Three-alternative forced-choice method (3AFC) for tinnitus matching and digital frequency customized relieving sound (DFCRS) generation strategy for tinnitus management. Sound & Vibration, 59(1), 1928. https://doi.org/10.59400/sv1928

Download Citation

Issue

Vol. 59 No. 1 (2025)

Section

Articles

This work is licensed under a Creative Commons Attribution 4.0 International License.

Editor-in-Chief

Prof. Jun Yang

Institute of Acoustics, Chinese Academy of Sciences, China

ISSN

1541-0161 (Print)

2693-1443 (Online)

Publication Frequency

Continuously

About the Publisher

Academic Publishing insists on taking academic exchange and publication as the main line, carrying out comprehensive management based on science and technology, and fully exploring excellent international publishing resources. Within 5 years, it will form a strategic framework and scale with science (S), technology (T), medicine (M), education (E), and humanities and arts (H) as the main publishing fields. Academic Publishing is headquartered in Singapore and based in Malaysia, with the United States and China providing the main scientific and academic resources. At the same time, it has established long-term good cooperative relations with other publishing companies, scientific research communities, and academic organizations in more than a dozen countries and regions. Academic Publishing uses English and Chinese as its main publishing languages, mainly publishing books, journals, and conference papers in print and online. The vast majority of publications follow the international open access policy, providing stable and long-term quality and professional publications. With the joint efforts of the expert team and our professional editorial team, our publications will gradually be indexed by international databases in stages to provide convenient and professional retrieval for various scholars. At the same time, manuscripts we accept will be subject to the peer review principle, and cutting-edge and innovative research articles will be preferentially accepted for peer reference and discussion. All kinds of our publications are welcome for peer to contribute, access, and download.

more

Volume Arrangement

Vol 59 Iss 1 (2025)

more issues

Featured Articles

Soundscapes in Arab Cities: A Systematic Review and Research Agenda

In the context of Arab cities, this study explores the intricate interplay between cultural, historical, and environmental elements that shape their unique soundscapes. The paper aims to shed light on this underrepresented field of study by employing a three-fold research approach: systematic review, a comprehensive literature review, and the formulation of a future research agenda. The first part of the investigation focuses on research productivity in the Arab world regarding soundscape studies. An analysis of publication trends reveals that soundscape research in Arab cities is still an emerging area of interest. Critical gaps in the existing body of literature are identified, highlighting the importance of addressing these gaps within the broader context of global soundscape research. The second part of the study delves into the distinctive features that inform the soundscapes of Arab cities. These features are categorized into three overarching groups: (i) cultural and religious life, (ii) daily life, and (iii) heritage and history, by exploring these factors, the study aims to elucidate the multifaceted nature of Arab urban soundscapes. From the resonating calls to prayer and the vibrant ambiance of traditional cafes to the bustling markets and architectural characteristics, each factor contributes to the auditory tapestry that defines Arab cities. The paper concludes with a forward-looking research agenda, proposing sixteen key questions organized into descriptive and comparative categories. These questions emphasize the need for a more profound understanding of sound perception, sources, and the impact of urban morphology on the soundscape. Additionally, they highlight the need for interdisciplinary research, involving fields such as urban planning, architecture, psychology, sociology, and cultural studies to unravel the complexity of Arab urban soundscapes.

Prediction of Sound Transmission Loss of Vehicle Floor System Based on 1D-Convolutional Neural Networks

The Noise, Vibration, and Harshness (NVH) experience during driving is significantly influenced by the sound insulation performance of the car floor acoustic package. As such, accurate and efficient predictions of its sound insulation performance are crucial for optimizing related noise reduction designs. However, the complex acoustic transmission mechanisms and difficulties in characterizing the sound absorption and insulation properties of the floor acoustic package pose significant challenges to traditional Computer-Aided Engineering (CAE) methods, leading to low modeling efficiency and prediction accuracy. To address these limitations, a hierarchical multi-objective decomposition system for predicting the sound insulation performance of the floor acoustic package has been developed based on an analysis of the noise transmission path. This approach involves introducing a 1D-Convolutional Neural Network (1D-CNN) model for predicting the sound insulation performance of the floor acoustic package, thereby avoiding the limitations of conventional CAE approaches that rely solely on “data-driven” methods. The proposed method was applied and tested using specific vehicle models, and the results demonstrated the effectiveness and superiority of the proposed approach relative to those obtained using 2D-CNN and Support Vector Regression (SVR) models.

A Sound Quality Evaluation Method for Vehicle Interior Noise Based on Auditory Loudness Model

When designing and optimizing the hull of vehicles, their sound quality needs to be considered, which greatly depends on the psychoacoustic parameters. However, the traditional psychoacoustic calculation method does not consider the influence of the real human ear anatomic structure, even the loudness which is most related to the auditory periphery. In order to introduce the real physiological structure of the human ear into the evaluation of vehicle sound quality, this paper first carried out the vehicle internal noise test to obtain the experimental samples. Then, the physiological loudness was predicted based on an established human ear physiological model, and the noise evaluation vector was constructed by combining the remaining four psychoacoustic parameters. Finally, the evaluation vector was fitted into the subjective evaluation results of vehicle interior noise by a deep neural network. The results show that our proposed method can estimate the human subjective perception of vehicle interior noise well.

Prediction and Analysis of Vehicle Interior Road Noise Based on Mechanism and Data Series Modeling

Currently, the inexorable trend toward the electrification of automobiles has heightened the prominence of road noise within overall vehicle noise. Consequently, an in-depth investigation into automobile road noise holds substantial practical importance. Previous research endeavors have predominantly centered on the formulation of mechanism models and data-driven models. While mechanism models offer robust controllability, their application encounters challenges in intricate analyses of vehicle body acoustic-vibration coupling, and the effective utilization of accumulated data remains elusive. In contrast, data-driven models exhibit efficient modeling capabilities and can assimilate conceptual vehicle knowledge, but they impose stringent requirements on both data quality and quantity. In response to these considerations, this paper introduces an innovative approach for predicting vehicle road noise by integrating mechanism-driven and data-driven methodologies. Specifically, a series model is devised, amalgamating mechanism analysis with data-driven techniques to predict vehicle interior noise. The simulation results from dynamic models serve as inputs to the data-driven model, ultimately generating outputs through the utilization of the Long Short-Term Memory with Autoencoder (AE-LSTM) architecture. The study subsequently undertakes a comparative analysis between different dynamic models and data-driven models, thereby validating the efficacy of the proposed series vehicle road noise prediction model. This series model, encapsulating the rigid-flexible coupling dynamic model and AE-LSTM series model, not only demonstrates heightened computational efficiency but also attains superior prediction accuracy.