Advanced Sound Processing for Hearing Loss

Overseen By Donghyeon Yun

Age: 18+

Sex: Any

Trial Phase: Academic

Sponsor: Indiana University

Disqualifiers: Normal hearing, Mixed hearing loss, others

No Placebo Group All trial participants will receive the active study treatment (no placebo)

Compensation: Varies

Number of Visits: 2

What You Need to Know Before You Apply

What is the purpose of this trial?

This trial examines how new sound processing techniques can enhance speech understanding for people with hearing loss. It tests various settings of Nonlinear Signal Processing Algorithms in different noisy environments. Participants should have similar hearing loss in both ears, which should not be too severe. Those who struggle to understand speech in noisy places and have been diagnosed with this type of hearing loss might be suitable for this trial. As an unphased study, this trial provides a unique opportunity to contribute to innovative research that could advance hearing aid technology for many.

Will I have to stop taking my current medications?

The trial information does not specify whether you need to stop taking your current medications.

What prior data suggests that these nonlinear signal processing algorithms are safe for hearing loss?

Research has shown that special computer programs in some digital hearing aids are generally well-received by users. One study tested three different programs—LinEar, DynEar, and RangeEar—and participants had positive experiences with each. These programs did not cause any major side effects.

Another study examined how these programs could improve speech understanding, especially for those with severe hearing loss. The results were encouraging, showing improved speech understanding without any safety concerns.

Overall, these programs aim to enhance hearing without causing harm. While research continues, evidence so far suggests they are safe for use in hearing devices. ^{1 2 3 4 5}

Why are researchers excited about this trial?

Unlike traditional hearing aids that amplify sound, nonlinear signal processing algorithms aim to enhance hearing by optimizing how sound is processed in different environments. Researchers are excited about these algorithms because they adapt to various noise levels and signal-to-noise ratios, potentially offering clearer sound in challenging listening situations. This innovative approach could significantly improve the quality of life for those with hearing loss by making conversations and environmental sounds more intelligible, even in noisy settings.

What evidence suggests that nonlinear signal processing algorithms are effective for hearing loss?

Research has shown that special computer programs, such as the Nonlinear Signal Processing Algorithms studied in this trial, can help people with hearing loss understand speech better. One study showed that these programs assisted individuals with high-frequency hearing loss by adjusting sound frequencies to clarify speech. Another study found that children with hearing aids using these programs could hear sounds they usually miss. Additionally, different types of these programs have improved sound quality for users. These findings suggest that such programs could effectively help people with hearing loss hear speech more clearly. ^{3 4 6 7 8}

Are You a Good Fit for This Trial?

This trial is for English-speaking adults aged 18-65 with bilateral, symmetric sensorineural hearing loss that's less than 75 dB at low frequencies. It excludes non-native English speakers, those with normal or mixed hearing loss, asymmetric hearing loss, and severe loss above 70 dB at higher frequencies.

Inclusion Criteria

I am a native English speaker.

My hearing loss in both ears is less than 75 dB at low tones.

Exclusion Criteria

English is not my first language.

You have hearing loss that is worse than 70 decibels at 2000 Hertz and below.

My hearing is normal or I have mixed or uneven hearing loss.

Timeline for a Trial Participant

Screening

Participants are screened for eligibility to participate in the trial

1-2 weeks

Experimental Testing

Participants will undergo perceptual measures for different algorithm settings and environmental variables

1-2 hours

1 visit (in-person)

Preference Assessment

Algorithm preference will be measured for each experimental condition

15 minutes

1 visit (in-person)

Follow-up

Participants are monitored for any delayed effects or feedback on the algorithms used

1-2 weeks

What Are the Treatments Tested in This Trial?

Interventions

• Nonlinear Signal Processing Algorithms

Trial Overview The study tests the Tympan device to see how its nonlinear signal processing algorithms affect speech understanding in people with certain types of hearing loss.

How Is the Trial Designed?

Group I: Perceptual measures Experimental Treatment 1 Intervention

Perception will be measured for different algorithm settings and environmental variables (type of noise and signal-to-noise ratio)

Who Is Running the Clinical Trial?

Indiana University

Lead Sponsor

Trials

1,063

Recruited

1,182,000+

Published Research Related to This Trial

The new method for measuring distortion product otoacoustic emissions (DPOAE) uses a nonlinear adaptive algorithm that effectively extracts and measures signals, demonstrating high immunity to background noise and variations.

This method not only simplifies the measurement process but also significantly reduces measurement time compared to conventional techniques, making it particularly beneficial for clinical examinations.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

A novel method of estimation of DPOAE signals. Ziarani, AK., Konrad, A.[2019]

Digital filtering methods, such as Wiener and Kalman filtering, have significantly improved the estimation of waveforms in evoked potential research, which is crucial due to the low signal-to-noise ratio typically encountered.

Pattern recognition techniques, including linear stepwise discriminant analysis, are increasingly applied to analyze evoked potentials, enhancing the accuracy of psychophysiological testing for auditory and visual stimuli.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Signal processing in evoked potential research: applications of filtering and pattern recognition. McGillem, CD., Aunon, JI., Childers, DG.[2007]

Complex digital signal processing in bone anchored hearing aids shows a small but statistically non-significant improvement in speech understanding in quiet environments, with an average increase of +0.9 dB.

The most notable benefit of complex digital signal processing occurs in noisy environments, particularly when noise comes from behind the listener, where users experienced an average improvement of +3.2 dB, indicating enhanced speech understanding in challenging listening situations.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Is complex signal processing for bone conduction hearing aids useful? Kompis, M., Kurz, A., Pfiffner, F., et al.[2014]

Audiometric data base analysis (ADBA) is crucial for evaluating the effectiveness of hearing conservation programs (HCPs) in preventing occupational hearing loss, but it requires careful consideration of various influencing factors such as testing techniques and environmental conditions.

The paper highlights the importance of analyzing population parameters like age, sex, and noise exposure history, and presents case studies to demonstrate how ADBA can be applied to assess hearing loss trends in different work environments.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Using audiometric data base analysis. Royster, JD., Royster, LH.[2019]

Brainstem auditory evoked potentials (BSEP) are an effective method for assessing hearing loss in both humans and animals, providing a reliable way to measure auditory function.

The study highlights the advantages of digital filtering techniques over traditional analog methods in recording BSEP, which can enhance the accuracy of detecting threshold shifts in hearing, especially in noise exposure studies conducted on rats.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Laboratory methods of assessing hearing loss. Møller, AR.[2018]

A computerized system for collecting and analyzing audiometric data can effectively identify workers at high risk for hearing loss due to noise exposure, enhancing hearing protection efforts.

This system allows for better monitoring of hearing impairment progression, which can lead to improved medical care and targeted protection for at-risk workers.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

[A computerized system for the protection of the hearing of workers exposed to noise]. Sliwińska-Kowalska, M., Sułkowski, W., Jurewicz, B., et al.[2006]

In a study involving 64 children aged 2 to 7 years with bilateral hearing loss, nonlinear frequency compression (NLFC) in hearing aids significantly improved speech intelligibility and cortical responses compared to conventional processing.

Parents reported that their children's functional performance with NLFC hearing aids was similar or better in both quiet and noisy environments, indicating that NLFC may enhance real-life communication abilities, especially for children with poorer hearing at 4 kHz.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Aided cortical response, speech intelligibility, consonant perception and functional performance of young children using conventional amplification or nonlinear frequency compression. Zhang, VW., Ching, TY., Van Buynder, P., et al.[2018]

Compression amplification in hearing aids is becoming increasingly popular, highlighting the importance of nonlinear signal processing for improving hearing aid performance.

The paper discusses various nonlinear regulation systems beyond just amplitude compression, suggesting advancements in hearing aid technology that could enhance user experience and sound quality.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Automatic regulation systems with relevance to hearing aids. Barfod, J.[2000]

Two digital signal processing techniques, frequency domain processing and time domain processing, significantly improved speech intelligibility by 15-30% for 16 subjects with sensorineural hearing loss when tested with modified audio signals.

In a follow-up experiment with 16 additional subjects, the signal with 6 dB per octave emphasis was preferred over other processed signals, indicating a potential effective approach for enhancing telephone communication in individuals with high-frequency hearing loss.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Processing the telephone speech signal for the hearing impaired. Terry, M., Bright, K., Durian, M., et al.[2019]

The study evaluated a new adaptive non-linear frequency compression (NLFC) in 14 children aged 6-17 with varying degrees of hearing loss, showing that this new processing method significantly improved speech perception compared to conventional NLFC.

Children using the adaptive NLFC demonstrated better performance in word recognition and plural detection, indicating that this approach may better preserve the sound characteristics important for understanding speech.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Preliminary evaluation of a novel non-linear frequency compression scheme for use in children. Wolfe, J., Duke, M., Schafer, EC., et al.[2019]

Digital signal processing techniques in hearing aids allow for advanced features like noise reduction and speech enhancement, which are not possible with traditional analog aids.

The paper reviews various algorithms that improve hearing aid performance, suggesting that these technologies can significantly enhance the listening experience for users.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Application of digital signal processing to hearing aids: a critical survey. Murray, DJ., Hanson, JV.[2020]

The study explores the use of non-linearly transformed speech signals to better understand how the auditory system works in both healthy individuals and those with auditory disorders.

Psycho-acoustic experiments were conducted to assess how people perceive these transformed speech signals, providing insights into the effectiveness of these transformations in preserving the original meaning of the speech.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

[Use of non-linearly transformed speech signals for studying the auditory analyzer]. Solodilov, VIu., Strangul', ON.[2006]

Citations

1. pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov/articles/PMC2705616/

Evaluation of nonlinear frequency compression This study evaluated prototype multichannel nonlinear frequency compression (NFC) signal processing on listeners with high-frequency hearing loss.

2. pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov/articles/PMC4402226/

Nonlinear Frequency Compression in Hearing Aids The research questions of this study were: (1) Are children using nonlinear frequency compression (NLFC) in their hearing aids getting better access to the ...

3. researchgate.net researchgate.net/publication/13088114_Non-Linear_Signal_Processing_in_Digital_Hearing_Aids

Non-Linear Signal Processing in Digital Hearing Aids Three different non-linear digital signal processing algorithms were developed; LinEar, DynEar and RangeEar. All three provided individual ...

4. arxiv.org arxiv.org/abs/2406.05286

Signal processing algorithm effective for sound quality of ... Signal processing algorithm effective for sound quality of hearing loss simulators. Authors:Toshio Irino, Shintaro Doan, Minami Ishikawa.

5. tandfonline.com tandfonline.com/doi/abs/10.1080/14992020902971349

Evaluation of nonlinear frequency compression: Clinical ... Abstract. This study evaluated prototype multichannel nonlinear frequency compression (NFC) signal processing on listeners with high-frequency hearing loss.

6. pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov/articles/PMC4168920/

Nonlinear Hearing Aids and Verification of Fitting Targets - PMC This paper addresses the issue of initial verification of hearing aid gain and output for nonlinear hearing aids.

7. e-ceo.org e-ceo.org/m/journal/view.php?number=349

Simulation Test In order to improve the speech intelligibility of such severe hearing loss patients, two techniques have been suggested: nonlinear frequency ...

8. pubs.asha.org pubs.asha.org/doi/abs/10.1044/2022_JSLHR-22-00018

Preference for Combinations of Hearing Aid Signal ... The purpose of this study was to determine how multiple types of signal processing activated together influence listeners' preferences.