Advanced Sound Processing for Hearing Loss

Age: 18+

Sex: Any

Travel: May Be Covered

Time Reimbursement: Varies

Trial Phase: Academic

Recruiting

Sponsor: Indiana University

Disqualifiers: Normal hearing, Mixed hearing loss, others

No Placebo Group

Trial Summary

What is the purpose of this trial?

This trial is testing special computer programs in a wearable device to help people who use hearing aids understand speech better. The device adjusts sound volume based on how loud the sounds are, making it easier to hear quiet sounds without making loud sounds too loud.

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 data supports the effectiveness of the treatment Advanced Sound Processing for Hearing Loss?

Research shows that nonlinear signal processing techniques, like those used in hearing aids, can improve sound quality and speech understanding by enhancing complex sound processing and reducing noise. Studies have found that these methods, including nonlinear frequency compression, can be particularly beneficial for children with hearing loss, helping them better perceive speech and sounds. ^{1 2 3 4 5}

Is there any safety data available for advanced sound processing methods used in hearing loss treatment?

The research articles provided do not contain specific safety data for advanced sound processing methods used in hearing loss treatment. ^{6 7 8 9 10}

How does the Advanced Sound Processing treatment for hearing loss differ from other treatments?

The Advanced Sound Processing treatment for hearing loss is unique because it uses digital signal processing techniques that allow for complex processing beyond what is possible with traditional analog hearing aids. This includes advanced algorithms for filtering, noise reduction, and speech enhancement, which can significantly improve speech intelligibility and reduce background noise, offering a more tailored and effective hearing experience. ^{1 2 6 11 12}

Eligibility Criteria

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.

I am between 18 and 65 years old.

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

Exclusion Criteria

English is not my first language.

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

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

Trial Timeline

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

Treatment Details

Interventions

• Nonlinear Signal Processing Algorithms (Other)

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.

Participant Groups

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+

Findings from Research

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]

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]

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]

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]

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]

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]

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]

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]

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 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]

References

1. Denmark pubmed.ncbi.nlm.nih.gov

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

2. United States pubmed.ncbi.nlm.nih.gov

Application of digital signal processing to hearing aids: a critical survey. [2020]

3. England pubmed.ncbi.nlm.nih.gov

Is complex signal processing for bone conduction hearing aids useful? [2014]

4. England pubmed.ncbi.nlm.nih.gov

Preliminary evaluation of a novel non-linear frequency compression scheme for use in children. [2019]

5. Ireland 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. [2018]

6. United States pubmed.ncbi.nlm.nih.gov

A novel method of estimation of DPOAE signals. [2019]

7. United States pubmed.ncbi.nlm.nih.gov

Using audiometric data base analysis. [2019]

8. United States pubmed.ncbi.nlm.nih.gov

Signal processing in evoked potential research: applications of filtering and pattern recognition. [2007]

9. Poland pubmed.ncbi.nlm.nih.gov

[A computerized system for the protection of the hearing of workers exposed to noise]. [2006]

10. United States pubmed.ncbi.nlm.nih.gov

Laboratory methods of assessing hearing loss. [2018]

11. United States pubmed.ncbi.nlm.nih.gov

Processing the telephone speech signal for the hearing impaired. [2019]

12. Russia (Federation) pubmed.ncbi.nlm.nih.gov

[Use of non-linearly transformed speech signals for studying the auditory analyzer]. [2006]