Problem In Hearing Aids Research Articles

A Switched Algorithm for Adaptive Feedback Cancellation Using Pre-Filters in Hearing Aids.

Acoustic coupling between microphone and loudspeaker is a significant problem in open-fit digital hearing aids. An open-fit compared to a close-fit hearing aid significantly lowers the signal quality and limits the achievable maximum stable gain. Adaptive feedback cancellation (AFC) enables an efficient approach to reduce the impact of acoustic coupling. However, without careful consideration, it can also introduce bias in estimating the feedback path due to the high correlation between the loudspeaker signal and the incoming signal, especially when the incoming signal is spectrally coloured, e.g., speech and music. The prediction error method (PEM) is well known for reducing this bias. The presented study aims to propose a switched PEM with soft-clipping (swPEMSC) that allows for further improvement in convergence/tracking rates, resulting in a better ability to recover from unstable/howling status. This swPEMSC employs a new update rule inspired by a soft-clipping based stability detector (SCSD). It allows to pick up either the PEMSC-NLMS or PEMSC-APA depending on the magnitude of the effective feedback signal; howling corresponds to a large feedback signal. The PEMSC-NLMS with a small step-size ensures a low steady-state error, but slow convergence/tracking rates, while PEMSC-APA with a large step-size allows for fast convergence/tracking rates, but a high steady-state error. By combining those approaches, the proposed approach can take advantage of good characteristics from both. Experimental results using different types of incoming signals and an abrupt change of feedback paths show that the swPEMSC can shorten unstable periods (howling) by improving the convergence and tracking rates while retaining a low steady-state error and good signal quality.

Adaptive Feedback Cancellation in Hearing Aids Based on Orthonormal Basis Functions With Prediction-Error Method Based Prewhitening

Acoustic feedback is a persistent problem in hearing aids, which limits the achievable amplification and may severely degrade the sound quality by producing howling artifacts. A potential approach to feedback cancellation is to estimate the feedback path utilizing an adaptive filter. However, estimation of the feedback path suffers a large model error, known as the bias, due to the correlation between the loudspeaker and source signals. A prediction-error method (PEM) based prewhitening filter has been widely utilized to reduce the bias. This approach, however, requires a large number of adaptive parameters, thus increasing the computational complexity, reducing the convergence rate, and limiting the added stable gain. We introduce an adaptive feedback cancellation (AFC) algorithm derived based on the orthonormal basis functions (OBFs) for closed-loop identification of the feedback path by minimizing the prediction error. The OBFs are defined by a set of fixed poles and a small number of adaptive tap-output weights. We study two methods for obtaining the fixed poles, an inherently stable least-squares method and a log-scale frequency resolution method. The poles are then embedded as the a priori information into the algorithm. The proposed algorithm is extensively evaluated with speech and music source signals and with sudden changes in the feedback path. The experimental results show that the proposed method significantly increases the added stable gain, accelerates the convergence rate, and enhances the sound quality compared to state-of-the-art, while requiring far fewer adaptive parameters which leads to reduced computational complexity.

Improving Speech Intelligibility in Monaural Segregation System by Fusing Voiced and Unvoiced Speech Segments

Improving the speech intelligibility remains a challenging problem in digital hearing aids. This research work proposes a new speech segregation algorithm to improve the speech intelligibility by effectively fusing the voiced and unvoiced segment of the speech signal using the genetic algorithm. The voiced speech segments are obtained using perceptual speech cues such as auto-correlation, cross-channel correlation and pitch. Similarly, the unvoiced speech segments are obtained using another perceptual speech cue onset/offset after subtracting the voiced segments. The speech onset- and offset-based segregation process actually produce segments for both voiced and unvoiced. The unvoiced speech segments are obtained by subtracting the voiced speech segments from the segments obtained using speech onset and offset. The unvoiced speech segments obtained using onset and offset may contain interference. This research work proposes a scheme to remove those interferences from the unvoiced speech segments and effectively fuse the segments of voiced and unvoiced speech using the genetic algorithm. The performance of the proposed algorithm is evaluated using the intelligibility measures such as CSII, NCM and STOI. The experimental results show that the proposed algorithm significantly improves the speech intelligibility with an average of 0.23 for CSII, 0.20 for NCM and 0.16 for STOI as compared with other existing systems.

Measurements of the acoustic feedback path of hearing aids on human subjects

Feedback is a problem in hearing aids which will cause signal degradation and reduce the maximum applicable gain. More specifically, the advantages of open fittings (e.g., minimizing the occlusion effect) are limited by acoustic feedback. Feedback cancelation algorithms are used to overcome these limitations. For the development of such algorithms, the acoustic feedback path of the hearing aid must be known. The acoustic feedback path is not only affected by the outer sound field but by the individual anatomy and physiology as well. In order to quantify these different influences, feedback path measurements were performed on 20 human subjects. The measurements included different static conditions as well as dynamic ones (i.e., repetitive movements were performed during the measurement). Since the sound pressure level must be limited in measurements on human subjects, a valid identification of the feedback path is difficult in many cases, due to a low signal to noise ratio. Therefore, all measurements were performed reciprocally in addition to the direct measurements. Results show that yaw movements only have a small influence on the acoustic feedback path, whereas changes of the outer sound field can have a substantial impact on the feedback path.

Structural feedback analysis of a hearing aid using finite element and lumped parameters methods

Hearing aids are designed to overcome hearing losses suffered by some individuals and operated by measuring and amplifying the acoustic field at certain frequency depending on the user hearing loss. In many cases, its transducers (microphone and loudspeaker) are near located, and a feedback signal phenomenon may occur, either through structural or airborne transmission. The structural feedback is characterized by a vibrational response at the microphone position produced by the loudspeaker, also called receiver, that result in a unwanted signal due to the microphone vibration sensitivity. If not properly controlled, the feedback signal builds up, resulting in a loud whistle at the user ear causing great discomfort. The objective of this work is to analyse the structural feedback mechanism at a behind-the-ear hearing aid, and proposed a numerical approach that allows the consideration of the phenomena during the design phase of such systems. A numerical model, based on the finite element method (FEM) and the lumped parameters method, was used to analyse and quantify the problem. While the hearing aid case was modelled using FEM, the receiver and its suspensions were represented by means of a single degree-of-freedom or a multiple degree-of-freedom systems. The procedures used to define material properties and dynamic parameters are presented and discussed. Experimental tests are used to validate the models separately and to determine vibration levels imposed at the microphone location during the hearing aid operation, which are used to verify the overall accuracy of the numerical model. Finally, a sensitivity analysis is performed, indicating some design options that can be used to minimize the structural feedback problem in hearing aids.

Improved prediction error filters for adaptive feedback cancellation in hearing aids

Acoustic feedback is a well-known problem in hearing aids, caused by the undesired acoustic coupling between the hearing aid loudspeaker and microphone. Acoustic feedback produces annoying howling sounds and limits the maximum achievable hearing aid amplification. This paper is focused on adaptive feedback cancellation (AFC) where the goal is to adaptively model the acoustic feedback path and estimate the feedback signal, which is then subtracted from the microphone signal. The main problem in identifying the acoustic feedback path model is the correlation between the near-end signal and the loudspeaker signal caused by the closed signal loop, in particular when the near-end signal is spectrally colored as is the case for a speech signal. This paper adopts a prediction-error method (PEM)-based approach to AFC, which is based on the use of decorrelating prediction error filters (PEFs). We propose a number of improved PEF designs that are inspired by harmonic sinusoidal modeling and pitch prediction of speech signals. The resulting PEM-based AFC algorithms are evaluated in terms of the maximum stable gain (MSG), filter misadjustment, and computational complexity. Simulation results for a hearing aid scenario indicate an improvement up to 5–7dB in MSG and up to 6–8dB in terms of filter misadjustment.

Steady-state analysis of continuous adaptation in acoustic feedback reduction systems for hearing-aids

Acoustic feedback is a problem in hearing aids that contain a substantial amount of gain, hearing aids that are used in conjunction with vented or open molds, and in-the-ear hearing aids. Acoustic feedback is both annoying and reduces the maximum usable gain of hearing-aid devices. This paper studies analytically the steady-state convergence behavior of LMS-based adaptive algorithms when used in continuous adaptation to reduce acoustic feedback. A bias is found in the adaptive filter's estimate of the hearing-aid acoustic feedback path. Methods for reducing this bias and producing an improved estimate of the acoustic feedback path are analyzed and compared. It is shown that by the use of a delay in the forward or cancellation paths of the hearing aid plant, and for representative feedback paths, it is possible to reduce this bias by more than 15 dB.

Feedback path variability modeling for robust hearing aids.

Acoustic feedback is a common problem in hearing aids with vented earmolds. Hearing aids designed to work under normal conditions become unstable when the feedback path varies under changing conditions. A comprehensive study of the variability of the feedback path under various conditions and for different users is presented in this paper. A multiplicative uncertainty bound widely used in H-infinity robust control is suggested to model the variations, which is then used to formulate a robust stability condition for the hearing aid. The upper limit of the closed-loop acoustic gain of the hearing aid for maintaining robust stability is also derived. Examples of robust constant amplification hearing aids, which maintain stability in the face of the given variations in the feedback path, are presented. The robust stability condition is also suggested as a tool to design more robust digital, hearing aids.

An investigation into sound attenuation by earmould tubing.

A major problem in high-gain post-aural hearing aids is acoustic feedback. One of the sources of feedback is the plastic tubing that guides the sound from the hearing aid hook to the ear canal. The objectives of this study were to determine the effects of increases in tubing wall thickness on the amount of acoustic feedback in the hearing aid system and to characterize earmould tubing. Five different samples of Tygon tubing were tested, of which four had different wall thicknesses; the study also compared Tygon tubing with medical grade PVC tubing. Measurement of the wall thickness, taken from scanning electron micrographs, showed that the wall thickness differed from the National Association of Earmould Laboratories standard by less than 6% and was well within the manufacturer's tolerances. Measurement of sound attenuation showed that an increase in the tubing wall thickness of 0.330 mm (Tygon 13 Standard to Tygon 13 Double Wall) caused an increase in sound attenuation of 2 dB, across the frequency range measured (0.5-4 kHz). It was also found that the medical grade PVC had a 5 dB greater sound attenuation than the equivalent Tygon tubing. While these differences are quite small, they could contribute to a reduction in acoustic feedback when used in conjunction with other hearing aid or earmould improvements.