Hearing rehabilitation of adults with auditory processing disorder: a systematic review and meta-analysis of current evidence-based interventions.

Background: For adults with auditory processing disorder (APD), listening and communicating can be difficult, potentially leading to social isolation, depression, employment difficulties and certainly reducing the quality of life. Despite existing practice guidelines suggesting treatments, the efficacy of these interventions remains uncertain due to a lack of comprehensive reviews. This systematic review and meta-analysis aim to establish current evidence on the effectiveness of interventions for APD in adults, addressing the urgent need for clarity in the field. Methods: Following the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines, we conducted a systematic search across MEDLINE (Ovid), Embase (Ovid), Web of Science and Scopus, focusing on intervention studies involving adults with APD. Studies that met the inclusion criteria were grouped according to intervention with a meta-analysis only conducted where intervention, study design and outcome measure were comparable. Results: Out of 1,618 screened records, 13 studies were included, covering auditory training (AT), low-gain hearing aids (LGHA), and personal remote microphone systems (PRMS). Our analysis revealed: AT, Mixed results with some improvements in speech intelligibility and listening ability, indicating potential benefits but highlighting the need for standardized protocols; LGHA, The included studies demonstrated significant improvements in monaural low redundancy speech testing (p < 0.05), suggesting LGHA could enhance speech perception in noisy environments. However, limitations include small sample sizes and potential biases in study design. PRMS, Demonstrated the most consistent evidence of benefit, significantly improving speech testing results, with no additional benefit from combining PRMS with other interventions. Discussion: PRMS presents the most evidence-supported intervention for adults with APD, although further high-quality research is crucial for all intervention types. The establishment and implementation of standardized intervention protocols alongside rigorously validated outcome measures will enable a more evidence-based approach to managing APD in adults.

Features for Evaluating Source Localization Effectiveness in Sound Maps from Acoustic Cameras.

Acoustic cameras (ACs) have become very popular in the last decade as an increasing number of applications in environmental acoustics are observed, which are mainly used to display the points of greatest noise emission of one or more sound sources. The results obtained are not yet certifiable because the beamforming algorithms or hardware behave differently under different measurement conditions, but at present, not enough studies have been dedicated to clarify the issues. The present study aims to provide a methodology to extract analytical features from sound maps obtained with ACs, which are generally only visual information. Based on the inputs obtained through a specific measurement campaign carried out with an AC and a known sound source in free field conditions, the present work elaborated a methodology for gathering the coordinates of the maximum emission point on screen, its distance from the real position of the source and the uncertainty associated with this position. The results obtained with the proposed method can be compared, thus acting as a basis for future comparison studies among calculations made with different beamforming algorithms or data gathered with different ACs in all real case scenarios. The method can be applicable to any other sector interested in gathering data from intensity maps not related to sound.

Piezoelectric Micromachined Microphone with High Acoustic Overload Point and with Electrically Controlled Sensitivity.

Currently, the most advanced micromachined microphones on the market are based on a capacitive coupling principle. Capacitive micro-electromechanical-system-based (MEMS) microphones resemble their millimetric counterparts, both in function and in performance. The most advanced MEMS microphones reached a competitive level compared to commonly used measuring microphones in most of the key performance parameters except the acoustic overload point (AOP). In an effort to find a solution for the measurement of high-level acoustic fields, microphones with the piezoelectric coupling principle have been proposed. These novel microphones exploit the piezoelectric effect of a thin layer of aluminum nitride, which is incorporated in their diaphragm structure. In these microphones fabricated with micromachining technology, no fixed electrode is necessary, in contrast to capacitive microphones. This specificity significantly simplifies both the design and the fabrication and opens the door for the improvement of the acoustic overload point, as well as harsh environmental applications. Several variations of piezoelectric structures together with an idea leading to electrically controlled sensitivity of MEMS piezoelectric microphones are discussed in this paper.

Quartz Enhanced Photoacoustic Spectroscopy on Solid Samples.

Quartz-Enhanced Photoacoustic Spectroscopy (QEPAS) is a technique in which the sound wave is detected by a quartz tuning fork (QTF). It enables particularly high specificity with respect to the excitation frequency and is well known for an extraordinarily sensitive analysis of gaseous samples. We have developed the first photoacoustic (PA) cell for QEPAS on solid samples. Periodic heating of the sample is excited by modulated light from an interband cascade laser (ICL) in the infrared region. The cell represents a half-open cylinder that exhibits an acoustical resonance frequency equal to that of the QTF and, therefore, additionally amplifies the PA signal. The antinode of the sound pressure of the first longitudinal overtone can be accessed by the sound detector. A 3D finite element (FE) simulation confirms the optimal dimensions of the new cylindrical cell with the given QTF resonance frequency. An experimental verification is performed with an ultrasound micro-electromechanical system (MEMS) microphone. The presented frequency-dependent QEPAS measurement exhibits a low noise signal with a high-quality factor. The QEPAS-based investigation of three different solid synthetics resulted in a linearly dependent signal with respect to the absorption.

Differential photoacoustic spectroscopy for flow gas detection based on single microphone.

Differential photoacoustic spectroscopy (PAS) for flow gas detection based on single microphone is innovatively proposed and experimentally demonstrated. Unlike the traditional systems, only one microphone is used to suppress flowing gas noise. Wavelength modulation spectroscopy and second harmonic detection technique are applied in this PAS system with Q-point demodulation for acetylene (C2H2) gas detection. The experiment is conducted at 1 atm and 300 K. Different concentrations and flow rates of C2H2 from 0 sccm to 225 sccm are detected by using nitrogen (N2) as the carrier gas, which indicates that the system can respond well to flowing gases while maintaining the noise at the same level. The system response time decreases to 3.58 s while the gas velocity is 225 sccm. The detection limit of 43.97 ppb with 1 s integration time and normalized noise equivalent absorption (NNEA) coefficient of 4.0 × 10-9 cm-1 W Hz-1/2 is achieved at the flow rate of 225 sccm. The firstly proposed differential PAS based on single microphone greatly simplifies the system structure for flow gas detection, which provides a novel route for development of PAS with significant practical implementation prospects.

Chapter 1: Introduction and Getting Ready for Hearing Aid Test Box Measures.

In this chapter you will be introduced to the hearing aid test box equipment and work through how to prepare the equipment so that it is ready to provide the testing you will use to evaluate, fit, and troubleshoot hearing aids and other amplifiers. At the end of this chapter, you will be familiar with terminology associated with hearing aid test box measures and the leveling required with the reference microphone and coupler microphone to ensure that your measurements are accurate and can be interpreted.

Chapter 5: Setting the Hearing Aid Response and Verifying Signal Processing and Features with Real-Ear Probe Microphone Measures.

The real-ear probe microphone system provides a powerful tool to individual hearing aid fittings accounting for your patient's hearing and ear canal characteristics. The primary treatment for hearing loss is audibility, returning an audible signal across frequencies and input levels given the constraints of the hearing loss. This chapter will provide detailed information on the measures needed to individualize the hearing aid fitting and will present various clinical scenarios that will allow you to work with this information and see how you apply this knowledge clinically. You will explore the verification of signal processing and features that allow you to support your patients.

Chapter 4: Introduction and Getting Ready for Real-Ear Probe Microphone Measures.

Probe microphone measurements are an essential step in an individualized hearing aid fitting. These measurements allow audiologists to account for the individual's hearing and ear canal acoustics when programming hearing aids. An evidence-based hearing aid fitting includes matching the measured output of the hearing aids to targets for each input level and frequency. This allows the audiologist to confidently counsel the patient that the acoustic fitting is accurate, and the next step is for the individual to use the amplification during all waking hours to adapt to the newly amplified sounds. This also avoids mistakes such as overamplification or insufficient gain, which can endanger the patient and/or lead to a compromised fitting.

callsync: An R package for alignment and analysis of multi-microphone animal recordings.

To better understand how vocalisations are used during interactions of multiple individuals, studies are increasingly deploying on-board devices with a microphone on each animal. The resulting recordings are extremely challenging to analyse, since microphone clocks drift non-linearly and record the vocalisations of non-focal individuals as well as noise. Here we address this issue with callsync, an R package designed to align recordings, detect and assign vocalisations to the caller, trace the fundamental frequency, filter out noise and perform basic analysis on the resulting clips. We present a case study where the pipeline is used on a dataset of six captive cockatiels (Nymphicus hollandicus) wearing backpack microphones. Recordings initially had a drift of ~2 min, but were aligned to within ~2 s with our package. Using callsync, we detected and assigned 2101 calls across three multi-hour recording sessions. Two had loud beep markers in the background designed to help the manual alignment process. One contained no obvious markers, in order to demonstrate that markers were not necessary to obtain optimal alignment. We then used a function that traces the fundamental frequency and applied spectrographic cross correlation to show a possible analytical pipeline where vocal similarity is visually assessed. The callsync package can be used to go from raw recordings to a clean dataset of features. The package is designed to be modular and allows users to replace functions as they wish. We also discuss the challenges that might be faced in each step and how the available literature can provide alternatives for each step.

Evaluating benefits of remote microphone technology for adults with hearing loss using behavioural and predictive metrics.

OBJECTIVE: To investigate the benefit of remote-microphone (RM) systems for adults with sensory hearing loss. DESIGN: Speech recognition in quiet and in background noise was assessed. Participants with hearing loss underwent testing in two device conditions: hearing aids (HAs) alone and HAs with a RM. Normal hearing participants completed testing in the unaided condition. Predictive speech intelligibility modelling using the Hearing-Aid Speech Perception Index (HASPI) was also performed on recordings of HA processed test material. STUDY SAMPLE: Twenty adults with sensory hearing loss and 10 adults with normal hearing participated. RESULTS: Speech recognition for participants with hearing loss improved significantly when using the RM compared to HAs alone fit to Phonak's proprietary prescription. Largest benefits were observed in the most challenging conditions. At the lowest signal-to-noise ratio, participants with hearing loss using a RM outperformed normal hearing listeners. Predicted intelligibility scores produced by HASPI were strongly correlated to behavioural results. CONCLUSIONS: Adults using HAs who have significant difficulties understanding speech in noise will experience considerable benefits with the addition of a RM. Improvements in speech recognition were observed for all participants using RM systems, including those with relatively mild hearing loss. HASPI modelling reliably predicted the speech perception difficulties experienced.

Recurrence plot embeddings as short segment nonlinear features for multimodal speaker identification using air, bone and throat microphones.

Speech is produced by a nonlinear, dynamical Vocal Tract (VT) system, and is transmitted through multiple (air, bone and skin conduction) modes, as captured by the air, bone and throat microphones respectively. Speaker specific characteristics that capture this nonlinearity are rarely used as stand-alone features for speaker modeling, and at best have been used in tandem with well known linear spectral features to produce tangible results. This paper proposes Recurrent Plot (RP) embeddings as stand-alone, non-linear speaker-discriminating features. Two datasets, the continuous multimodal TIMIT speech corpus and the consonant-vowel unimodal syllable dataset, are used in this study for conducting closed-set speaker identification experiments. Experiments with unimodal speaker recognition systems show that RP embeddings capture the nonlinear dynamics of the VT system which are unique to every speaker, in all the modes of speech. The Air (A), Bone (B) and Throat (T) microphone systems, trained purely on RP embeddings perform with an accuracy of 95.81%, 98.18% and 99.74%, respectively. Experiments using the joint feature space of combined RP embeddings for bimodal (A-T, A-B, B-T) and trimodal (A-B-T) systems show that the best trimodal system (99.84% accuracy) performs on par with trimodal systems using spectrogram (99.45%) and MFCC (99.98%). The 98.84% performance of the B-T bimodal system shows the efficacy of a speaker recognition system based entirely on alternate (bone and throat) speech, in the absence of the standard (air) speech. The results underscore the significance of the RP embedding, as a nonlinear feature representation of the dynamical VT system that can act independently for speaker recognition. It is envisaged that speech recognition too will benefit from this nonlinear feature.

Low cost MEMS accelerometer and microphone based condition monitoring sensor, with LoRa and Bluetooth Low Energy radio.

Vibration-based Condition Monitoring (CM) is an essential tool for identifying potential defects in industrial machinery. However, the implementation of an efficient CM system often necessitates the use of high-cost accelerometers with a large bandwidth. To address this challenge, this study introduces a low-cost CM sensor composed of an ultrasonic MEMS microphone - SPH0641LU and an ADXL1002 MEMS accelerometer. The combination of these two sensor types allows for comparative analysis of the captured data. The SPH641LU microphone is capable of detecting audible vibration signals with a frequency range up to 80 kHz, while the ADXL1002 accelerometer can measure vibrations up to 21 kHz. In addition a three axis ultra low power accelerometer is included, allowing measurement of unbalance or rotating speed, below 200Hz. Moreover, the sensor is designed to operate on battery power and provides the capability for raw data transmission via Bluetooth Low Energy (BLE) or the transmission of pre-processed features from the raw data using LoRaWAN.

Remediation of Perceptual Deficits in Progressive Auditory Neuropathy: A Case Study.

BACKGROUND: Auditory neuropathy (AN) is a hearing disorder that affects neural activity in the VIIIth cranial nerve and central auditory pathways. Progressive forms have been reported in a number of neurodegenerative diseases and may occur as a result of both the deafferentiation and desynchronisation of neuronal processes. The purpose of this study was to describe changes in auditory function over time in a patient with axonal neuropathy and to explore the effect of auditory intervention. METHODS: We tracked auditory function in a child with progressive AN associated with Charcot-Marie-Tooth (Type 2C) disease, evaluating hearing levels, auditory-evoked potentials, and perceptual abilities over a 3-year period. Furthermore, we explored the effect of auditory intervention on everyday listening and neuroplastic development. RESULTS: While sound detection thresholds remained constant throughout, both electrophysiologic and behavioural evidence suggested auditory neural degeneration over the course of the study. Auditory brainstem response amplitudes were reduced, and perception of auditory timing cues worsened over time. Functional hearing ability (speech perception in noise) also deteriorated through the first 1.5 years of study until the child was fitted with a "remote-microphone" listening device, which subsequently improved binaural processing and restored speech perception ability to normal levels. CONCLUSIONS: Despite the deterioration of auditory neural function consistent with peripheral axonopathy, sustained experience with the remote-microphone listening system appeared to produce neuroplastic changes, which improved the patient's everyday listening ability-even when not wearing the device.

Optimal Microphone Array Placement Design Using the Bayesian Optimization Method.

In addition to the filter coefficients, the location of the microphone array is a crucial factor in improving the overall performance of a beamformer. The optimal microphone array placement can considerably enhance speech quality. However, the optimization problem with microphone configuration variables is non-convex and highly non-linear. Heuristic algorithms that are frequently employed take a long time and have a chance of missing the optimal microphone array placement design. We extend the Bayesian optimization method to solve the microphone array configuration design problem. The proposed Bayesian optimization method does not depend on gradient and Hessian approximations and makes use of all the information available from prior evaluations. Furthermore, Gaussian process regression and acquisition functions make up the Bayesian optimization method. The objective function is given a prior probabilistic model through Gaussian process regression, which exploits this model while integrating out uncertainty. The acquisition function is adopted to decide the next placement point based upon the incumbent optimum with the posterior distribution. Numerical experiments have demonstrated that the Bayesian optimization method could find a similar or better microphone array placement compared with the hybrid descent method and computational time is significantly reduced. Our proposed method is at least four times faster than the hybrid descent method to find the optimal microphone array configuration from the numerical results.

A Feedback Active Control Approach to Road Noise Based on a Single Microphone Sensor to Improve Automotive Cabin Sound Comfort.

Tire-road noise deteriorates the sound quality of a vehicle's interior and affects the driving safety and comfort. Obtaining low interior noise is a challenge for passenger car manufacturers. Traditional passive noise control (PNC) is efficient for canceling high frequency noise but not useful for low frequency noise, while active noise control (ANC), according to the residual error signal, can generate an anti-noise signal to reduce the original noise. Most research has focused on improving the control effect for a feedforward ANC system. However, this paper emphasizes a feedback ANC system based on a signal microphone sensor. There are two main contributions in this study to improve automotive cabin sound comfort. One is that the algorithm of the feedback ANC system using a single microphone sensor without a reference noise signal is proposed based on the Filtered-x Least Mean Square method. The other is that the algorithm applies additive random noise online to estimate the secondary path model. A simulation was implemented based on measured real road noise data, and the simulation results indicate that the proposed feedback ANC system with the single microphone sensor can effectively attenuate road noise. This study shows the feasibility of applying a feedback ANC system in automobiles to increase the cabin sound quality.

Objective verification of audibility in bone conduction devices.

OBJECTIVE: To objectively measure audibility in patients wearing bone conduction devices (BCDs) with a new approach using a skin microphone at the patient's forehead. DESIGN: The skin microphone was attached by a softband and shielded by an earmuff. This set-up was confirmed not to be influenced by neither noise floor nor sound bypassing the BCD. Sound field warble tones were used for measuring aided hearing thresholds and maximum power output (MPO) whereas an international speech test signal (ISTS) was presented at different speech levels. STUDY SAMPLE: 29 patients were tested (two were bilateral), 19 used percutaneous, eight used active transcutaneous and two used passive transcutaneous devices. RESULTS: The skin microphone responses at ISTS levels, hearing threshold and MPO, could be obtained in all patients. Two patients with poor audibility are highlighted in this article as examples. After adjusting the gain of the BCD, they were retested with the skin microphone (for verification) and with speech-in-noise tests (for validation). Both tests confirmed an improved audibility after the adjustments. CONCLUSION: In summary, the proposed measurement of audibility of speech using a skin microphone is a promising method that can be used in a clinical setting for all types of BCDs.

Micro-Electro-Mechanical Systems Microphones: A Brief Review Emphasizing Recent Advances in Audible Spectrum Applications.

The MEMS microphone is a representative device among the MEMS family, which has attracted substantial research interest, and those tailored for human voice have earned distinct success in commercialization. Although sustained development persists, challenges such as residual stress, environmental noise, and structural innovation are posed. To collect and summarize the recent advances in this subject, this paper presents a concise review concerning the transduction mechanism, diverse mechanical structure topologies, and effective methods of noise reduction for high-performance MEMS microphones with a dynamic range akin to the audible spectrum, aiming to provide a comprehensive and adequate analysis of this scope.

SonicGuard Sensor-A Multichannel Acoustic Sensor for Long-Term Monitoring of Abdominal Sounds Examined through a Qualification Study.

Auscultation is a fundamental diagnostic technique that provides valuable diagnostic information about different parts of the body. With the increasing prevalence of digital stethoscopes and telehealth applications, there is a growing trend towards digitizing the capture of bodily sounds, thereby enabling subsequent analysis using machine learning algorithms. This study introduces the SonicGuard sensor, which is a multichannel acoustic sensor designed for long-term recordings of bodily sounds. We conducted a series of qualification tests, with a specific focus on bowel sounds ranging from controlled experimental environments to phantom measurements and real patient recordings. These tests demonstrate the effectiveness of the proposed sensor setup. The results show that the SonicGuard sensor is comparable to commercially available digital stethoscopes, which are considered the gold standard in the field. This development opens up possibilities for collecting and analyzing bodily sound datasets using machine learning techniques in the future.

An Accelerometer-Based Wearable Patch for Robust Respiratory Rate and Wheeze Detection Using Deep Learning.

Wheezing is a critical indicator of various respiratory conditions, including asthma and chronic obstructive pulmonary disease (COPD). Current diagnosis relies on subjective lung auscultation by physicians. Enabling this capability via a low-profile, objective wearable device for remote patient monitoring (RPM) could offer pre-emptive, accurate respiratory data to patients. With this goal as our aim, we used a low-profile accelerometer-based wearable system that utilizes deep learning to objectively detect wheezing along with respiration rate using a single sensor. The miniature patch consists of a sensitive wideband MEMS accelerometer and low-noise CMOS interface electronics on a small board, which was then placed on nine conventional lung auscultation sites on the patient's chest walls to capture the pulmonary-induced vibrations (PIVs). A deep learning model was developed and compared with a deterministic time-frequency method to objectively detect wheezing in the PIV signals using data captured from 52 diverse patients with respiratory diseases. The wearable accelerometer patch, paired with the deep learning model, demonstrated high fidelity in capturing and detecting respiratory wheezes and patterns across diverse and pertinent settings. It achieved accuracy, sensitivity, and specificity of 95%, 96%, and 93%, respectively, with an AUC of 0.99 on the test set-outperforming the deterministic time-frequency approach. Furthermore, the accelerometer patch outperforms the digital stethoscopes in sound analysis while offering immunity to ambient sounds, which not only enhances data quality and performance for computational wheeze detection by a significant margin but also provides a robust sensor solution that can quantify respiration patterns simultaneously.

Plant ultrasound detection: a cost-effective method for identifying plant ultrasonic emissions.

Plants have been observed to produce short ultrasonic emissions (UEs), and current research is focusing on developing noninvasive techniques for recording and analyzing these emissions. A standardized methodology has not been established yet; in this paper we suggest a cost-effective procedure for recording, extracting, and identifying plant UEs using only a single ultrasound microphone, a laptop computer, and open-source software.