The adaptation of noise-induced temporary hearing threshold shift predictive models for modelling the public health policy.

Objectives: It has been shown that monitoring temporary threshold shift (TTS) after exposure to noise may have a predictive value for susceptibility of developing permanent noise-induced hearing loss. The aim of this study is to present the assumptions of the TTS predictive model after its verification in normal hearing subjects along with demonstrating the usage of this model for the purposes of public health policy.

Material And Methods: The existing computational predictive TTS models were adapted and validated in a group of 18 bartenders exposed to noise at the workplace.

Investigating the Provision and Context of Use of Hearing Aid Listening Programs From Real-world Data: Observational Study.

Background: Listening programs enable hearing aid (HA) users to change device settings for specific listening situations and thereby personalize their listening experience. However, investigations into real-world use of such listening programs to support clinical decisions and evaluate the success of HA treatment are lacking.

Objective: We aimed to investigate the provision of listening programs among a large group of in-market HA users and the context in which the programs are typically used.

Clustering Users Based on Hearing Aid Use: An Exploratory Analysis of Real-World Data.

While the assessment of hearing aid use has traditionally relied on subjective self-reported measures, smartphone-connected hearing aids enable objective data logging from a large number of users. Objective data logging allows to overcome the inaccuracy of self-reported measures. Moreover, data logging enables assessing hearing aid use with a greater temporal resolution and longitudinally, making it possible to investigate hourly patterns of use and to account for the day-to-day variability.

Public health policy-making for hearing loss: stakeholders' evaluation of a novel eHealth tool.

Background: Hearing loss (HL) affects 466 million people of all ages worldwide, with a rapidly increasing prevalence, and therefore requires appropriate public health policies. Multi-disciplinary approaches that make use of eHealth services can build the evidence to influence public policy. The European Union-funded project EVOTION developed a platform that is fed with real-time data from hearing aids, a smartphone, and additional clinical data and makes public health policy recommendations based on hypothetical public health policy-making models, a big data engine and decision support system.

A Competing Voices Test for Hearing-Impaired Listeners Applied to Spatial Separation and Ideal Time-Frequency Masks.

People with hearing impairment find competing voices scenarios to be challenging, both with respect to switching attention from one talker to the other, as well as maintaining attention. With the Danish competing voices test (CVT) presented here, the dual-attention skills can be assessed. The CVT provides sentences spoken by three male and three female talkers, played in sentence pairs.

Big Data for Sound Policies: Toward Evidence-Informed Hearing Health Policies.

Purpose: The scarcity of health care resources calls for their rational allocation, including within hearing health care. Policies define the course of action to reach specific goals such as optimal hearing health. The process of policy making can be divided into 4 steps: (a) problem identification and issue recognition, (b) policy formulation, (c) policy implementation, and (d) policy evaluation.

Improving competing voices segregation for hearing impaired listeners using a low-latency deep neural network algorithm.

Hearing aid users are challenged in listening situations with noise and especially speech-on-speech situations with two or more competing voices. Specifically, the task of attending to and segregating two competing voices is particularly hard, unlike for normal-hearing listeners, as shown in a small sub-experiment. In the main experiment, the competing voices benefit of a deep neural network (DNN) based stream segregation enhancement algorithm was tested on hearing-impaired listeners.

Clinical validation of a public health policy-making platform for hearing loss (EVOTION): protocol for a big data study.

Introduction: The holistic management of hearing loss (HL) requires an understanding of factors that predict hearing aid (HA) use and benefit beyond the acoustics of listening environments. Although several predictors have been identified, no study has explored the role of audiological, cognitive, behavioural and physiological data nor has any study collected real-time HA data. This study will collect 'big data', including retrospective HA logging data, prospective clinical data and real-time data via smart HAs, a mobile application and biosensors.

Associations Between Hearing Performance and Physiological Measures - An Overview and Outlook.

The current paper summarises the research investigating associations between physiological data and hearing performance. An overview of state-of-the-art research and literature is given as well as promising directions for associations between physiological data and data regarding hearing loss and hearing performance. The physiological parameters included in this paper are: electrodermal activity, heart rate variability, blood pressure, blood oxygenation and respiratory rate.

The effect of tone-vocoding on spatial release from masking for old, hearing-impaired listeners.

Old, hearing-impaired listeners generally benefit little from lateral separation of multiple talkers when listening to one of them. This study aimed to determine how spatial release from masking (SRM) in such listeners is affected when the interaural time differences (ITDs) in the temporal fine structure (TFS) are manipulated by tone-vocoding (TVC) at the ears by a master hearing aid system. Word recall was compared, with and without TVC, when target and masker sentences from a closed set were played simultaneously from the front loudspeaker (co-located) and when the maskers were played 45° to the left and right of the listener (separated).

Perception of a sung vowel as a function of frequency-modulation rate and excursion in listeners with normal hearing and hearing impairment.

Purpose: Frequency fluctuations in human voices can usually be described as coherent frequency modulation (FM). As listeners with hearing impairment (HI listeners) are typically less sensitive to FM than listeners with normal hearing (NH listeners), this study investigated whether hearing loss affects the perception of a sung vowel based on FM cues.

Method: Vibrato maps were obtained in 14 NH and 12 HI listeners with different degrees of musical experience.