Today, medical technology manufacturers enter the service market through the development of digital service innovations. In the field of audiology, these developments increasingly shift the service capacities from audiologists to manufacturers and technical systems. However, the technology-driven developments of manufacturers lack acceptance of hearing device users and undermine the important role of audiologists within the service provision. By following a user-centered design approach in order to deal with the technological and social challenges of disruptive services, we aim to develop service innovations on an integrated service platform in the field of tele-audiology. To ensure the acceptance of technology-driven service innovations among hearing device users and audiologists, we systematically integrated these actors in a participatory innovation process. With qualitative and quantitative data we identified several requirements and preferences for different service innovations in the field of tele-audiology. According to the preferences of the different actors, we proposed a service platform approach based on a connected hearing device in three pillars of application: 1) one-to-one (1:1) service innovations based on a remote fitting concept directly improve the availability of services offered by audiologists without being physically present. Based on this, 2) one-to-many (1:N) service innovations allow the use of the connected hearing device as an indirect data source for training a machine learning algorithm that empowers users through the automation of service processes. A centralized server system collects the data and performs the training of this algorithm. The optimized algorithm is provided to the connected hearing devices to perform automatic acoustic scene classification. This in turn allows optimization of the hearing devices within each acoustic scene. After the user-centered development of the different service innovations which are designed to converge on an integrated service platform, we experimentally evaluated the functionality and applicability of the system as well as the associated role models between the technical system, the hearing device users and audiologists. As a future outlook, we show potentials to use the connected hearing device for 3) cross-industry (N:M) service innovations in contexts outside the healthcare domain and give practical implications for the market launch of successful service innovations in the field of tele-audiology.
Hearing impairment is associated with a decrease in speech intelligibility and health-related quality of life, such as social isolation and participation restriction. However, little is known about the extent to which hearing impairment and hearing aid fittings change behavior in acute communication situations as well as interrelated behavior patterns. Based on a pilot study, in which the basis for annotating communication behavior was laid, group discussions in noise were initiated with 10 participants using three different hearing-aid brands. The proposed offline annotation scheme revealed that different hearing aids were associated with changes in behavior patterns. These behavioral changes were congruent with speech recognition threshold results and also with subjective assessments. Some of the results were interpreted in terms of participation restriction and activity limitation following the framework of the International Classification of Functioning, Disability and Health. In addition to the offline annotation scheme, a procedure for instantaneous coding of eight behavior patterns was iteratively developed and used for the quick examination of lab studies with good to excellent interrater reliability values.
An adaptive procedure for controlling the signal-to-noise ratio (SNR) when rating the subjectively perceived listening effort (Adaptive Categorical Listening Effort Scaling) is described. For this, the listening effort is rated on a categorical scale with 14 steps after the presentation of three sentences in a background masker. In a first phase of the procedure, the individual SNR range for ratings from “no effort” to “extreme effort” is estimated. In the following phases, stimuli with randomly selected SNRs within this range are presented. One or two linear regression lines are fitted to the data describing subjective listening effort as a function of SNR. The results of the adaptive procedure are independent of the initial SNR. Although a static procedure using fixed, predefined SNRs produced similar results, the adaptive procedure avoided lengthy pretests for suitable SNRs and limited possible bias in the rating procedures. The adaptive procedure resolves individual differences, as well as differences between maskers. Inter-individual standard deviations are about three times as large as intra-individual standard deviations and the intra-class correlation coefficient for test-retest reliability is, on average, 0.9.
To assess perception with and performance of modern and future hearing devices with advanced adaptive signal processing capabilities, novel evaluation methods are required that go beyond already established methods. These novel methods will simulate to a certain extent the complexity and variability of acoustic conditions and acoustic communication styles in real life. This article discusses the current state and the perspectives of virtual reality technology use in the lab for designing complex audiovisual communication environments for hearing assessment and hearing device design and evaluation. In an effort to increase the ecological validity of lab experiments, that is, to increase the degree to which lab data reflect real-life hearing-related function, and to support the development of improved hearing-related procedures and interventions, this virtual reality lab marks a transition from conventional (audio-only) lab experiments to the field. The first part of the article introduces and discusses the notion of the communication loop as a theoretical basis for understanding the factors that are relevant for acoustic communication in real life. From this, requirements are derived that allow an assessment of the extent to which a virtual reality lab reflects these factors, and which may be used as a proxy for ecological validity. The most important factor of real-life communication identified is a closed communication loop among the actively behaving participants. The second part of the article gives an overview of the current developments towards a virtual reality lab at Oldenburg University that aims at interactive and reproducible testing of subjects with and without hearing devices in challenging communication conditions. The extent to which the virtual reality lab in its current state meets the requirements defined in the first part is discussed, along with its limitations and potential further developments. Finally, data are presented from a qualitative study that compared subject behavior and performance in two audiovisual environments presented in the virtual reality lab—a street and a cafeteria—with the corresponding field environments. The results show similarities and differences in subject behavior and performance between the lab and the field, indicating that the virtual reality lab in its current state marks a step towards more ecological validity in lab-based hearing and hearing device research, but requires further development towards higher levels of ecological validity.
Speech audiometry in noise based on sentence tests is an important diagnostic tool to assess listeners’ speech recognition threshold (SRT), i.e., the signal-to-noise ratio corresponding to 50% intelligibility. The clinical standard measurement procedure requires a professional experimenter to record and evaluate the response (expert-conducted speech audiometry). The use of automatic speech recognition enables self-conducted measurements with an easy-to-use speech-based interface. This article compares self-conducted SRT measurements using smart speakers with expert-conducted laboratory measurements. With smart speakers, there is no control over the absolute presentation level, potential errors from the automated response logging, and room acoustics. We investigate the differences between highly controlled measurements in the laboratory and smart speaker-based tests for young normal-hearing (NH) listeners as well as for elderly NH, mildly and moderately hearing-impaired listeners in low, medium, and highly reverberant room acoustics. For the smart speaker setup, we observe an overall bias in the SRT result that depends on the hearing loss. The bias ranges from +0.7 dB for elderly moderately hearing-impaired listeners to +2.2 dB for young NH listeners. The intrasubject standard deviation is close to the clinical standard deviation (0.57/0.69 dB for the young/elderly NH compared with 0.5 dB observed for clinical tests and 0.93/1.09 dB for the mild/moderate hearing-impaired listeners compared with 0.9 dB). For detecting a clinically elevated SRT, the speech-based test achieves an area under the curve value of 0.95 and therefore seems promising for complementing clinical measurements.
Speech audiometry in noise based on matrix sentence tests is an important diagnostic tool to assess the speech reception threshold (SRT) of a subject, i.e., the signal-to-noise ratio corresponding to 50% intelligibility. Although the matrix test format allows for self-conducted measurements by applying a visual, closed response format, these tests are mostly performed in open response format with an experimenter entering the correct/incorrect responses (expert-conducted). Using automatic speech recognition (ASR) enables self- conducted measurements without the need of visual presentation of the response alternatives. A combination of these self-conducted measurement procedures with signal presentation via smart speakers could be used to assess individual speech intelligibility in an individual listening environ- ment. Therefore, this paper compares self-conducted SRT measurements using smart speakers with expert-conducted lab measurements. With smart speakers, the experimenter has no control over the absolute presentation level, mode of presentation (headphones vs. loudspeaker), potential errors from the automated response logging, and room acoustics. We present the differences between measurements in the lab and with a smart speaker for normal- hearing, mildly hearing-impaired and moderate hearing-impaired subjects in low, medium, and high reverberation.
Numerous studies showed that different hearing aid (HA) algorithms improve speech intelligibility in typical lab situations as measures of clinical efficacy. From the perspective of auditory ecology, it remains obscure to what extent these results really allow for estimating the outcome in listening situations in real life. One promising tool is the observation of participants behaviour induced by different HA settings. We developed an annotation system for coding the behaviour related to the framework of the International Classification of Functioning, Disability and Health (ICF) in iterative steps. The first inputs were derived from a series of lab studies, using virtual acoustics. It was shown that different directional modes of HAs influenced real life behaviour. First indications of activity limitation according to ICF (d3504 ‘Conversing with many people’) were found. Additionally, the behaviour of users in real life was described by means of ‘ethnographical walks’ outside of the laboratory using field notes. We identified further behaviour patterns addressing spatial awareness. The conversation related ICF sub-categories were validated by analyses of inter-rater reliability (IRR). The outcome of these analyses led to a reformulation of an annotation/coding system for the usage on tablet PCs for instantaneous coding of the test persons behaviour in real life.
Listening to speech in noisy environments is challenging and effortful. Factors like the signal-to-noise ratio (SNR), the spatial separation between target speech and noise interferer(s), and possibly also the listener's age might influence perceived listening effort (LE). This study measured and modeled the effect of the spatial separation of target speech and interfering stationary speech-shaped noise on the perceived LE and its relation to the age of the listeners. Reference ranges for the relationship between subjectively perceived LE and SNR for different noise azimuths were established. For this purpose, 70 listeners with normal hearing and from three age groups rated the perceived LE using the Adaptive Categorical Listening Effort Scaling method (ACALES, Krueger et al., 2017a) with speech from the front and noise from 0°, 90°, 135°, or 180° azimuth. Based on these data, the spatial release from listening effort (SRLE) was calculated. The noise azimuth had a strong effect on SRLE, with the highest release for 135°. The binaural speech intelligibility model (BSIM2020, Hauth et al., 2020) predicted SRLE very well at negative SNRs, but overestimated for positive SNRs. No significant effect of age was found on the respective subjective ratings. Therefore, the reference ranges were determined independently of age. These reference ranges can be used for the classification of LE measurements. However, when the increase of the perceived LE with SNR was analyzed, a significant age difference was found between the listeners of the youngest and oldest group when considering the upper range of the LE function.
Subjective ratings of listening effort might be applicable to estimate hearing difficulties at positive signal-to-noise ratios (SNRs) at which speech intelligibility scores are near 100%. Hence, ratings of listening effort were compared with speech intelligibility scores at different SNRs, and the benefit of hearing aids was evaluated.Two groups of listeners, 1 with normal hearing and 1 with hearing impairment, performed adaptive speech intelligibility and adaptive listening effort tests (Adaptive Categorical Listening Effort Scaling; Krueger, Schulte, Brand, & Holube, 2017) with sentences of the Oldenburg Sentence Test (Wagener, Brand, & Kollmeier, 1999a, 1999b; Wagener, Kühnel, & Kollmeier, 1999) in 4 different maskers. Model functions were fitted to the data to estimate the speech reception threshold and listening effort ratings for extreme effort and no effort.Listeners with hearing impairment showed higher rated listening effort compared with listeners with normal hearing. For listeners with hearing impairment, the rating extreme effort, which corresponds to negative SNRs, was more correlated to the speech reception threshold than the rating no effort, which corresponds to positive SNRs. A benefit of hearing aids on speech intelligibility was only verifiable at negative SNRs, whereas the effect on listening effort showed high individual differences mainly at positive SNRs.The adaptive procedure for rating subjective listening effort yields information beyond using speech intelligibility to estimate hearing difficulties and to evaluate hearing aids.
