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Abstract Background When performing magnetic resonance imaging (MRI) in patients with a cochlear implant (CI), complication rates vary widely in the literature. The primary objective of this retrospective study was to determine the prevalence of complications, in particular magnet dislocation, in patients with CI undergoing 1.5 Tesla (T) MRI. As a secondary objective, the prevalence of magnet dislocation for specific cochlear implant device types was elaborated. Methods In a single-center retrospective study, all patients with a cochlear implant presenting for an MRI examination at 1.5 T at our institution between January 1st, 2010 and December 31st, 2020 were included. Implants with axial and diametrical magnets were included in the study. MRI safety measures were applied before imaging. The prevalence of complications was evaluated. Magnet dislocation rates were calculated for device types with at least 20 MRI exposures. Results During the study period, 196 MRI examinations were performed in a total of 128 patients, accounting for 149 different implants (21 implanted bilaterally) with a total of 231 implant exposures to MRI (average 1.69 ± 1.57; min. 1, max. 12). Complications were reported in 50 out of 231 cochlear implant exposures (21.6%). Magnet dislocation occurred in a total of 27 cases (11.7%). Dislocation rates were 29.6% for the Cochlear® CI500 series (24 dislocations from 81 exposures), 1.1% for the Cochlear® CI24RE series (1 from 87) and 0% for the MED-EL® Synchrony (0 from 36). The dislocation rate for the CI500 was significantly higher than for the CI24RE (χ2 (1) = 26.86; p

IntroductionResidual hearing in cochlear implant (CI) candidates requires the functional integrity of the nerve in particular regions of the cochlea. Nerve activity can be elicited as electrically evoked compound action potentials (ECAP) after cochlear implantation. We hypothesize that ECAP thresholds depend on preoperative residual hearing ability.Materials and methodsIn a retrospective study, we analyzed 84 adult cochlear implant users who had received a Nucleus® CI632 Slim Modiolar Electrode and who preoperatively had had residual hearing. Inclusion criteria were severe to profound hearing loss with preoperative measurable hearing in the ear to receive the implant, postlingual hearing loss, German as native language and correct placement of the electrode, inserted completely into the scala tympani. Electrically evoked compound action potential (ECAP) was recorded intraoperatively. The angular insertion was measured for each electrode contact from postoperative computed tomography to estimate the corresponding spiral ganglion frequency. Pure-tone audiometry and allocated ECAP thresholds were tested to investigate possible correlation.ResultsThe average of hearing thresholds, tested at 0.5, 1, 2, and 4 kHz (4FPTA) was 82 ± 18 (range 47–129) dB HL. The success rate for recording ECAP thresholds was 96.9%. For all comparable pure-tone frequencies (1, 2, 4, and 8 kHz), there was significant correlation between preoperative hearing levels and intraoperative ECAP thresholds (p

Social media have become an integral part of our lives, expanding our interlinking capabilities to new levels. There is plenty to be said about their positive effects. On the other hand, however, some serious negative implications of social media have been repeatedly highlighted in recent years, pointing at various threats to society and its more vulnerable members, such as teenagers, in particular, ranging from much-discussed problems such as digital addiction and polarization to manipulative influences of algorithms and further to more teenager-specific issues (e.g., body stereotyping). The impact of social media—both at an individual and societal level—is characterized by the complex interplay between the users' interactions and the intelligent components of the platform. Thus, users' understanding of social media mechanisms plays a determinant role. We thus propose a theoretical framework based on an adaptive “Social Media Virtual Companion” for educating and supporting an entire community, teenage students, to interact in social media environments in order to achieve desirable conditions, defined in terms of a community-specific and participatory designed measure of Collective Well-Being (CWB). This Companion combines automatic processing with expert intervention and guidance. The virtual Companion will be powered by a Recommender System (CWB-RS) that will optimize a CWB metric instead of engagement or platform profit, which currently largely drives recommender systems thereby disregarding any societal collateral effect. CWB-RS will optimize CWB both in the short term by balancing the level of social media threats the users are exposed to, and in the long term by adopting an Intelligent Tutor System role and enabling adaptive and personalized sequencing of playful learning activities. We put an emphasis on experts and educators in the educationally managed social media community of the Companion. They play five key roles: (a) use the Companion in classroom-based educational activities; (b) guide the definition of the CWB; (c) provide a hierarchical structure of learning strategies, objectives and activities that will support and contain the adaptive sequencing algorithms of the CWB-RS based on hierarchical reinforcement learning; (d) act as moderators of direct conflicts between the members of the community; and, finally, (e) monitor and address ethical and educational issues that are beyond the intelligent agent's competence and control. This framework offers a possible approach to understanding how to design social media systems and embedded educational interventions that favor a more healthy and positive society. Preliminary results on the performance of the Companion's components and studies of the educational and psychological underlying principles are presented.

Hearing loss is one of the most common disorders worldwide. It affects communicative abilities in all age groups. However, it is well known that elderly people suffer more frequently from hearing loss. Two different model approaches were employed: A generalised linear model and a random forest regression model were used to quantify the relationship between pure-tone hearing loss, age, and speech perception. Both models were applied to a large clinical data set of 19,801 ears, covering all degrees of hearing loss. They allow the estimation of age-related decline in speech recognition for different types of audiograms. Our results show that speech scores depend on the specific type of hearing loss and life decade. We found age effects for all degrees of hearing loss. A deterioration in speech recognition of up to 25 percentage points across the whole life span was observed for constant pure-tone thresholds. The largest decrease was 10 percentage points per life decade. This age-related decline in speech recognition cannot be explained by elevated hearing thresholds as measured by pure-tone audiometry.

ObjectiveUnderstanding speech in noisy conditions is challenging even for people with mild hearing loss, and intelligibility for an individual person is usually evaluated by using several subjective test methods. In the last few years, a method has been developed to determine a temporal response function (TRF) between speech envelope and simultaneous electroencephalographic (EEG) measurements. By using this TRF it is possible to predict the EEG signal for any speech signal. Recent studies have suggested that the accuracy of this prediction varies with the level of noise added to the speech signal and can predict objectively the individual speech intelligibility. Here we assess the variations of the TRF itself when it is calculated for measurements with different signal-to-noise ratios and apply these variations to predict speech intelligibility.MethodsFor 18 normal hearing subjects the individual threshold of 50% speech intelligibility was determined by using a speech in noise test. Additionally, subjects listened passively to speech material of the speech in noise test at different signal-to-noise ratios close to individual threshold of 50% speech intelligibility while an EEG was recorded. Afterwards the shape of TRFs for each signal-to-noise ratio and subject were compared with the derived intelligibility.ResultsThe strongest effect of variations in stimulus signal-to-noise ratio on the TRF shape occurred close to 100 ms after the stimulus presentation, and was located in the left central scalp region. The investigated variations in TRF morphology showed a strong correlation with speech intelligibility, and we were able to predict the individual threshold of 50% speech intelligibility with a mean deviation of less then 1.5 dB.ConclusionThe intelligibility of speech in noise can be predicted by analyzing the shape of the TRF derived from different stimulus signal-to-noise ratios. Because TRFs are interpretable, in a manner similar to auditory evoked potentials, this method offers new options for clinical diagnostics.

Hearing loss is associated with decreased speech perception as well as with changes in the auditory pathway. The effects of those changes on binaural speech perception with hearing aids are not yet fully understood. To provide further evidence on the functional changes of the auditory pathway, several speech perception tests (unilateral and bilateral, aided and unaided, in quiet, and in noise) were conducted in a population of 370 bilateral hearing aid users covering the entire range of the World Health Organization’s most recent classification of hearing loss. To characterize the effects of asymmetric hearing thresholds, a generalized linear model was used for regression analysis. The model revealed a detrimental effect of the poorer ears’ thresholds on both the unaided and the aided unilateral word recognition scores that were attained by the better ear. Moreover, aided binaural word recognition (in quiet and in noise) was affected to a degree that cannot be explained on the sole basis of bilateral summation. Thus, this study provides evidence that there is reorganization and altered functioning of the afferent and efferent auditory pathways due to asymmetric hearing loss. Consequently, more attention should be paid to provision with a hearing aid as early as possible, and separately for each ear.

Human brain performs remarkably well in segregating a particular speaker from interfering ones in a multispeaker scenario. We can quantitatively evaluate the segregation capability by modeling a relationship between the speech signals present in an auditory scene, and the listener's cortical signals measured using electroencephalography (EEG). This has opened up avenues to integrate neuro-feedback into hearing aids where the device can infer user's attention and enhance the attended speaker. Commonly used algorithms to infer the auditory attention are based on linear systems theory where cues such as speech envelopes are mapped on to the EEG signals. Here, we present a joint convolutional neural network (CNN)—long short-term memory (LSTM) model to infer the auditory attention. Our joint CNN-LSTM model takes the EEG signals and the spectrogram of the multiple speakers as inputs and classifies the attention to one of the speakers. We evaluated the reliability of our network using three different datasets comprising of 61 subjects, where each subject undertook a dual-speaker experiment. The three datasets analyzed corresponded to speech stimuli presented in three different languages namely German, Danish, and Dutch. Using the proposed joint CNN-LSTM model, we obtained a median decoding accuracy of 77.2% at a trial duration of 3 s. Furthermore, we evaluated the amount of sparsity that the model can tolerate by means of magnitude pruning and found a tolerance of up to 50% sparsity without substantial loss of decoding accuracy.

Abstract The glycerol test is an easy‐to‐use instrument to elucidate fluctuations of electrical hearing in patients with Meniere's disease and it might be also used as a therapeutic option.

Social media usage has become a daily habit for the younger generation. It can have positive effects on educational processes, but it also raises concerns about harmful content, such as fake news or hate speech. Fake news is often distributed with the intention to manipulate the public opinion by propagating disinformation. This includes the manipulation of images taken from reputable news resources. In response to these concerns and manipulations, we developed a web-based learning environment with a virtual learning companion (VLC). The VLC is designed to assist students in developing their critical thinking skills while interacting with social media content. The VLC is incorporated into a controlled learning environment that resembles Instagram and contains real and manipulated content. The "Courage" companion communicates with the students through chat dialogue and knowledge-activating questions. It also links additional images from web sources discovered through reverse image search based on image similarity. Learners are provided with various textual descriptions and keywords and are prompted to reflect on this information. The system's effectiveness and assistance in identifying real or manipulated images have been evaluated in an empirical classroom study in August 2022 with 22 high school students in Germany that generated 95 conversations around five images and their texts assisted by the companion. Users' interactions with the companion in a controlled Instagram-like social media environment have been recorded in xAPI format and then analyzed using a research dashboard. The results of this evaluation demonstrate that guidance through the VLC, along with the provision of additional content sources containing similar images and their explanation through the companion, improves the learners' judgment. This corroborates the claim that the tool can help enhance learners' critical thinking, resilience, and sensitivity facing social media issues.

This study presents numerical and experimental models for the analysis of the excavation of soft soils by means of a cutting tool. The computational model is constructed using an Updated Lagrangean (UL) velocity-based Finite Element approach. A hypoplastic formulation is employed to describe the constitutive behavior of soft soils. Large displacements and deformations of the ground resulting from the cutting tool-soil interaction are handled by means of the Particle Finite Element method, characterized by a global re-meshing strategy and a boundary identification procedure called α-shape technique. The capabilities and performance of the proposed model are demonstrated through comparative analyses between experiments and simulations of cutting tool-soft soil interactions. The experiments are performed using an excavation device at Ruhr-Universität Bochum (RUB), Germany. The main details concerning the setup and calibration and evolution of the measured draft forces are discussed. Selected computational results characterizing the cutting tool-soft soil interaction including the topology of the free surface, void ratio distribution ahead of the tool, spatio-temporal evolution of the reaction forces and abrasive wear behavior are evaluated. Keywords: Velocity-based finite elements formulation, Hypoplasticity, Large deformations, Particle finite elements, Cutting tool-soil interaction, Excavation experiments

29.03.2017 | Wolfgang Greller & Ulrich Hoppe

The aim of this survey was to gather data from both implant recipients and professionals on the ease of use of the Naída CI Q70 (Naída CI) sound processor from Advanced Bionics and on the usefulness of the new functions and features available. A secondary objective was to investigate fitting practices with the new processor. A comprehensive user satisfaction survey was conducted in a total of 186 subjects from 24 centres. In parallel, 23 professional questionnaires were collected from 11 centres. Overall, there was high satisfaction with the Naída CI processor from adults, children, experienced and new CI users as well as from professionals. The Naída CI processor was shown as being easy to use by all ages of recipients and by professionals. The majority of experienced CI users rated the Naída CI processor as being similar or better than their previous processor in all areas surveyed. The Naída CI was recommended by the professionals for fitting in all populations. Features like UltraZoom, ZoomControl and DuoPhone would not be fitted to very young children in contrast to adults. Positive ratings were obtained for ease of use, comfort and usefulness of the new functions and features of the Naída CI sound processor. Seventy-seven percent of the experienced CI users rated the new processor as being better than their previous sound processor from a general point of view. The survey also showed that fitting practices were influenced by the age of the user.

This paper presents a feature-list cross-correlation algorithm based on: a common feature extraction algorithm, a transformation of the results into a feature-list representation form, and a list-based cross-correlation algorithm. The feature-list cross-correlation algorithms are compared with known results of the common cross-correlation algorithms. Therefore, simple test images containing different objects under changing image conditions and with several image distortions are used. In addition, a medical application is used to verify the results. The results are analyzed by means of curve progression of coefficients and curve progression of peak signal-to-noise ratio (PSNR). As a result, the presented feature list cross-correlation algorithms are sensitive to all changes of image conditions. Therefore, it is possible to separate objects that are similar but not equal. Because of the high quantity of feature points and the strong PSNR, the loss of a few feature points does not have a significant influence on the detection results. These results are confirmed by a successfully applied medical application. The calculation time of the feature list cross-correlation algorithms only depends on the length of the feature-lists. The amount of feature points is much less than the number of pixels in the image. Therefore, the feature-list cross-correlation algorithms are faster than common cross-correlation algorithms. Better image conditions tend to reduce the size of the feature-list. Hence, the processing time decreases considerably.

Commentary on: Chapter5: An Architecture for Learning Design Engines. (Vogten, Koper, Martens and Tattersall, 2005) Abstract: Chapter 5 of the Learning Design book describes the operational model of a learning design engine based on the concept of finite automata with output alphabet. We rely on this event concept to include pre-existing learning tools in flexibe and rich learning designs. We sketch an approach for the integration of complex learning environments in learning designs. Interactive learning support environments, such as argumentation or modelling tools are pre-existent and have a high potential when integrated in learning designs. We propose an approach that aims at a clear separation of the learning design engine, the specification of the learning flow (as LD documents) and learning environments. According to its current state, the engine controls the learning environment with events (such as "start a new phase"), defined as a vocabulary for a set of environments, that are mapped to the environments' existing functionality (such as "create new workspace"). Thus the engine remotely controls the learning tools while the tools can initiate state transitions in the engine on specific events in the tool. Editors: Colin Tattersall and Rob Koper.

Under the notion of "CSCL scripts", different pedagogical models for structuring and supporting collaboration in the classroom have been proposed. We report on a practical experience with scripts based on the Pyramid collaborative learning flow pattern supported by a specific classroom tool and a teacher-facing dashboard that implements mirroring and guiding support. The input data of our analysis stems from recordings of classroom interactions guided by several teachers using the PyramidApp with different levels of teaching support. For the analysis, we introduce a specific coding scheme enabling a quantitative comparison and deeper analysis using epistemic network analysis. The results show that the guiding support enabled teachers to perform more orchestration actions, more targeted interactions and to make more announcements to the class (regarding time, phase transitions, and students' activity participation) when compared to the mirroring support. Teachers' actionable differences observed under the mirroring and guiding support directed us to deconstruct the notion of orchestration load into different facets and to discuss how different support provisions correspond to the different facets of orchestration load.