Search Results (27)

Humans may have evolved to be “hyperactive agency detectors”. Upon hearing a rustle in a pile of leaves, it would be safer to assume that an agent, like a lion, hides beneath (even if there may ultimately be nothing there). Can this evolutionary cognitive mechanism—and related mechanisms of anthropomorphism—explain some of people’s contemporary experience with using chatbots (e.g., ChatGPT, Gemini)? In this paper, we sketch how such mechanisms may engender the seemingly irresistible anthropomorphism of large language-based chatbots. We then explore the implications of this within the educational context. Specifically, we argue that people’s tendency to perceive a “mind in the machine” is a double-edged sword for educational progress: Though anthropomorphism can facilitate motivation and learning, it may also lead students to trust—and potentially over-trust—content generated by chatbots. To be sure, students do seem to recognize that LLM-generated content may, at times, be inaccurate. We argue, however, that the rise of anthropomorphism towards chatbots will only serve to further camouflage these inaccuracies. We close by considering how research can turn towards aiding students in becoming digitally literate—avoiding the pitfalls caused by perceiving agency and humanlike mental states in chatbots. Full article

In the current landscape of hearing rehabilitation, ear mold manufacturing typically involves the injection of silicone into the external ear canal (EEC) of each patient. This invasive procedure poses several risks, including the potential for silicone residue retention and tympanic membrane perforation, which may necessitate surgical intervention. To mitigate these risks, we present the design of a video otoscope that integrates a scanner capable of capturing high-precision, real-time images of the EEC’s geometry. The developed device allows (i) the generation of a 3D CAD model leading to the direct, quick, and low-cost production of customized hearing aids using 3D printing and (ii) the establishment of medical protocols for carrying out diagnoses and monitoring of hearing pathology evolution using methodologies based on Artificial Intelligence. Furthermore, the use of customized hearing aids that allow the application of Rhythmic Auditory Stimulation (RAS) and music therapy enhances audiology as an alternative and innovative way to treat cognitive and degenerative diseases, as well as pathological disorders. Full article

Introduction: Acceptable Noise Level (ANL) is defined as the most comfortable level (MCL) intensity for speech and is calculated by subtracting the maximum noise tolerable by an individual. The ANL test has been used over time to predict hearing aid use and the impact of digital noise reduction. This study analyzes this impact by using different masker babble spectra when performing the ANL test in both hearing-impaired and healthy subjects in three different languages (Dutch, French, and Italian). Materials and Methods: A total of 198 patients underwent the ANL test in their native language using a standardized protocol. The babble file was speech-weighted to match the long-term spectrum of the specific ANL language version. ANL was proposed in three different masking conditions: with multitalker Matched babble speech noise, with the same masking signal with the spectrum reduced from 2 kHz onwards (High Cut), and with the spectrum increased from 2 kHz onwards (High Boost). Results: In all of the comparisons among the three languages, ANL with High Boost noise gave significantly higher (worse) scores than ANL with Matched noise (p-value S1: <0.0001, S2: <0.0001, S3: 0.0003) and ANL with High Cut noise (p-value S1: 0.0002, S2: <0.0001, S3: <0.0001). The ANL values did not show any significant correlation with age and gender. In French, a weak correlation was found between ANL with High Cut noise and the Fletcher index of the worst ear. In Italian, a weak correlation was found between both ANL with Matched and High Boost noise and the Fletcher index of the best ear. Conclusions: ANL with High Boost added to noise stimuli was less acceptable for all patients in all of the languages. The ANL results did not vary in relation to the patients’ characteristics. This study confirms that the ANL test has potential application for clinical use regardless of the native language spoken. Full article

There are few studies on the representation of older people regarding aids and assistive devices and even fewer that incorporate more inclusive views (gender, emotions, anti-ageist, territorial or land approach) as well as virtual or land ethnography or artificial intelligence. The general objective was to evaluate digital images of aids and assistive aids in the older population, from the perspectives mentioned above. Method. A descriptive and cross-sectional study that searched, observed and analyzed images. An evaluation of intentionally selected images from Freepik, Pixabay, Storyblocks, Splitshire, Gratisography and ArtGPT, included in an original database constructured by several authors of this article, was carried out in the context of the ENCAGEn-CM project (2020–2023, financed by the CAM and FSE). This base was updated and expanded in October and November 2023. In addition, an image generation process was carried out using artificial intelligence, and this was also part of the analysis (ArtGPT). Finally, algorithms were used to solve and retrain with the images. Results. Of the total final images included in the expanded database until November 2023 (n = 427), only a third (28.3%, 121/427) included the aids and assistive aids label. Representations of mixed groups predominated (38.8%) and, to a lesser extent, those of women. A large proportion of the devices were ‘glasses’ (74.6%) and the ‘use of a cane’ (14.9%). To a lesser extent, ‘wheelchairs’ (4.4%) or ‘hearing aids’ (0.9%) and the presence of more than one device (simultaneously) (5.3%) were noted. The main emotions represented were ‘joy’ (45.6%) and ‘emotion not recognized’ (45.6%), with, to a lesser extent, ‘sadness’ (3.5%), ‘surprise’ (4.4%) and ‘anger’ (0.9%). Differences by sex were found in the represented emotions linked to aids and assistive aids. The representation of images of the built environment predominated significantly (70.2%), and it was observed that older women were less represented in natural environments than men. Based on the previous findings, a method is proposed to address stereotypes in images of older individuals. It involves identifying common stereotypical features, like glasses and hospital settings, using deep learning and quantum computing techniques. A convolutional neural network identifies and suppresses these elements, followed by the use of quantum algorithms to manipulate features. This systematic approach aims to mitigate biases and enhance the accuracy in representing older people in digital imagery. Conclusion. A limited proportion of images of assistive devices and older people were observed. Furthermore, among them, the lower representation of images of women in a built environment was confirmed, and the expressions of emotions were limited to only three basic ones (joy, sadness and surprise). In these evaluated digital images, the collective imagination of older people continues to be limited to a few spaces/contexts and emotions and is stereotyped regarding the same variables (sex, age, environment). Technology often overlooks innovative support tools for older adults, and AI struggles in accurately depicting emotions and environments in digital images. There is a pressing need for thorough pretraining analysis and ethical considerations to address these challenges and ensure more accurate and inclusive representations of older persons in digital media. Full article

The aim of this study was to examine the relationship between an American English Digits in Noise (DIN) test and commonly used audiological measures to evaluate the DIN test’s ability to detect hearing loss and validate hearing aid fitting. QuickSIN and DIN tests were completed by participants with untreated hearing loss (n = 46), prescription hearing aids (n = 15), and over-the-counter (OTC) hearing aids (n = 12). Performance on the QuickSIN showed moderate positive correlations with DIN for untreated hearing loss participants and prescription hearing aid users, but not for OTC hearing aid users. For untreated hearing loss participants, both QuickSIN and DIN tests showed positive moderate to strong correlations with high frequency puretone averages. In OTC users, DIN scores did not significantly change over a 6-month time period and were better when conducted remotely compared to in-person testing. Our results suggest that the DIN test may be a feasible monitoring option for individuals with hearing loss and those fitted with hearing aids. However, due to small sample size in this pilot study, future research is needed to examine DIN test’s utility for fitting and validating OTC hearing aids. Full article

Background: the word recognition score (WRS) achieved with cochlear implants (CIs) varies widely. To account for this, a predictive model was developed based on patients’ age and their pre-operative WRS. This retrospective study aimed to find out whether the insertion depth of the nucleus lateral-wall electrode arrays contributes to the deviation of the CI-achieved WRS from the predicted WRS. Materials and methods: patients with a pre-operative maximum WRS > 0 or a pure-tone audiogram ≥80 dB were included. The insertion depth was determined via digital volume tomography. Results: fifty-three patients met the inclusion criteria. The median WRS achieved with the CI was 70%. The comparison of pre- and post-operative scores achieved with a hearing aid and a CI respectively in the aided condition showed a median improvement of 65 percentage points (pp). A total of 90% of the patients improved by at least 20 pp. The majority of patients reached or exceeded the prediction, with a median absolute error of 11 pp. No significant correlation was found between the deviation from the predicted WRS and the insertion depth. Conclusions: our data support a previously published model for the prediction of the WRS after cochlear implantation. For the lateral-wall electrode arrays evaluated, the insertion depth did not influence the WRS with a CI. Full article

Communication between Deaf and hearing individuals remains a persistent challenge requiring attention to foster inclusivity. Despite notable efforts in the development of digital solutions for sign language recognition (SLR), several issues persist, such as cross-platform interoperability and strategies for tokenizing signs to enable continuous conversations and coherent sentence construction. To address such issues, this paper proposes a non-invasive Portuguese Sign Language (Língua Gestual Portuguesa or LGP) interpretation system-as-a-service, leveraging skeletal posture sequence inference powered by long-short term memory (LSTM) architectures. To address the scarcity of examples during machine learning (ML) model training, dataset augmentation strategies are explored. Additionally, a buffer-based interaction technique is introduced to facilitate LGP terms tokenization. This technique provides real-time feedback to users, allowing them to gauge the time remaining to complete a sign, which aids in the construction of grammatically coherent sentences based on inferred terms/words. To support human-like conditioning rules for interpretation, a large language model (LLM) service is integrated. Experiments reveal that LSTM-based neural networks, trained with 50 LGP terms and subjected to data augmentation, achieved accuracy levels ranging from 80% to 95.6%. Users unanimously reported a high level of intuition when using the buffer-based interaction strategy for terms/words tokenization. Furthermore, tests with an LLM—specifically ChatGPT—demonstrated promising semantic correlation rates in generated sentences, comparable to expected sentences. Full article

The objective of this work was to develop a temperature sensor system that accurately measures core body temperature from an ear-worn device. Two digital temperature sensors were embedded in a hearing aid shell along the thermal gradient of the ear canal to form a linear heat balance relationship. This relationship was used to determine best fit parameters for estimating body temperature. The predicted body temperatures resulted in intersubject limits of agreement (LOA) of ±0.49 °C over a range of physiologic and ambient temperatures without calibration. The newly developed hearing aid-based temperature sensor system can estimate core body temperature at an accuracy level equal to or better than many devices currently on the market. An accurate, continuously worn, temperature monitoring and tracking device may help provide early detection of illnesses, which could prove especially beneficial during pandemics and in the elderly demographic of hearing aid wearers. Full article

Wearable electroencephalography (EEG) has the potential to improve everyday life through brain–computer interfaces (BCI) for applications such as sleep improvement, adaptive hearing aids, or thought-based digital device control. To make these innovations more practical for everyday use, researchers are looking to miniaturized, concealed EEG systems that can still collect neural activity precisely. For example, researchers are using flexible EEG electrode arrays that can be attached around the ear (cEEGrids) to study neural activations in everyday life situations. However, the use of such concealed EEG approaches is limited by measurement challenges such as reduced signal amplitudes and high recording system costs. In this article, we compare the performance of a lower-cost open-source amplification system, the OpenBCI Cyton+Daisy boards, with a benchmark amplifier, the MBrainTrain Smarting Mobi. Our results show that the OpenBCI system is a viable alternative for concealed EEG research, with highly similar noise performance, but slightly lower timing precision. This system can be a great option for researchers with a smaller budget and can, therefore, contribute significantly to advancing concealed EEG research. Full article

In this paper, an ultra-low-power second-order, single-bit discrete-time (DT) double sampling ΔΣ modulator was proposed for hearing aid applications. In portable biomedical devices that are permanently used such as hearing aids, short battery lifetime and power dissipation are considerable issues. In a typical delta–sigma modulator, the most power-consuming parts are the operational transconductance amplifiers (OTAs), and their elimination without loss of efficiency is now challenging. This proposed modulator includes an ultra-low-power self-biased inverter-based amplifier with swing enhancement instead of power-hungry OTAs. Low voltage amplifier design reduces output swing voltage, affecting delta–sigma modulator efficiency and decreasing the signal-to-noise and distortion ratio (SNDR) and dynamic range (DR) values. In this article, the proposed amplifier’s source and tail transistors were biased in the sub-threshold region, increasing the output swing voltage significantly and leading to desired properties for a hearing aid modulator. The proposed amplifier peak-to-peak swing voltage was approximately 1.01 V at a 1 V power supply. In addition, the proposed modulator design used a standard 180 nm CMOS technology, which obtained 140 dB DR and 93.27 dB SNDR for a 10 kHz signal bandwidth with an oversampling ratio (OSR) of 128. Finally, the modulator’s effective chip area was 0.02 mm² and consumed only about 9.9 µW, while the figure of merit (FOM_W) and FOMs achieved 1.31 fJ/step and 183.31, respectively. Full article

Nowadays, digital printing technologies such as inkjet and aerosol jet printing are gaining more importance since they have proven to be suitable for the assembly of complex microsystems. This also applies to medical technology applications like hearing aids where patient-specific solutions are required. However, assembly is more challenging than with conventional printed circuit boards in terms of material compatibility between substrate, interconnect material and printed ink. This paper describes how aerosol jet printing of nano metal inks and subsequent assembly processes are utilized to connect electrical components on 3D substrates fabricated by Digital Light Processing (DLP). Conventional assembly technologies such as soldering and conductive adhesive bonding were investigated and characterized. For this purpose, curing methods and substrate pretreatments for different inks were optimized. Furthermore, the usage of electroless plating on printed metal tracks for improved solderability was investigated. Finally, a 3D ear mold substrate was used to build up a technology demonstrator by means of conductive adhesives. Full article

Because the hearing impaired often experience different degrees of hearing loss along with the loss of frequencies, the loudness compensation algorithm in hearing aids decomposes the speech signal and compensates with different frequency bands based on their audiograms. However, the speech quality of the compensated signal is unsatisfactory because the traditional filterbanks fail to fully consider the characteristics of human hearing and personalized hearing loss. In this study, an effective design for the gammachirp filterbank for the loudness compensation algorithm was proposed to improve the speech quality of hearing aids. Firstly, a multichannel gammachirp filterbank was employed to decompose the signals. Then, the adjacent bands were merged into one channel, guided by the proposed combination method. After obtaining the personalized filterbank, each band conducted a loudness compensation to match the requirements of the audiograms. The excellent advantage of the gammachirp filterbank is that it can simulate the characteristics of the basilar membrane. Furthermore, the novel channel combination method considers the information from the audiograms and the relationship between frequency ranges and speech intelligibility. The experimental results showed that the proposed multichannel gammachirp filterbank achieves better speech signal decomposition and synthesis, and good performance can be gained with fewer channels. The loudness compensation algorithm based on the gammachirp filterbank effectively improves sentence intelligibility. The sentence recognition rate of the proposed method is higher than that of a system with a gammatone filterbank by approximately 13%. Full article

Hearing aids can be effective devices to compensate for age- or non-age-related hearing losses. Their overall adoption in the affected population is still low, especially in underdeveloped countries in the subpopulation experiencing milder hearing loss. One of the major reasons for low adoption is the need for repeated complex fitting by professional audiologists, which is often not completed for various reasons. As a result, self-fitting procedures have been appearing as an alternative. Key open questions with these digital tools are linked to their effectiveness, utilized algorithms, and achievable end-results. A digital self-fitting prototype tool with a novel quick four-step fitting workflow was evaluated in a study on 19 individuals with moderate hearing loss. The tool was evaluated in a double-blinded, randomized study, having two study aims: comparing traditional audiological fitting with the new self-fitting tool, which can also be used as a remote tool. The main reported results show moderately high usability and user satisfaction obtained during self-fitting, and quasi-equivalence of the performance of the classical audiological fitting approach. The digital self-fitting tool enables multiple sessions and easy re-fitting, with the potential to outperform the classical fitting approach. Full article

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. Full article

Background: The aim of this study was to compare, in users of bimodal cochlear implants, the performance obtained using their own hearing aids (adjusted with the standard NAL-NL1 fitting formula) with the performance using the Phonak Naìda Link Ultra Power hearing aid adjusted with both NAL-NL1 and a new bimodal system (Adaptive Phonak Digital Bimodal (APDB)) developed by Advanced Bionics and Phonak Corporations. Methods: Eleven bimodal users (Naìda CI Q70 + contralateral hearing aid) were enrolled in our study. The users’ own hearing aids were replaced with the Phonak Naìda Link Ultra Power and fitted following the new formula. Speech intelligibility was assessed in quiet and noisy conditions, and comparisons were made with the results obtained with the users’ previous hearing aids and with the Naída Link hearing aids fitted with the NAL-NL1 generic prescription formula. Results: Using Phonak Naìda Link Ultra Power hearing aids with the Adaptive Phonak Digital Bimodal fitting formula, performance was significantly better than that with the users’ own rehabilitation systems, especially in challenging hearing situations for all analyzed subjects. Conclusions: Speech intelligibility tests in quiet settings did not reveal a significant difference in performance between the new fitting formula and NAL-NL1 fittings (using the Naída Link hearing aids), whereas the performance difference between the two fittings was very significant in noisy test conditions. Full article