Search Results (38)

Background/Objectives: Access to specialized care for patients with cognitive impairment in remote areas is often limited. Despite the increasing adoption of telemedicine, standardized guidelines have not yet been specified. This study aimed to develop a comprehensive protocol for the specialized neurological, neuropsychological, and neuropsychiatric assessment of patients with cognitive disorders in remote areas through telemedicine. Methods: We analyzed data from (i) a comprehensive literature review of the existing recommendations, reliability studies, and telemedicine models for cognitive disorders, (ii) insights from a three-year experience of a specialized telemedicine outpatient clinic for cognitive movement disorders in Greece, and (iii) suggestions coming from dementia specialists experienced in telemedicine (neurologists, neuropsychologists, psychiatrists) who took part in three focus groups. A critical synthesis of the findings was performed in the end. Results: The final protocol included: technical and organizational requirements (e.g., a high-resolution screen and a camera with zoom, room dimensions adequate for gait assessment, a noise-canceling microphone); medical history; neurological, neuropsychiatric, and neuropsychological assessment adapted to videoconferencing; ethical–legal aspects (e.g., data security, privacy, informed consent); clinician–patient interaction (e.g., empathy, eye contact); diagnostic work-up; linkage to other services (e.g., tele-psychoeducation, caregiver support); and instructions for treatment and follow-up. Conclusions: This protocol is expected to serve as an example of good clinical practice and a source for official telemedicine guidelines for cognitive disorders. Ultimate outcomes include the potential enhanced access to specialized care, minimized financial and logistical costs, and the provision of a standardized, effective model for the remote diagnosis, treatment, and follow-up. This model could be applied not only in Greece, but also in other countries with similar healthcare systems and populations living in remote, difficult-to-access areas. Full article

Effective health management during the transition period depends on early disease detection, which can be achieved through continuous monitoring using precision livestock farming tools. This study assessed reticulorumen temperature, rumination time, and activity in dairy cows during the periparturient period under summer heat stress. We hypothesized differences in these parameters between healthy (HE) cows and those developing postpartum disorders (DI). Forty clinically healthy, multiparous cows were monitored from 5 days prepartum to 14 days after calving (days in milk; DIM). A cow was considered healthy and allocated to the HE group (n = 26) if she was not affected by any postpartum health disorders until the end of the study period. A cow was considered diseased and allocated to the DI group (n = 14) if she had been diagnosed with mastitis, metritis, lameness, or ketosis. Weather loggers recorded barn microclimate data, while rumination, activity, and rumen temperature were tracked using a microphone-based sensor in the neck collar (Ruminact HR) and rumen bolus (Smaxtec). THI values remained above 68 throughout the study, peaking at 80, indicating sustained heat stress. Rumen temperature ranged between 39 and 41 °C and moderately correlated with THI (correlation coefficient was 0.27; 95% CI: 0.20; 0.33; p < 0.0001). Both groups exhibited a nadir in rumen temperature at calving, with no differences. Rumination time declined prepartum, reaching its lowest at 2 DIM in DI cows. It was significantly affected by days around calving, postpartum disorders, and THI. Activity increased prepartum and normalized by 4 DIM in HE cows, while DI cows showed higher activity at 4 DIM, stabilizing by 5–7 DIM. These findings underscore the value of precision monitoring tools for early disease detection and intervention. Full article

The adoption of kiosks in public spaces is steadily increasing, with a trend toward providing more natural user experiences through embodied conversational agents (ECAs). To achieve human-like interactions, ECAs should be able to appropriately gaze at the speaker. However, kiosks in public spaces often face challenges, such as ambient noise and overlapping speech from multiple people, making it difficult to accurately identify the speaker and direct the ECA’s gaze accordingly. In this paper, we propose a lightweight gaze control system that is designed to operate effectively within the resource constraints of kiosks and the noisy conditions common in public spaces. We first developed a speaker detection model that identifies the active speaker in challenging noise conditions using only a single camera and microphone. The proposed model achieved a 91.6% mean Average Precision (mAP) in active speaker detection and a 0.6% improvement over the state-of-the-art lightweight model (Light ASD) (as evaluated on the noise-augmented AVA-Speaker Detection dataset), while maintaining real-time performance. Building on this, we developed a gaze control system for ECAs that detects the dominant speaker in a group and directs the ECA’s gaze toward them using an algorithm inspired by real human turn-taking behavior. To evaluate the system’s performance, we conducted a user study with 30 participants, comparing the system to a baseline condition (i.e., a fixed forward gaze) and a human-controlled gaze. The results showed statistically significant improvements in social/co-presence and gaze naturalness compared to the baseline, with no significant difference between the system and human-controlled gazes. This suggests that our system achieves a level of social presence and gaze naturalness comparable to a human-controlled gaze. The participants’ feedback, which indicated no clear distinction between human- and model-controlled conditions, further supports the effectiveness of our approach. Full article

If we can understand dialogue activities, it will be possible to know the role of each person in the discussion, and it will be possible to provide basic materials for formulating facilitation strategies. This understanding can be expected to be used for business negotiations, group work, active learning, etc. To develop a system that can monitor speech activity over a wide range of areas, we propose a method for detecting multiple acoustic events and localizing sound sources using an asynchronous distributed microphone array arranged in a regular hexagonal repeating structure. In contrast to conventional methods based on sound source direction using triangulation with microphone arrays, we propose a method for detecting acoustic events and determining sound sources from local maximum positions based on estimation of the spatial energy distribution inside the observation space. We evaluated the conventional method and the proposed method in an experimental environment in which a dialogue between two people was simulated under 22,104 conditions by using the sound source signal convolving the measured impulse response.We found that the performance changes depending on the selection of the microphone array used for estimation. Our finding is that it is best to choose five microphone arrays close to the evaluation position. Full article

Background/Objectives: Autism spectrum disorder (ASD) is a lifelong neurodevelopmental condition characterised by impairments in social communication, sensory abnormalities, and attentional deficits. Children with ASD often face significant challenges with speech perception and auditory attention, particularly in noisy environments. This study aimed to assess the effectiveness of noise cancelling Bluetooth earbuds (Nuheara IQbuds Boost) in improving speech perception and auditory attention in children with ASD. Methods: Thirteen children aged 6–13 years diagnosed with ASD participated. Pure tone audiometry confirmed normal hearing levels. Speech perception in noise was measured using the Consonant-Nucleus–Consonant-Word test, and auditory/visual attention was evaluated via the Integrated Visual and Auditory Continuous Performance Task. Participants completed these assessments both with and without the IQbuds in situ. A two-week device trial evaluated classroom listening and communication improvements using the Listening Inventory for Education-Revised (teacher version) questionnaire. Results: Speech perception in noise was significantly poorer for the ASD group compared to typically developing peers and did not change with the IQbuds. Auditory attention, however, significantly improved when the children were using the earbuds. Additionally, classroom listening and communication improved significantly after the two-week device trial. Conclusions: While the noise cancelling earbuds did not enhance speech perception in noise for children with ASD, they significantly improved auditory attention and classroom listening behaviours. These findings suggest that Bluetooth earbuds could be a viable alternative to remote microphone systems for enhancing auditory attention in children with ASD, offering benefits in classroom settings and potentially minimising the stigma associated with traditional assistive listening devices. Full article

Purpose: The purpose of this study was to evaluate the efficacy of auditory training (AT) in patients with unilateral hearing loss (UHL) using hearing aids (HAs), comparing traditional methods with a new approach involving a wireless remote microphone. Methods: The study included 96 participants, divided into two groups, with ages ranging from 42 to 64 years, comprising both male and female subjects. A clinical trial including consecutive moderate UHL patients was performed at our institution. For the study group, a Roger Pen was used during AT with patients inside a sound-attenuating cabin. Controls followed conventional sessions. Professional speech and language pathologists performed the rehabilitation. Audiological outcomes were measured, including word recognition at signal-to-noise ratios (SNRs) of 0 dB, +5 dB, and +10 dB, to determine the effectiveness of the training. Measurements also included the Speech, Spatial, and Qualities of Hearing Scale to assess perceived auditory abilities. Results: A total of 46 and 50 UHL patients were randomly included in the study and control groups, respectively. No differences were found in terms of sex, age, presence of tinnitus, duration of hearing loss, pure tone average, and speech-in-noise perception without an HA. Following HA fitting and AT, a notable enhancement in the ability to identify speech in noisy environments was observed in the study group. This improvement was significant at SNRs of +5 and +10. When comparing the ability to identify speech in noise using HAs across both groups, it was observed that hearing capabilities post-wireless AT showed a significant improvement at an SNR of +5. Only the study group had a significant improvement in the total Speech, Spatial, and Qualities of Hearing Scale score after the training. Conclusions: In our group of UHL patients, we found significantly better speech-in-noise perception when HA fitting was followed by wireless AT. Wireless AT may facilitate usage of HAs, leading to binaural hearing in UHL patients. Our findings suggest that future interventions might benefit from incorporating wireless technology in AT programs. Full article

In this paper, we propose a method for estimating the classes and directions of static audio objects using stereo microphones in a drone environment. Drones are being increasingly used across various fields, with the integration of sensors such as cameras and microphones, broadening their scope of application. Therefore, we suggest a method that attaches stereo microphones to drones for the detection and direction estimation of specific emergency monitoring. Specifically, the proposed neural network is configured to estimate fixed-size audio predictions and employs bipartite matching loss for comparison with actual audio objects. To train the proposed network structure, we built an audio dataset related to speech and drones in an outdoor environment. The proposed technique for identifying and localizing sound events, based on the bipartite matching loss we proposed, works better than those of the other teams in our group. Full article

Postpartum support for new parents can normalize experiences, increase confidence, and lead to positive health outcomes. While in-person gatherings may be the preferred choice, not all parents can or want to join parenting groups in person. Online asynchronous chat spaces for parents have increased over the past 10 years, especially during the COVID pandemic, when “online” became the norm. However, synchronous postpartum support groups have not been as accessible. The purpose of our study was to examine how parents experienced postpartum videoconferencing support sessions. Seven one-hour videoconferencing sessions were conducted with 4–8 parents in each group (n = 37). Nineteen parents from these groups then participated in semi-structured interviews. Feminist poststructuralism and sociomaterialism were used to guide the research process and analysis. Parents used their agency to actively think about and interact using visual (camera) and audio (microphone) technologies to navigate socially constructed online discourses. Although videoconferencing fostered supportive connections and parents felt less alone and more confident, the participants also expressed a lack of opportunities for individual conversations. Nurses should be aware of the emerging opportunities that connecting online may present. This study was not registered. Full article

Breathiness (perception of turbulence noise in the voice) is one of the major components of hoarseness in dysphonic voices. This study aims to validate a multiparameter analysis tool, the Acoustic Breathiness Index (ABI), for quantification of breathiness in the speaking voice, including both sustained vowels and continuous speech. One hundred and eight speakers with dysphonia (28 M, 80 F, mean age 50, SD 15.4 years) and 87 non-dysphonic controls (18 M, 69 F, mean age 42, SD 14 years) volunteered as participants. They read a standard text and sustained vowel /a:/. Acoustic recordings were made using a head-mounted microphone. Acoustic samples were evaluated perceptually by nine voice experts of different backgrounds (speech therapists, vocologists and laryngologists). Breathiness (B) from the GRBAS scale was rated. Headphones were used in the perceptual analysis. The dysphonic and non-dysphonic speakers differed significantly from each other in the auditory perceptual evaluation of breathiness. A significant difference was also found for ABI, which had a mean value of 2.26 (SD 1.15) for non-dysphonic and 3.07 (SD 1.75) for dysphonic speakers. ABI correlated strongly with B (r_s = 0.823, p = 0.01). ABI’s power to distinguish the groups was high (88.6%). The highest sensitivity and specificity of ABI (80%) was obtained at threshold value 2.68. ABI is a valid tool for differentiating breathiness in non-dysphonic and dysphonic speakers of Finnish. Full article

Congenital unilateral hearing loss (UHL) represents a contemporary audiologic challenge. Children with UHL can struggle with understanding speech in noise, localizing sounds, developing language, and maintaining academic performance, leading to low self-esteem, anxiety, and decreased social support. Two specific conditions related to UHL in children are single-sided deafness (SSD) and unilateral auris atresia (UAA). This was a retrospective observational study on a group of children with UHL. The Simplified Italian Matrix Sentence Test was used for the assessment of speech reception threshold (SRT) in different conditions: speech and noise from the front (S0N0), speech at 45° from the side of the better ear and noise at 45° from the opposite side (SbNw), and vice versa (SwNb). Each test was conducted unaided, with a bone-anchored hearing device (BAHD), and with a remote microphone (RM) system. The use of a BAHD and RM led to an improvement in SRT in S0N0 and SwNb conditions. The SSD subgroup demonstrated significant benefits with both devices in SwNb, and the UAA subgroup from the use of BAHD in S0N0. In conclusion, the study underscores the potential benefits of both devices in enhancing speech perception for UHL children, providing insights into effective intervention strategies for these challenging cases. Full article

Despite the evolution of hearing aids and cochlear implants, noisy environments are reportedly still an important hurdle for persons with hearing loss, especially in the process of speech recognition. The development of pre-processing algorithms and the pairing with a wireless device can bring relief to this situation, but it is still under scrutiny whether one or the other is more effective. The purpose of this study was to compare the benefits of speech recognition in a noisy environment by recipients of cochlear implants when using the pre-processing automatic algorithms or when using a wireless microphone. Twenty-nine participants were selected, aged 14 to 83, suffering from sensorineural hearing loss and recipients of cochlear implants for at least 6 months. The proprietary Cochlear Limited SCAN technology uses pre-processing algorithms to attenuate various noises; the wireless device MiniMic2 uses a 2.4 GHz connection to facilitate communications between the recipient and the signal source. Participants were asked to repeat 20 sentences randomly generated by the adaptive Italian Matrix Sentence Test, first while using the SCAN technology and then with the wireless MiniMic2. Both signal and noise were administered through a single loudspeaker set 1 m away from the subject. Significantly better results in speech recognition of noise were achieved with the wireless MiniMic2 when compared to the SCAN technology. Full article

Acoustic dyadic sensors (ADSs) are a new type of acoustic sensor with higher directivity than microphones and acoustic vector sensors, which has great application potential in the fields of sound source localization and noise cancellation. However, the high directivity of an ADS is seriously affected by the mismatches between its sensitive units. In this article, (1) a theoretical model of mixed mismatches was established based on the finite-difference approximation model of uniaxial acoustic particle velocity gradient and its ability to reflect the actual mismatches was proven by the comparison of theoretical and experimental directivity beam patterns of an actual ADS based on MEMS thermal particle velocity sensors. (2) Additionally, a quantitative analysis method based on directivity beam pattern was proposed to easily estimate the specific magnitude of the mismatches, which was proven to be useful for the design of ADSs to estimate the magnitudes of different mismatches of an actual ADS. (3) Moreover, a correction algorithm based on the theoretical model of mixed mismatches and quantitative analysis method was successfully demonstrated to correct several groups of simulated and measured beam patterns with mixed mismatches. Full article

The aim of the study was to develop a universal-platform-based (UPB) application suitable for different smartphones for estimation of the Acoustic Voice Quality Index (AVQI) and evaluate its reliability in AVQI measurements and normal and pathological voice differentiation. Our study group consisted of 135 adult individuals, including 49 with normal voices and 86 patients with pathological voices. The developed UPB “Voice Screen” application installed on five iOS and Android smartphones was used for AVQI estimation. The AVQI measures calculated from voice recordings obtained from a reference studio microphone were compared with AVQI results obtained using smartphones. The diagnostic accuracy of differentiating normal and pathological voices was evaluated by applying receiver-operating characteristics. One-way ANOVA analysis did not detect statistically significant differences between mean AVQI scores revealed using a studio microphone and different smartphones (F = 0.759; p = 0.58). Almost perfect direct linear correlations (r = 0.991–0.987) were observed between the AVQI results obtained with a studio microphone and different smartphones. An acceptable level of precision of the AVQI in discriminating between normal and pathological voices was yielded, with areas under the curve (AUC) displaying 0.834–0.862. There were no statistically significant differences between the AUCs (p > 0.05) obtained from studio and smartphones’ microphones. The significant difference revealed between the AUCs was only 0.028. The UPB “Voice Screen” application represented an accurate and robust tool for voice quality measurements and normal vs. pathological voice screening purposes, demonstrating the potential to be used by patients and clinicians for voice assessment, employing both iOS and Android smartphones. Full article

In mechanical cutting and machining, self-excited vibration known as “Chatter” often occurs, adversely affecting a product’s quality and tool life. This article proposes a method to identify chatter by applying a machine learning model to classify data, determining whether the machining process is stable or vibrational. Previously, research studies have used detailed surface image data and sound generated during the machining process. To increase the specificity of the research data, we constructed a two-input model that enables the inclusion of both acoustic and visual data into the model. Data for training, testing, and calibration were collected from machining flanges SS400 in the form of thin steel sheets, using electron microscopes for imaging and microphones for sound recording. The study also compares the accuracy of the two-input model with popular models such as a visual geometry group network (VGG16), residual network (Restnet50), dense convolutional network (DenseNet), and Inception network (InceptionNet). The results show that the DenseNet model has the highest accuracy of 98.8%, while the two-input model has a 98% higher accuracy than other models; however, the two-input model is more appreciated due to the generality of the input data of the model. Experimental results show that the recommended model has good results in this work. Full article

Voice communication using an air-conduction microphone in noisy environments suffers from the degradation of speech audibility. Bone-conduction microphones (BCM) are robust against ambient noises but suffer from limited effective bandwidth due to their sensing mechanism. Although existing audio super-resolution algorithms can recover the high-frequency loss to achieve high-fidelity audio, they require considerably more computational resources than is available in low-power hearable devices. This paper proposes the first-ever real-time on-chip speech audio super-resolution system for BCM. To accomplish this, we built and compared a series of lightweight audio super-resolution deep-learning models. Among all these models, ATS-UNet was the most cost-efficient because the proposed novel Audio Temporal Shift Module (ATSM) reduces the network’s dimensionality while maintaining sufficient temporal features from speech audio. Then, we quantized and deployed the ATS-UNet to low-end ARM micro-controller units for a real-time embedded prototype. The evaluation results show that our system achieved real-time inference speed on Cortex-M7 and higher quality compared with the baseline audio super-resolution method. Finally, we conducted a user study with ten experts and ten amateur listeners to evaluate our method’s effectiveness to human ears. Both groups perceived a significantly higher speech quality with our method when compared to the solutions with the original BCM or air-conduction microphone with cutting-edge noise-reduction algorithms. Full article