Search Results (54)

Emotion recognition by wearable devices is essential for advancing emotion-aware human–computer interaction in real life. Earphones have the potential to naturally capture brain activity and its lateralization, which is associated with emotion. In this study, we newly introduced tympanic membrane temperature (TMT), previously used as an index of lateralized brain activation, for earphone-based emotion recognition. We developed custom earphones to measure bilateral TMT and conducted two experiments consisting of emotion induction by autobiographical recall and scenario imagination. Using features derived from the right–left TMT difference, we trained classifiers for both four-class discrete emotion and valence (positive vs. negative) classification tasks. The classifiers achieved 36.2% and 42.5% accuracy for four-class classification and 72.5% and 68.8% accuracy for binary classification, respectively, in the two experiments, confirmed by leave-one-participant-out cross-validation. Notably, consistent improvement in accuracy was specific to models utilizing right–left TMT and not observed in models utilizing the right–left wrist skin temperature. These findings suggest that lateralization in TMT provides unique information about emotional state, making it valuable for emotion recognition. With the ease of measurement by earphones, TMT has significant potential for real-world application of emotion recognition. Full article

Background/Objectives: This study examined the effect of sound preference on loudness tolerance (LTLs) and preferred listening levels (PLLs) using personal listening devices (PLDs). The implication of this relationship on hearing health promotion counseling and practices using PLDs is discussed. Methods: Participants were 50 individuals, aged 21 to 90 years, with normal hearing or hearing loss. Listeners rated several sound samples (i.e., music, running speech, and machinery noise) played through a PLD using earphones according to their sound preference (i.e., enjoyable, acceptable, and unpleasant) and then self-adjusted the volume setting to their LTL and PLL for a sound sample in each sound preference category. Results: Most listeners judged music (70%) as enjoyable, running speech (54%) as acceptable, and machinery noise (84%) as unpleasant. No significant differences were found in LTLs according to sound preference, but PLLs for enjoyable sounds occurred at significantly higher levels compared with those deemed acceptable or unpleasant. Conclusions: Listeners using PLDs perceived LTLs and PLLs differently according to their sound preferences. PLLs occurred at significantly higher volumes for sounds deemed enjoyable when using PLDs. The implication is that hearing health counseling should include information to PLD users on the potential of altered loudness perception with enjoyable sounds, which may lead to higher and riskier PLD listening levels. Full article

We demonstrated that focusing an ultrasonic beam on the eardrum can overcome the high-frequency sensitivity limitations and acoustic distortion of conventional hearing aid receivers. Multilayer PZT was used for an ultrasonic receiver that operates at low voltage and enters the external auditory canal, and a 3 mm radius radiator was designed to radiate the focused parametric acoustic signal to the center of the eardrum based on an acoustic analysis according to the frequency. To this end, an ultrasonic earphone consisting of a radiator attached to multilayer PZT and a 130 kHz parametric ultrasonic modulator was implemented; vibration and sound pressure were measured using a laser vibrometer and a tube-type microphone. The proposed parametric ultrasonic receiver generates an average sound pressure of 70 dB SPL at a frequency of 1~10 kHz with a 10 V_peak applied voltage; this was implemented to provide a higher output in the range of 5 kHz and above, which is difficult to cover with existing receivers. Full article

Background/Objectives: Previous research has shown that listeners may use acoustic cues for speech processing that are perceived during brief segments in the noise when there is an optimal signal-to-noise ratio (SNR). This “glimpsing” effect requires higher cognitive skills than the speech tasks used in typical audiometric evaluations. Purpose: The aim of this study was to investigate the use of an online test of speech processing in noise in listeners with typical hearing sensitivity (TH, defined as thresholds ≤ 25 dB HL) who were asked to determine the gender of the subject in sentences that were presented in increasing levels of continuous and interrupted noise. Methods: This was a repeated-measures design with three factors (SNR, noise type, and syntactic complexity). Study Sample: Participants with self-reported TH (N = 153, ages 18–39 years, mean age = 20.7 years) who passed an online hearing screening were invited to complete an online questionnaire. Data Collection and Analysis: Participants completed a sentence recognition task under four SNRs (−6, −9, −12, and −15 dB), two syntactic complexity settings (subjective-relative and objective-relative center-embedded), and two noise types (interrupted and continuous). They were asked to listen to 64 sentences through their own headphones/earphones that were presented in an online format at a user-selected comfortable listening level. Their task was to identify the gender of the person performing the action in each sentence. Results: Significant main effects of all three factors as well as the SNR by noise-type two-way interaction were identified (p < 0.05). This interaction indicated that the effect of SNR on sentence comprehension was more pronounced in the continuous noise compared to the interrupted noise condition. Conclusions: Listeners with self-reported TH benefited from the glimpsing effect in the interrupted noise even under low SNRs (i.e., −15 dB). The evaluation of glimpsing may be a sensitive measure of auditory processing beyond the traditional word recognition used in clinical evaluations in persons who report hearing challenges and may hold promise for the development of auditory training programs. Full article

Within the evolving field of sentiment analysis, the integration of topic modeling and association rule mining presents a promising yet underexplored method. This approach currently lacks an organized framework for maximizing insights that aid in drawing robust conclusions concerning customer sentiments. Therefore, this study addresses the need and rationale for having comprehensive sentiment analysis systems by integrating topic modeling and association rule mining to analyze online customer reviews of earphones sold on Amazon. It employs Bidirectional Encoder Representations from Transformers for Topic Modeling (BERTopic), a technique that generates coherent topics by effectively capturing contextual information, and Frequent Pattern Growth (FPGrowth), an efficient association rule mining algorithm used for discovering patterns and relationships in a dataset without candidate generation. This analysis of reviews on ten earphone products identified key customer concerns as follows: sound quality, noise cancellation, durability, and battery life. The results indicate an overall positive sentiment towards sound quality and battery life, mixed reviews on noise cancellation, and significant dissatisfaction with product durability. Using integrated topic modeling and association rule mining offers deeper insights into customer preferences and highlights specific areas for product improvement and guiding targeted marketing strategies. Moreover, we focused on algorithm selection to improve the model’s performance and efficiency, ensuring effective compatibility with our sentiment analysis framework. This study demonstrates how combining advanced data mining techniques and structuring insights from written customer feedback enhances the depth and clarity of sentiment analysis, furthering its applicability in e-commerce research. Full article

Pedestrian distraction poses significant risks at signalized intersections, especially in populated urban areas. This study investigates the primary causes of pedestrian distraction to determine the contributing factors affecting crossing behavior. Data were collected from ten signalized intersections by conducting in-person interviews, performing real-time observation, and reviewing video recordings. The study used binary logistic regression and Heuristic Bin analysis to examine different levels of distraction among pedestrians. Three major types of pedestrian distractions were identified: visual, auditory, and cognitive distractions. From the regression analysis, two models were developed to predict moderate and high levels of distraction based on factors such as age, intersection location, walking behavior, use of electronic devices, and awareness of traffic signals. The results indicated that smartphone usage and earphones were the predominant sources of distraction. Pedestrians walking in pairs demonstrated higher levels of distraction than those walking alone or in groups. Heuristic Bins analysis revealed that females were slightly more distracted than males while walking alone, in pairs, or in a group. Pedestrians also tended to be more distracted when they were walking in pairs than when walking alone or in groups. Full article

The emergence of AIGC has significantly improved design efficiency, enriched creativity, and promoted innovation in the design industry. However, whether the content generated from its own database meets the preferences of target users still needs to be determined through further testing. This study investigates the appeal of AI-generated stylized products to users, utilizing 12 images as stimuli in conjunction with eye-tracking technology. The stimulus is composed of top-selling gender-based stylized Bluetooth earphones from the Taobao shopping platform and the gender-based stylized earphones generated by the AIGC software GPT4.0, categorized into three experimental groups. An eye-tracking experiment was conducted in which 44 participants (22 males and 22 females, mean age = 21.75, SD = 2.45, range 18–27 years) observed three stimuli groups. The eye movements of the participants were measured while viewing product images. The results indicated that variations in stimuli category and gender caused differences in fixation durations and counts. When presenting a mix of the two types of earphones, the AIGC-generated earphones and earphones from the Taobao shopping platform, the two gender groups both showed a significant effect in fixation duration with F (2, 284) = 3.942, p = 0.020 < 0.05, and η = 0.164 for the female group and F (2, 302) = 8.824, p < 0.001, and η = 0.235 for the male group. They all had a longer fixation duration for the AI-generated earphones. When presenting exclusively the two types of AI-generated gender-based stylized earphones, there was also a significant effect in fixation duration with F (2, 579) = 4.866, p = 0.008 < 0.05, and η = 0.129. The earphones generated for females had a longer fixation duration. Analyzing this dataset from a gender perspective, there was no significant effect when the male participants observed the earphones, with F (2, 304) = 1.312 and p = 0.271, but there was a significant difference in fixation duration when the female participants observed the earphones (F (2, 272) = 4.666, p = 0.010 < 0.05, and η = 0.182). The female participants had a longer fixation duration towards the earphones that the AI generated for females. Full article

This prospective crossover study aimed to investigate the effect of binaural beat therapy music on soccer player performance. Between July 2023 and December 2023, 45 athletes (31 females/14 males, mean age = 20.47 ± 0.99) wore Bluetooth earphones through which one of the following was given during initial 20 min warm-up exercises before undergoing repeated sprint ability tests: no music/fast-tempo music/fast-tempo music with background binaural beat therapy music. Heart rate change after warm-up exercises/repeated sprint ability (RSA) tests and the time to finish RSA tests were recorded. Despite no significant difference in heart rate increase after warm-up between the two genders regardless of intervention, larger increases after RSA tests were found in males following any of the three interventions (all p < 0.01) with the most notable difference observed after fast-tempo music (p < 0.0001). A significant effect size (r = 0.2) correlated with fast-tempo music during warm-up in either gender. Binaural beat therapy music during warm-up reached a significant effect size only when all participants were considered, suggesting limited benefits. Full article

Emerging energy storage systems have received significant attention along with the development of renewable energy, thereby creating a green energy platform for humans. Lithium-ion batteries (LIBs) are commonly used, such as in smartphones, tablets, earphones, and electric vehicles. However, lithium has certain limitations including safety, cost-effectiveness, and environmental issues. Sodium is believed to be an ideal replacement for lithium owing to its infinite abundance, safety, low cost, environmental friendliness, and energy storage behavior similar to that of lithium. Inhered in the achievement in the development of LIBs, sodium-ion batteries (SIBs) have rapidly evolved to be commercialized. Among the cathode, anode, and electrolyte, the cathode remains a significant challenge for achieving a stable, high-rate, and high-capacity device. In this review, recent advances in the development and optimization of cathode materials, including inorganic, organometallic, and organic materials, are discussed for SIBs. In addition, the challenges and strategies for enhancing the stability and performance of SIBs are highlighted. Full article

This research investigated a mathematical model of earphone design with principal component analysis. Along with simplifying the design problem, a predictive model for the sound quality indicators, namely, total harmonic distortion, power of output, range of frequency response, signal-to-noise ratio, impedance of the speaker, and headroom, was formulated. (1) Background: Earphone design is a difficult problem requiring excessive experience and know-how in the process. Therefore, this research was developed to formulate a predictive model to facilitate the design process. (2) Methods: A simplified model for the design was developed in previous research, while the sound quality indicators were found to be connected to the eight material-specific parameters. Simultaneously, a principal component analysis (PCA) was utilized to decrease the number of input variables and create a more convenient and streamlined model. (3) Results: The principal component analysis-based approach obtained suboptimal predictive accuracy for the sound quality indicators, but a simplified formulation was obtained. (4) Conclusions: Based on the development and comparison of the modelling approach, it can be seen that principal component analysis can be utilized to simplify the mathematical model of the earphone design problem with a trade-off of accuracy. Full article

Internet of Things, blockchain and deep learning are emerging technologies that have recently gained popularity due to their various benefits and applications. All three domains have had success independently in various applications such as automation, agriculture, travel, finance, image recognition, speech recognition, and many others. This paper proposes an efficient, lightweight, and user-friendly solution to help visually impaired individuals navigate their way by taking advantage of modern technologies. The proposed method involves the usage of a camera lens attached to a Raspberry Pi device to capture live video frames of the user’s environment, which are then transmitted to cloud storage. The link to access these images is stored within a symmetrical private blockchain network (no superior access), where all deep learning servers act as nodes. The deep learning model deployed on these servers analyses the video frames to detect objects and feeds the output back to the cloud service. Ultimately, the user receives audio notifications about obstacles through an earphone plugged into the Raspberry Pi. In particular, when running the model on a high-performing network and an RTX 3090 GPU, the average obstacle notification time is reported within 2 s, highlighting the proposed system’s responsiveness and effectiveness in aiding visually impaired individuals. Full article

Fe-Co alloys have the advantages of high saturation magnetization and high magnetic elongation. They are used in electromagnet pole heads, earphone vibration films, magnetostriction transducers, and so on. At present, few papers have been published on the co-deposition process of Fe-Co alloys. In the present work, smooth dense Fe-Co films of 10 μm were successfully prepared in an economical, green, sulfate solution system via electrodeposition. The cathodic polarization curves were measured separately under different conditions, and the electrochemical analyses showed that the increase in the main salt concentration is beneficial for obtaining higher deposition rates. An increase in temperature can increase the current density of electrochemical reduction of Fe²⁺, and 50 °C is a suitable temperature at which to prepare the Fe-deposited layer with a flat surface. The increase in Co²⁺ concentration can favor the co-electrodeposition process of Fe-Co alloys. Secondly, the EDS results showed that the mass fraction of Co in the films increased linearly with the increase in Co²⁺ concentration in the solution. The mass fraction of Co in the films gradually increased with the increase in current density. The mass fraction of Co in the films gradually decreased with the increase in (NH₄)₂SO₄ concentration. In addition, the XRD showed that the grain size of the Fe-Co alloy films was closely related to the concentration of (NH₄)₂SO₄ in the electrolyte, and the smallest crystallite size of the Fe-Co alloy film was 17 nm. SEM showed that (NH₄)₂SO₄ can significantly affect the surface morphology of the films, in which the cracks are obviously removed. Full article

Nowadays, the use of 3D printing is becoming a key process for on-demand and customized manufacturing. One of the most flexible 3D printing techniques is fused deposition modeling (FDM), where the combination of multiple materials was recently introduced. A quantum leap in part design is possible by integrating local variations between materials that allow for expanded functionality to be built into a single part. Therefore, the process of co-extrusion and material mixing is becoming more and more popular. The process of management and design of the engineered part are still complicated, and there are no commercially available tools that follow the process from design to production of these highly engineered products. This paper proposes a methodology to fill this gap and allow any designer to be able to produce multi-material parts by editing a G-code (computer numerical control programming language) with engineered gradients for FDM technology. More specifically, the proposed approach is based on the modification of the G-code according to a volumetric model describing the local combination of two or more materials. This original aspect allows for a wide extension of the current software capabilities. To explain and test the method, a simple test case was investigated, in which two components of an earphone are consolidated and developed gradually by combining polylactic acid and thermoplastic polyurethane. The results show the effectiveness of the proposed approach within the limits of the material coextrusion additive manufacturing process. Full article

Wearable devices capable of measuring gait parameters may provide a means to more economical gait analysis compared to conventional equipment comprising of a motion capture system and a forced treadmill. Beflex Coach (Beflex, Republic of Korea) is one such device but worn on the ear as Bluetooth earphones, unlike other wearables worn on the wrist, feet, or torso. In this study, the validity of the device was examined against a motion capture system and a forced treadmill for walking and running parameters. Five walking parameters (cadence, single support time, double support time, vertical oscillation (VO), and instantaneous vertical loading rate (IVLR)) and six running parameters (cadence, stance time, flight time, peak force, VO, and IVLR) were studied. Twenty young adults participated in walking or running on a forced treadmill at different speeds (walking: 0.8, 1.25, and 1.7 m/s for walking; running: 2, 2.5, and 3 m/s) while the two systems operated simultaneously. As a result, all parameters showed excellent associations (ICC > 0.75) and good agreements in Bland–Altman plots. The results of the study support the potential use of the ear-worn device as an inexpensive gait analysis equipment. Full article

Although hearing devices based on cartilage conduction have become more widely used in Japan, methods for evaluating the output volume of such devices have not yet been established. Although the output of air-conduction-based sound-generating devices (e.g., earphones and hearing aids) can be standardized via the head and torso simulator (HATS), this is not applicable to cartilage conduction devices because the simulated pinna is too soft (hardness: A5) compared with human aural cartilage. In this study, we developed polyurethane pinna that had the same shape but different degrees of hardness (A40, A20, and A10). We then compared the HATS results for the new pinna simulators with data from human ears. We found that the spectral shapes of the outputs increasingly approximated those of human ears as the simulated pinna hardness decreased. When a durometer was pressed against the ear tragus of a human ear, the hardness value ranged from A10 to A20. Accordingly, cartilage-conduction-based sound information could be obtained using a HATS that had a simulated pinna with a similar hardness value. Full article