This study explores the relationship between lifestyle and purchasing priorities among Chinese consumers. The participants were segmented into four lifestyle types through a survey, and machine learning models were applied to investigate the Kansei factors influencing purchasing decisions. Statistical analysis using multivariate analysis of variance (MANOVA) and one-way analysis of variance (ANOVA) identified significant differences in purchasing priorities across lifestyle types. Furthermore, classification models, including tandom forest and shapley additive explanations (SHAP) revealed the key features affecting the decision-making process of each type. These findings provide valuable insights into designing marketing strategies tailored to consumer lifestyles.

Advancements in deep learning-based pose estimation models like OpenPose have brought attention to emotion recognition from posture. However, the need for emotion-labeled datasets derived from posture presents a significant challenge. Researchers have attempted to address this issue using transfer learning and data augmentation, but these methods need to fundamentally diversify the emotional expressions within datasets, making them incomplete solutions. This study used ensemble learning to efficiently train an emotion-recognition model on a small dataset. Simultaneously, we tackled diversifying emotional expressions by leveraging skeletal coordinates extracted from videos. The proposed method includes preprocessing, feature extraction, and ensemble learning. During preprocessing, we normalized skeletal coordinates to eliminate variations caused by individual differences. We used 15 skeletal points for feature extraction and calculated 13 joint angles from these points as features. Numerical experiments revealed that the ensemble- learned MLP (EnMLP) achieved the highest accuracy of 69.69%, outperforming the 64.37% accuracy reported in prior studies by 5.32%. While the results demonstrate the proposed method's effectiveness, recognition accuracy remains below human-level performance, necessitating further refinements. Future work will focus on integrating posture variation and addressing challenges in recognizing emotions from non-frontal views, enhancing practical applicability in real-world scenarios.

Accurate prognostic prediction is essential in end-of-life care, particularly in Japan, where cultural values emphasize the importance of being present at the time of death. However, tools that are both accurate and feasible for use in home settings remain limited. Home-visiting nurses are often the primary healthcare professionals most involved during the terminal phase, providing detailed observations through their nursing records. These records may offer valuable insights for prognostic prediction in home-based care. A retrospective analysis was conducted using nursing records from 71 patients who received care from the Nana-r Home-visit Nursing Station between April 2016 and December 2023. Data from the final month before death were analyzed, comprising 1,217 nursing records and 57,884 words of text data. Text mining with KH Coder was used to examine co-occurrence networks and analyze keyword patterns in relation to the number of days until death. The analysis identified themes such as excretion-related activities, distress symptoms, skin and oral health, and consciousness levels. Temporal patterns revealed that terms like "walking" and " eating" were more common earlier, while "consciousness," "breathing," and "urination" appeared closer to death, reflecting systemic decline. These findings suggest that nursing records, particularly their free-text descriptions, provide meaningful insights into the terminal phase. Integrating these observations with quantitative data may support the development of practical tools to improve care strategies for patients receiving end-of-life care in home settings.

Individuals with the sensory processing sensitivity (SPS) exhibit hypersensitivity to environmental stimuli and are at increased risk for stress, anxiety, and depression (Aron & Aron, 1997). Although the physiological basis of SPS is not fully understood, previous research suggests that electroencephalography (EEG) may partially capture its characteristics. In this study, we examined 117 participants with SPS traits to examine their neurophysiological characteristics. We quantified each participant's SPS level using the HSPS-J19 scale, originally developed by Aron and adapted for Japanese by Takahashi (2016). Our analysis focused on EEG band activity and neural synchronization. The results showed significantly increased synchronous activity in the delta band within the auditory-visual association region of the right posterior temporal lobe during rest with eyes closed. This suggests that individuals with SPS have a neural signature of excessive attention-related activity. We continue to conduct neurophysiological approach to these findings and are exploring minimally invasive methods to regulate such excessive activity.

This study aims measurement and analysis to pile the knowledge for developing everyone’s life career through various roles and satisfaction. Firstly, this paper focused on the factors of the satisfaction UP-DOWN and Resilience (pattern to UP) by Life-Line chart (LLC) analysis. This study consists of 1) LLC interview and physical measurement, 2) Structural Analysis of factors and UP-DOWN samples, 3) Improvement of LLC measurement and analysis. As a result, 1) 15 LLC data collected, 2) 177 UP-DOWN were analyzed and summarized in a new structure of PCSRTG (Pride, Complex, Stress, Relax, affection Take, and affection Give), referring to literatures. 3) PCSRTG will make the measurement step easier.

This research developed methods and places for multicultural disaster prevention education and examined their effectiveness. Specifically, we implemented methods and place designs for multicultural disaster prevention education for both foreign-origin residents and Japanese residents in the Yoshizuka Area, Hakata Ward, Fukuoka City, Fukuoka Prefecture, and conducted qualitative and quantitative analysis. As a result, it was found that the disaster prevention knowledge of residents who participated in multicultural disaster prevention education places deepened. In addition, the study also showed the potential of multicultural disaster prevention education to promote multicultural exchange through disaster prevention. This perspective is a finding that could not be derived from previous research that only targeted foreign-origin residents, and it is a finding that can only be obtained through this research, which targets both foreign-origin residents and Japanese residents living in the same community.

Mode and tempo are crucial elements in the connection between music and emotion. Major keys typically evoke bright and optimistic emotions, while minor keys are associated with darker and more melancholic emotions. Similarly, faster tempos often convey a sense of activity, whereas slower tempos evoke a meditative or calm state. This study aimed to investigate the effects of mode and tempo by employing “sister pieces,” variations of the same musical composition with systematically modified mode and tempo. Four well-known classical pieces were selected, and three sister pieces were generated for each, resulting in 16 auditory stimuli. These were evaluated by 17 healthy adult participants to measure emotional impressions. The findings revealed that changes in mode and tempo significantly influence the emotional impact of music, underscoring the utility of pieces in exploring these musical elements.

In marketing communication, color has played an important role as a visual element. While previous studies on cross-modal correspondence involving visual color and other senses have been conducted in experimental settings, there has been little discussion on their applicability to real-world advertising environments. Additionally, research on cross-modal correspondence between visual color and auditory senses in advertising has been limited to musical stimuli, with few studies examining the effects of human voice stimuli. Therefore, this study set the research question of whether the congruence between the colors perceived from male and female voices and the colors perceived from the product enhances product attractiveness in detergent advertisements. Using a randomized controlled trial (RCT) conducted in Japan, we created 15-second video advertisements for a fictional detergent featuring blue or pink themes paired with male or female voices, representing congruent and incongruent color-voice conditions. The results showed that the color-voice congruent group perceived the product as more attractive than the color-voice incongruent group. These results highlight the importance of considering auditory color perception in marketing strategies. This study extends existing research on visual-auditory cross-modal correspondence to human voice stimuli and provides practical insights for marketers on effective auditory and visual perceived colors in advertising. Limitations include the focus on detergent, cultural specificity to Japan, and reliance on traditional gender-color stereotypes, which may evolve. Future research should explore diverse products, regions, and shifting societal norms around color and gender associations.

In recent years, many traditional techniques that have been handed down from generation to generation have been declining, and the question is how to carry on traditional culture. In response, the Hiwadabuki (cypress bark roofing), a traditional roofing technique in Japan, was utilized to develop the Hiwadabuki patterned panel, a panel with a traditional design pattern of Hiwadabuki. The purpose of this study was to clarify the appropriate shape of the Hiwadabuki patterned panel when used as an art panel. Experiments were conducted to compare the preference for Hiwadabuki patterned panels with different aspect ratios and monochrome panels of cypress bark color with different aspect ratios. The results showed that aspect ratios of 1.618 (horizontal) and 1.414 (horizontal) tended to be the most preferred, and similar results were obtained for the monochromatic panels. On the other hand, cluster analysis indicated the existence of several groups with different preferred aspect ratios.

This study investigates the role of aesthetics novelty in sustainable apparel consumption. According to McKinsey Survey in 2020, concern for environment coupled by COVID-19 pandemic has changed consumers’ attitude when it comes to fashion consumption. Consumer, especially the conscious consumers, no longer see newness, or novelty, as the most important factor in purchase decision. Through empirical study, we suggest that not only novelty is not a determining factor in purchase intention, novelty caused by aesthetic atypicality might cause suspicion for greenwashing (Perceived Greenwashing, PGW) among consumers, especially those scoring high in Green Consumption Value (GCV) and Fashion Interest (FI).

This study investigates four different audio models in virtual reality (VR) environments to improve social interactions specifically within Metaverse settings for poster conference presentation. The audio models include Global Voice (uniformly audible), Spatial Attenuation Voice (volume decreases with distance), Area Voice (Limited by area), and Directional Voice (audio dependent on the listener's head direction). A virtual conference room was created using Unity, and user experience was assessed through subjective questionnaires and physiological data. Results showed that Spatial Attenuation and Directional Voice models enhanced focus and interaction, while the Area model promoted relaxation. The findings highlight the potential of unique audio systems to enhance immersion and usability in VR.

The purpose of this study is to analyze the key factors that facilitate discussion of vehicle tsunami evacuation from the perspective of Learning Environment Design. In detail, a banner was created for a vehicle evacuation guidance in the Nishikino Area of Kuroshio Town, Kochi Prefecture. After the activity, there was progress in the discussion, such as the drill being conducted in the community. To identify these factors, surveys with participants were conducted. As a result, the impact of each element was identified following the 4 aspects of Learning Environment Design. In this practice particularly, it seems that the discussion has progressed because of the improved balance among each aspect in the learning environment.

This study evaluates the technique that can present virtual objects at freely-selected distances of tens to hundreds of meters in optical see-through mixed reality. Presenting virtual objects at freely-selected such far distances is crucial to outdoor applications of optical see-through mixed reality, e.g., outdoor navigation and outdoor annotation. However, it is difficult for conventional techniques because they control virtual objects’ depth perception with binocular disparity that does not work at the great distances. In the proposed technique, depth cues separated into three hierarchies are given virtual objects for each hierarchy. In the first hierarchy, physiological cues, e.g., vergence and binocular disparity, are given to indicate virtual objects are not at near depths. In the second hierarchy, pictorial cues, e.g., familiar sizes and luminance contrast, are given to indicate rough depths of virtual objects. In the third hierarchy, cues based on scene understanding are given to indicate accurate depths of virtual objects. In the evaluation, the effect of placements, which are one of cues based on scene understanding, are examined with virtual objects superimposed into stereo photographs. Their perceived depths are measured, and the results indicate that accurate depths of virtual objects can be indicated with placements of virtual objects. Such findings support the proposed technique, and we demonstrate its feasibility.

This study developed and evaluated a training assistance system designed to enhance internal focus (IF) during squatting exercises. IF, which directs attention to muscle activation, has been shown to promote muscle hypertrophy more effectively than external focus. The system utilized MediaPipe’s BlazePose for real-time posture estimation and provided visual and auditory feedback based on knee flexion angles to optimize muscle engagement. Electromyographic (EMG) measurements, including peak EMG, root mean square, and integrated EMG, were recorded for the rectus femoris and gastrocnemius muscles in eight participants. Results indicated that auditory feedback heightened the awareness of rectus femoris, while visual feedback enhanced focus on the gastrocnemius. These effects may also be influenced by factors such as ease of maintaining proper form. This findings highlight the potential of feedback-driven systems to improve training efficacy. Future research will focus on refining the system and experimental protocols to better isolate the effects of IF.

This study aimed to measure the P300wave of event-related potential around the ears using the P300-speller, as step in the development of an ear-mounted electroencephalography (EEG) device. In ordinary EEG measurements, challenges such as unsightly EEG caps and the mess caused by using conductive paste are notable issues. To address these problems, methods have been proposed in recent years for measuring EEG signals around the ears. Previous studies have reported classification rates of more than 70% for signals containing P300 using linear discriminant analysis (LDA), indicating that it is possible to record P300 from the ear periphery. In this study, EEG measurements were taken around the ears during tasks involved the P300-speller, and the results were evaluated by waveform analysis and LDA. P300 waveforms were successfully identified at measurement points near the ears, and in the eight participants for whom successful measurements were, captured; LDA achieved a classification accuracy exceeding 90%.

To solve the attitude-behavior gap in ethical consumption, it is necessary to develop a product concept that enhances consumers’ perceived value and embodies it with high perceived quality. Therefore, this study examined product concepts and package designs that enhance consumers’ perceived value of eggs and beef that are considerate of animal welfare. Owing to recent public interest in the welfare of intensive livestock, the number of cage-free livestock is increasing. Compared to conventional-range livestock, free-range systems are active, have less fat, and can produce high-quality products. In addition, packaging materials that realize environmental consideration without compromising product value increase consumer’s perceived value. Based on the above, the following two hypotheses are proposed: “H1: A concept that appeals to high product quality will increase the consumer’s perceived value more than a concept that appeals to animal welfare.” “H2: In the case of packaging for products that are considerate of animal welfare, paper materials will increase the consumer’s perceived value more than plastic materials.” A randomized controlled trial was conducted with 3,000 people using an online survey in a Japanese market. H1 and H2 were supported. Men who are good at deliberative thinking valued concepts, whereas women good at intuitive thinking valued packaging materials. the findings have implications for practitioners who should be aware that consumers value tangible value.

Several studies have examined the factors that shape facial impressions; however, the relationships between facial morphology, skin, and facial impressions remain unclear. This study examined the relationships between facial morphology, image features, and impressions such as attractiveness, sexual dimorphism, dominance, and trustworthiness. Using a linear non-Gaussian acyclic model (LiNGAM), which is a data-driven method for causal inferences, we found that face density, fractal dimension, and spectral slope influenced facial impressions. The causal pathways to trustworthiness varied across male and female images and were mediated by attractiveness and sexual dimorphism. This exploratory method clarified the role of facial features in impressions, aiding the development of psychological models and the understanding of these relationships.

This workshop study explores My Daily Badge (MDB), a wearable system that subtly translates biosignals (e.g., heart rate) into abstract patterns to represent emotions, aiding those with social cue challenges. A workshop with 12 participants (aged 16-27 years) revealed design principles: smooth shapes for positive valence, jagged edges for negativity, and complex patterns f or high arousal. The identified use cases included the enhancement of non-verbal communication, although it was noted that participants avoided displaying negative emotions in order to maintain social harmony. Younger users indicated a preference f or casual interactions, while older participants proposed applications for therapeutic and educational purposes. The study's findings underscore the potential of MDB for the subtle expression of emotion, but also highlight the challenges associated with priva cy, authenticity, and the ethical disclosure of emotion. This work contributes to the design of wearable technology for affective computing, emphasizing context-aware, socially harmonious solutions.

Unbiased recommender learning (URL) and off-policy evaluation/learning (OPE/L) techniques are effective in addressing the data bias caused by display position and logging policies, thereby consistently improving the performance of recommendations. However, when both bias exits in the logged data, these estimators may suffer from significant bias. In this study, we first analyze the position bias of the OPE estimator when rewards are missing not at random. To mitigate both biases, we propose a novel estimator that leverages two probabilities of logging policies and reward observations as propensity scores. Our experiments demonstrate that the proposed estimator achieves superior performance compared to other estimators, even as the levels of bias in reward observations increases.

Real objects can be transformed but cannot be copied and pasted. In contrast, digital objects can be copied and pasted. In this way, may not necessarily apply that people's perception of the real world may not apply to digitized objects. With the development of information technology, in an age where a wide variety of services are provided digitally, problems due to differences in perception, particularly people's perception of AI, may arise in the future. This paper explores the extent to which people perceive an object as retaining its original identity. In the experiment, participants were shown videos of real objects, computerized information, and digitalized objects moved by AI that were gradually changed, and a questionnaire was used to investigate whether the objects were the same as the original. Additionally, a questionnaire was conducted to examine people's perception of digital immortality.

With advancements in generative artificial intelligence (AI), including large language models (LLMs), AI technologies are being increasingly utilized in various aspects of daily life, and their adoption is expected to proliferate. However, only a few studies have evaluated the content created by generative AI and human responses based on real-world scenarios. Assessing the quality of content involving generative AI and its impact on human psychological acceptance is crucial for appropriate utilization of these technologies. In this study, we evaluated the content created by generative AI for book endorsements. Specifically, the quality of the content created was compared under four generation processes: (i) solely by humans, (ii) solely by ChatGPT, (iii) by ChatGPT and then revised by humans, and (iv) by humans and then revised by ChatGPT. In addition, we investigated how disclosing the content generation process affects evaluation. The results revealed that AI content has a more significant effect on increasing purchase intention than content generated solely by humans. However, when the content-generation process was explained, some resistance toward AI-generated content was observed. This resistance was mitigated when humans were involved in certain aspects of the generation process.

The retinal images of the left and right eyes contain differences caused by the disparity in interocular distance, and this difference is referred to as binocular disparity, which is one of the depth cues. In the virtual reality (VR) technology, binocular disparity is presented to create a three-dimensional appearance, but the perceived size of objects in VR differs from what is perceived in the real world. This difference is believed to be partly due to the differing depth cues used in VR and the real world. The aim of this study was to propose an image generation method that reproduces a size perception close to the real world by measuring the size of objects perceived in VR and adjusting the size through scaling to match their subjective size. Specifically, the study experimentally investigates the relationship between the perceived size of objects perceived in VR and their perceived size in the real world, expressing this difference as a magnification-rate function with the observation distance as a variable. Additionally, an evaluation experiment was conducted to compare the impressions of images created using this function with those of images generated via perspective projection. The results revealed that for distant objects, images with the magnification function gave an impression closer to the real world than images created using perspective projection.

Facial expressions play an important role in emotional communication and impression formation. However, existing studies have often focused on a limited set of expressions, overlooking the complexity and variety of human facial displays. This study proposes a method to generate diverse facial expressions using the facial action system, focusing on the synergistic and mutually exclusive relationships between action units (AUs). Based on Russell's Circumplex Model, we synthesized 49 different expressions and conducted a validation experiment, achieving an 83% accuracy rate and providing valuable insights into the AU-emotion relationship. Our approach captures a broader range of expressions than those used in previous studies. In future work, we will investigate how these 49 expressions affect users' impressions, explore which expressions are considered "favorable" or "approachable" in specific contexts, and identify the defining characteristics required to produce optimal facial expressions in different scenarios.

The impact of music on human emotion is both significant and multifaceted, with chord progressions playing a central role in shaping listeners' experiences. This study examines the emotional effects of harmonic complexity and tonality by analyzing two four-chord progressions ("I-V-vi-iv" and "IV-vi-VII-V"). By systematically varying the mode (major/minor) and chord structure (triad/seventh chord) of these progressions, the study reveals how harmonic variations influence emotional dimensions. Factor analysis identified two primary dimensions: Positive and Sentimental. Results showed that seventh chords elicited a more subtle negative emotional response compared to triads, particularly in major modes. However, sentimental emotions appeared less sensitive to these harmonic factors. These findings emphasize the significance of harmonic structure and progression context in shaping emotional perception, offering insights into the role of complexity and tonality in music's emotional expression.

Research on extracting impression information from text has increased in recent years. Many studies have evaluated impressions using impression words (adjectives). However, the influence of degree adverbs that modify impression words on the strength and degree of impressions has not been sufficiently examined. Therefore, in this study, impression words and degree adverbs related to the four impression scales are collected to construct an impression dictionary for evaluating impressions of apparel products. Furthermore, rules for calculating impression scores are formulated using the vocabulary included in the impression dictionary. Finally, based on the constructed impression dictionary and calculation rules, impression scores are calculated using actual review texts of apparel products.

This study aimed to develop a system that supports “walk-and-eat” experiences centered on a specific dish within a particular region. The system provides detailed information about the dish and its cultural and regional context, alongside personalized restaurant recommendations tailored to users’ preferences. These features enable even first-time visitors to plan their culinary explorations efficiently. Through this approach, users can gain a deeper understanding of local foods by exploring their variations, preparation methods, and cultural significance. This study integrates a culinary focus with tourism innovation, aiming to create a unique and engaging experience that enhances the connection between visitors and the local area.

This study developed and validated a tool to sensorially evaluate the "negative image psychological scale," aiming to use it in disaster education and learning about the natural environment. Based on insights from interviews with experts and findings from pediatric nursing practices, a spherical analog tool was prototyped to facilitate the visual and sensory interpretation of negative images. Experiments conducted with university students demonstrated that this tool outperformed traditional evaluation methods (VAS method) in terms of ease of visual and sensory expression. However, challenges such as difficulties in fine-tuning visual representations have been highlighted, necessitating further improvements and testing in diverse populations. This study suggests the potential application of the tool in disaster education while also exploring its expansion into medical and psychological fields.

This study examines the use of simulation technology to evaluate the comfort of upper garments. Current simulation tools allow for avatar pose adjustments to assess clothing comfort during movement; however, discrepancies between simulated and real- world conditions remain unresolved. This research investigates the effect of 3D wearer body reproduction on clothing comfort evaluation. The bodies of ten female participants in two poses (A-pose and F-pose) were 3D scanned, and corresponding avatars were created using simulation software. Differences between the scanned bodies and avatars were calculated using contour lines. Test garments were made for each participant, and clothing pressure was measured both in real-world tests using air packs and in simulations using avatars and pressure maps. Results showed minimal differences between avatars and human bodies in the A-pose, with participants reporting minimal discomfort and actual clothing pressures remaining below 1.2 kPa at all measurement points while simulations often showed 0 kPa. In contrast, significant discrepancies were observed in the F-pose, particularly in the armpit area, where simulated avatars exhibited unrealistic irregularities. In the F-pose, simulated pressures were up to three times higher in some cases. These findings suggest that simulation-based comfort evaluation could be viable for the A-pose. However, for the F-pose, accurate evaluation is hindered by large shape differences around the armpit. This study highlights the need to improve the accuracy of avatar joint modeling to better reflect real human deformation and pressure distribution.

It is known that, in a VR environment, introducing a misalignment between the user’s own motion and that of an avatar can alter the user’s impression. In a previous study, by utilizing camera shake effects, breathing motions were developed in a more immersive first-person perspective, where changes in the position of the avatar's viewpoint could be recognized. However, because that study dealt only with a stationary avatar, it remains unclear how breathing motion effects might function when the avatar is in motion. Therefore, the present research aims to investigate how breathing motion effects in a VR avatar walking around a field influence user perception. Experimental results suggest that while the avatar’s breathing motion effect acts as an independent factor during walking, its impact is weaker than when the avatar is standing still. Furthermore, participants developed a sense of bodily self-awareness toward the avatar, perceiving the shaking of the viewpoint as though it were their own motion. An analysis of LF/HF derived from heart rate variability indicates that slowing the breathing cycle can reduce user stress.

While happiness and wellbeing are traditionally assessed using tools like the Oxford Happiness Questionnaire and Ryff’s Psychological Wellbeing Scale, the present study examines the potential of facial EMG and facial action coding system (FACS) to measure these emotional traits in elderly participants. Ten individuals completed abbreviated versions of these questionnaires, followed by EMG measurements (zygomaticus, orbicularis oculi, corrugator) and video recording during emotional recall and expression tasks. The tasks involved rating happiness-related questions and recalling the feelings associated with those responses (Part 1) or recalling and actively expressing the feelings (Part 2). Main results revealed that participants with higher wellbeing (G1a) and happiness scores (G2a) demonstrated significantly stronger orbicularis muscle activity during the recall and expression of feelings associated with happiness-related questions compared to those with lower scores (G1b and G2b). Furthermore, the combined EMG activity associated with positive emotions (zygomaticus + orbicularis - corrugator) was significantly stronger in participants with higher wellbeing and happiness scores (G1a & G2a) compared to those with lower scores (G1b and G2b). Video analysis using FaceReader revealed that the action units associated with the measured EMG regions (AU12, AU6, AU4 respectively) did not show similar reactions to EMG but reflected different behavior such as increased AU12 values in G2a compared to G2b, but decreased AU6 values in G1a & G2a compared to G1b & G2b. These findings suggest that EMG and FACS measure different aspects of happiness and wellbeing. Orbicularis muscle activity may act as a biomarker for these traits, while FACS offers additional insights.

This study explores the asymmetry in forming and changing evaluations of good and bad behaviors and compares these to evaluations of neutral probabilistic events. Moral judgments, particularly those shaped by negativity bias, show that negative impressions outweigh positive ones in their influence. Experiments involved participants watching video sequences of helping (good) or obstructing (bad) actions, followed by a questionnaire assessing the characters’ perceived morality. A second experiment assessed subjective probability judgments using a simulated coin-toss task. The findings reveal that a single bad action significantly disrupts perceptions of goodness built through repeated good actions, while a single good action does not sufficiently restore disrupted positive evaluations. Bad evaluations, however, show more resistance to change when formed through repeated bad actions, though they can be weakened by a subsequent good action. Comparisons with probability judgments highlight distinct cognitive processes, showing that evaluations of goodness are fragile and prone to negativity bias, whereas evaluations of badness are more persistent and robust. These results underscore the asymmetry in moral evaluations and its implications for understanding cognitive biases. The study has practical applications, such as identifying unconscious biases in communication or media, which could aid in creating tools to visualize and address these biases. By shedding light on the mechanisms of evaluation formation and transformation, the research offers insights that could contribute to the development of fairer societal systems and decision-making frameworks. Future work aims to deepen this understanding and mitigate bias at both individual and systemic levels.

Affective engineering is an interdisciplinary domain within design research, yet its disciplinary scope remains ambiguous, particularly for newcomers. Here we show the location of affective engineering, represented by papers published in the Int. J. Affect. Eng. (IJAE), occupies a unique position within the broader landscape of design research. We analyzed and compared ~200 IJAE papers to the other ~60,000 design research papers using a bibliometric approach. After we collected high-dimensional representations of titles and abstracts, including externally generated text embeddings and TF-IDF, we further embedded them into two-dimensional visual maps using UMAP. Additionally, we visualized metadata such as author affiliation and citation metrics to highlight IJAE’s distinct characteristics. Our findings reveal IJAE’s relatively low author affiliation diversity and citation impact, underscoring challenges for affective engineering’s global recognition and integration. Notably, IJAE exhibits a predominantly Japanese authorship base despite the international scope implied by its title. Conversely, we demonstrate that affective engineering is a thematically expansive domain with a diverse disciplinary scope. IJAE is better grouped with interaction design journals than engineering design journals, as its title might imply. Through exploratory data visualization, we identify IJAE as a unique, predominantly Japanese, low-impact, omnivorous interaction design journal.

This study assessed mental fatigue using ear-EEG. Fatigue is a significant issue in Japanese society, where overwork is a severe problem. EEG frequency analysis is a common method for evaluating fatigue; however, it places a burden on participants due to the attachment of scalp electrodes. This study verified the accuracy of measuring fatigue in cognitive tasks while reducing the burden using ear-EEG. Alpha and beta waves were used for the measurement, and the frequency change with fatigue was used as an evaluation index. In addition, steady-state visual evoked potential and critical fusion frequency were used to measure concentration and fatigue, respectively, and subjective fatigue was evaluated to comprehensively assess the effectiveness of ear-EEG in measuring fatigue. The ear-EEG experimental results exhibited trends similar to those observed in case of head EEG. Therefore, ear-EEG is suitable for fatigue evaluation. However, compared to the head EEG setup, the ear-EEG setup is smaller, which renders detailed evaluation more challenging. Moreover, the ear-EEG results contained considerable noise, such as electromyograms. Therefore, further efforts are required for the fatigue level evaluation with the same accuracy as that of head EEG by applying a correction.

Humans obtain most of their information about the external world through vision. One of the difficulties that arise when vision is impaired is mobility. For this reason, special needs education schools for children who are visually impaired provide early training in some skills necessary for orientation and mobility. Specifically, this training begins with understanding spatial concepts, forming body images, and developing the ability to comprehend the surrounding environment. It progresses through guided walking practice within the school building and its surroundings before advancing to field training involving roads and stations. However, field training often includes tasks that are difficult to repeatedly practice or review thoroughly, such as boarding and alighting buses and trains, crossing crosswalks, and checking traffic signals. As a result, teachers strongly desire the development of ICT-based learning systems that can serve as a preparatory step before transitioning safely and smoothly to field training on actual school commuting routes. In this study, we conducted foundational research for the developing a digital teaching material to support instruction for visually impaired elementary school students commuting schools, aiming to enable independent school commuting. To this end, we explored the possibility of using 360-degree videos in instructional settings. As a result, we identified the benefits of using 360-degree videos and obtained insights for future directions.

In this study, experiments were carried out with high school and university students to determine whether drowsiness and concentration can be quantified by counting participants’ blinks during the calculation tasks. Physiological and behavioral indicators like blink count, questionnaire results, and the results of calculation tasks, were used to investigate the correlations between them. For university students, the results showed a positive correlation (r = 0.62) between the variance of blink count and the number of responses to the calculation task and a negative correlation (r = −0.30) between the number of responses and drowsiness. For high school students, a negative correlation (r = −0.47) was found between the average blink count during the task and levels of anxiety. Anxiety levels also showed a negative correlation (r = −0.47) with accuracy. These findings indicate that blink count is a useful indicator for effort level and suggest further links between eye movement, concentration, and psychological state.

This study investigates the impact of various teaching strategies on second language learners' physiological response and engagement state. the research explores physiological response through heart rate variability (HRV) signals and engagement detection. Seven adult participants were involved in three distinct teaching strategies (video explanations, quizzes, and AI interactions), while HRV data measured using Photoplethysmography (PPG) and engagement levels condition measured using image-based techniques. Results indicate that engagement correlates with HRV features such as RMSSD, SDNN, and pNN50, with higher HRV linked to not engagements result. Although ANOVA analysis showed no statistically significant differences across strategies, Moderate effect sizes indicate the presence of subtle physiological responses. These findings highlight the potential of physiological indicators in optimizing adaptive teaching methodologies for second language acquisition. Future work should extend the teaching variation and participants.

In this paper, we propose a machine learning model to predict tempo using sheet music alone. The model estimates tempo in a manner analogous to how humans interpret affective and contextual information in sheet music. To construct the dataset for training, we invited wind instrumentalists to provide tempo annotations. After applying data augmentation techniques, the model was trained and evaluated through experiments. The results show that for the training data, 98.0% of the predicted tempo values deviated by less than 10 from the expected values. For the validation data, this percentage was approximately 62.1%. Notably, sheet music with significant tempo deviations is difficult to judge, even for human instrumentalists. Overall, the model demonstrated the ability to predict tempo from sheet music, achieving performance comparable to that of a beginner instrumentalist.

Driver stress has a significant impact on cognitive function and driving performance, which increases the risk of an accident. Stress, which includes environments like congestion, monotonous conditions, and tailgating elicits distinct emotions that affect the driver’s psychological and physiological states. This study looks into the relationships between facial expression classification using the k-means, physiological indicators, and subjective evaluations under stress-related conditions. Facial features related to eye, mouth, and head movements were extracted using MediaPipe, and expressions were divided into four clusters using the elbow method. The physiological evaluation involved analyzing heart rate variability using the LF/HF ratio and nHF as indicators of sympathetic and parasympathetic nervous activity, respectively. Subjective evaluations were based on Russell’s circumplex model, which used a Visual Analog Scale (VAS) to quantitatively assess emotions along the “pleasure-unpleasure” and “arousing-sleepy” dimensions. Three participants drove in virtual environments that replicated congestion, monotony, and tailgating. The results showed that k-means classification accurately captured physiological changes, with monotonous driving exhibiting increased LF/HF and decreased nHF, which corresponded to cluster transitions over time. Furthermore, subjective evaluations revealed psychological differences between clusters that were not evident from physiological indicators alone. These distinctions, such as increased sleepiness in certain clusters, highlight the complementary roles of both methods in capturing complex emotional states. This study demonstrates the significant potential for combining k-means-based facial expression classification with physiological and subjective metrics to comprehensively assess driver emotions. By combining these approaches, this method provides useful insights for developing advanced driver assistance systems with the goal of improving emotion prediction accuracy and overall road safety.