Search Results (1,186)

Background: The COVID-19 pandemic significantly reduced physical activity levels, particularly among older people, negatively impacting their postural balance and increasing the risk of falls and hip fractures. This study aims to assess the effect of a virtual reality-based exergame physical activity protocol at home on improving postural balance in older people. Materials and Methods: A quasi-experimental design was employed with 10 older people (71 ± 9 years) who participated in a virtual reality-based exergame physical activity protocol consisting of eighteen 25 min sessions conducted at home. The protocol incorporated 3D movement tracking using a sensor attached to the participants’ bodies to monitor postural sway in real time. Clinical measurements included the Timed Up and Go test and posturographic measures of center-of-pressure, including sway area, velocity, and standard deviation in the mediolateral and anteroposterior directions under four conditions: static with the eyes open and eyes closed and dynamic voluntary sway in the mediolateral direction following a 30 Hz metronome with the eyes open and eyes closed. Paired t-tests were used to compare pre- and post-intervention data. Results: The intervention led to significant improvements in postural balance as measured using both posturographic measures (p < 0.05) and the Timed Up and Go test (p = 0.04). Conclusion: The virtual reality-based exergame physical activity protocol conducted at home, comprising eighteen 25 min sessions, effectively improves postural balance in older people. Full article

Using eye-tracking technology, the proposed study investigates how customers visually evaluate apples varieties and apple defects and how these evaluations affect their purchasing decisions. Three aspects were examined in this study: apple variety, defect severity, and cultural background. Idared, Golden Delicious Yellow, and Golden Delicious Green apple varieties with increasing degrees of bruising were shown to Chinese and Hungarian participants. The findings show that apple variety had no significant effect on gaze patterns, whereas cultural background had a considerable impact on visual attention measures. The most important element in grabbing and retaining customer attention was the severity of the defect, which was measured by area. The “Threshold of Rejection”, which characterizes consumer tolerance for Apple defects, is introduced in the study. Furthermore, a polynomial regression model was created to predict the probability of repurchasing an apple depending on its visual quality (level of bruising). These results provide useful information for marketing plans, quality assurance, and comprehending customer behavior in the fresh produce sector. Full article

Extended reality (XR) technologies—encompassing virtual reality (VR), augmented reality (AR), and mixed reality (MR)—are transforming cognitive assessment and training by offering immersive, interactive environments that simulate real-world tasks. XR enhances ecological validity while enabling real-time, multimodal data collection through tools such as galvanic skin response (GSR), electroencephalography (EEG), eye tracking (ET), hand tracking, and body tracking. This allows for a more comprehensive understanding of cognitive and emotional processes, as well as adaptive, personalized interventions for users. Despite these advancements, current XR applications often underutilize the full potential of multimodal integration, relying primarily on visual and auditory inputs. Challenges such as cybersickness, usability concerns, and accessibility barriers further limit the widespread adoption of XR tools in cognitive science and clinical practice. This review examines XR-based cognitive assessment and training, focusing on its advantages over traditional methods, including ecological validity, engagement, and adaptability. It also explores unresolved challenges such as system usability, cost, and the need for multimodal feedback integration. The review concludes by identifying opportunities for optimizing XR tools to improve cognitive evaluation and rehabilitation outcomes, particularly for diverse populations, including older adults and individuals with cognitive impairments. Full article

Ensuring the driver’s readiness to take over before a takeover request is issued by an autonomous driving system is crucial for a safe takeover. However, current takeover prediction models suffer from poor prediction accuracy and do not consider the time dependence of input features. In this regard, this study proposes a hybrid LSTM-BiLSTM-ATTENTION algorithm for driver takeover performance prediction. By building a takeover scenario and conducting experiments in the driving simulation experimental platform under the human–machine co-driving environment, the relevant state indicators in the 15 s per second before the takeover request is sent are extracted from three perspectives, namely, driver state, traffic environment, and personal attributes, as model inputs, and the level of takeover performance was labeled; the hybrid LSTM-BiLSTM-ATTENTION algorithm is used to construct a driver takeover performance prediction model and compare it with other five algorithms. The results show that the algorithm proposed in this study performs optimally, with an accuracy of 93.11%, a precision of 93.02%, a recall of 93.28%, and an F1 score of 93.12%. This study provides new ideas and methods for realizing the accurate prediction of driver takeover performance, and it can provide a decision basis for the safe design of self-driving vehicles. Full article

This paper presents a systematic review of the emerging applications of artificial intelligence (AI), Internet of Things (IoT), and sensor-based technologies in the diagnosis of autism spectrum disorder (ASD). The integration of these technologies has led to promising advances in identifying unique behavioral, physiological, and neuroanatomical markers associated with ASD. Through an examination of recent studies, we explore how technologies such as wearable sensors, eye-tracking systems, virtual reality environments, neuroimaging, and microbiome analysis contribute to a holistic approach to ASD diagnostics. The analysis reveals how these technologies facilitate non-invasive, real-time assessments across diverse settings, enhancing both diagnostic accuracy and accessibility. The findings underscore the transformative potential of AI, IoT, and sensor-based driven tools in providing personalized and continuous ASD detection, advocating for data-driven approaches that extend beyond traditional methodologies. Ultimately, this review emphasizes the role of technology in improving ASD diagnostic processes, paving the way for targeted and individualized assessments. Full article

The green vision rate of rural highway greening landscape is a key factor affecting the driver’s visual load. Based on this, this paper uses the eye tracking method to study the visual characteristics of drivers in different green vision environments on rural highways in Xianning County. Based on the HSV color space model, this paper obtains four sections of rural highway with a green vision rate of 10~20%, green vision rate of 20~30%, green vision rate of 30~40%, and green vision rate of 40~50%. Through the real car test, the pupil area, fixation time, saccade time, saccade angle, saccade speed, and other visual indicators of the driver’s green vision rate in each section were obtained. The visual load quantization model was combined with factor analysis to explore the influence degree of the green vision rate in each section on the driver’s visual load. The results show that the visual load of the driver in the four segments with different green vision rate is as follows: Z10~20% > Z20~30% > Z30~40% > Z40~50%. When the green vision rate is 10~20%, the driver’s fixation time becomes longer, the pupil area becomes larger, the visual load is the highest, and the driving is unstable. When the green vision rate is 40% to 50%, the driver’s fixation time and pupil area reach the minimum, the visual load is the lowest, and the driving stability is the highest. The research results can provide theoretical support for the design of rural highway landscape green vision rate and help to promote the theoretical research of traffic safety. Full article

To tackle the problems of power saturation and high energy consumption of the heavy-load servo system in a servo process, we propose a motion planning algorithm based on the stimuli-induced equilibrium point (SIEP), named the SIEP-MP algorithm. First, we explore the correlation between various modes of the bionic eye system and the heavy-load servo system through head-eye motion control theory and derive the core formula of the SIEP-MP algorithm from psychological field theory. Then, we design a speed loop of the heavy-load servo system by combining a speed controller and a disturbance observer. Furthermore, we create a position loop of the heavy-load servo system by combining a position controller and a feed-forward controller. We verify the low-pass filtering and range-limiting functions of the SIEP-MP algorithm by building the experimental platform, designing the target trajectory, and setting the control parameters. Experimental results demonstrate similar command filtering, elimination of power saturation, and energy-saving functions compared to low-pass filters, and the algorithm has a better mode-switching performance. The proposed SIEP-MP algorithm can ensure the optimal tracking performance of the heavy-load servo system in different modes through mode switching. Full article

This study introduces the Eye-tracking Translation Software (ETS), a system that leverages eye-tracking data and real-time translation to enhance reading flow for non-native language users in complex, technical texts. By measuring the fixation duration, we can detect moments of cognitive load, ETS selectively provides translations, maintaining reading flow and engagement without undermining language learning. The key technological components include a desktop eye-tracker integrated with a custom Python-based application. Through a user-centered design, ETS dynamically adapts to individual reading needs, reducing cognitive strain by offering word-level translations when needed. A study involving 53 participants assessed ETS’s impact on reading speed, fixation duration, and user experience, with findings indicating improved comprehension and reading efficiency. Results demonstrated that gaze-based adaptations significantly improved their reading experience and reduced cognitive load. Participants positively rated ETS’s usability and were noted through preferences for customization, such as pop-up placement and sentence-level translations. Future work will integrate AI-driven adaptations, allowing the system to adjust based on user proficiency and reading behavior. The study contributes to the growing evidence of eye-tracking’s potential in educational and professional applications, offering a flexible, personalized approach to reading assistance that balances language exposure with real-time support. Full article

Reading fluency depends on the typographic design. Letters can have different shapes that evoke different feelings in the reader and influence reading fluency. Previous studies that explored the link between typeface shape and taste and its impact on reading and readers’ attitudes mainly focused on shorter texts or individual words. In contrast, our study investigated how the taste (sweetness) attributed to the typeface is related to reading fluency and the pleasantness of the typeface during reading longer texts, and whether these relationships are the same in children and adult readers. We found that readers of both age groups perceived rounded letters as sweeter than angular letters. The perceived sweetness correlated positively with the pleasantness of the typeface and reading fluency. Younger readers showed a higher general rating of sweetness and a stronger relationship between the perceived sweetness and the pleasantness of the typeface than older, more experienced readers. This suggests that the sweeter and more pleasant the typeface is perceived to be, the faster it can be read. When fast processing of longer texts is required, we recommend the use of rounded typefaces with more organic shapes, including serif typefaces with some characteristics of old-style typefaces, rather than using angular, sans serif typefaces. Full article

With the increasing complexity of urban roads and rising traffic flow, traffic safety has become a critical societal concern. Current research primarily addresses drivers’ attention, reaction speed, and perceptual abilities, but comprehensive assessments of cognitive abilities in complex traffic environments are lacking. This study, grounded in cognitive science and neuropsychology, identifies and quantitatively evaluates ten cognitive components related to driving decision-making, execution, and psychological states by analyzing video footage of drivers’ actions. Physiological data (e.g., Electrocardiogram (ECG), Electrodermal Activity (EDA)) and non-physiological data (e.g., Eye Tracking (ET)) are collected from simulated driving scenarios. A dual-branch Transformer network model is developed to extract temporal features from multimodal data, integrating these features through a weight adjustment strategy to predict driving-related cognitive abilities. Experiments on a multimodal driving dataset from the Computational Physiology Laboratory at the University of Houston, USA, yield an Accuracy (ACC) of 0.9908 and an F1-score of 0.9832, confirming the model’s effectiveness. This method effectively combines scale measurements and driving behavior under secondary tasks to assess cognitive abilities, providing a novel approach for driving risk assessment and traffic safety strategy development. Full article

Background/Objectives: One of the key challenges in autism is early diagnosis. Early diagnosis leads to early interventions that improve the condition and not worsen autism in the future. Currently, autism diagnoses are based on monitoring by a doctor or specialist after the child reaches a certain age exceeding three years after the parents observe the child’s abnormal behavior. Methods: The paper aims to find another way to diagnose autism that is effective and earlier than traditional methods of diagnosis. Therefore, we used the Eye Gaze fixes map dataset and Eye Tracking Scanpath dataset (ETSDS) to diagnose Autistic Spectrum Disorder (ASDs), while a subset of the ETSDS was used to recognize autism scores. Results: The experimental results showed that the higher accuracy rate reached 96.1% and 98.0% for the hybrid model on Eye Gaze fixes map datasets and ETSDS, respectively. A higher accuracy rate was reached (98.1%) on the ETSDS used to recognize autism scores. Furthermore, the results showed the outperformer for the proposed method results compared to previous works. Conclusions: This confirms the effectiveness of using artificial intelligence techniques in diagnosing diseases in general and diagnosing autism, in addition to the need to increase research in the field of diagnosing diseases using advanced techniques. Full article

As the primary setting for students’ daily life and learning, university campuses are facing a growing concern about the impact of increased stress on students’ emotional well-being. The sound environment plays a critical role in affecting students’ mental health, learning efficiency, and overall well-being. However, research on the influence of campus soundscapes on students’ emotions is limited, and the mechanisms behind these effects remain to be explored. This study, using the Qishan Campus of Fuzhou University as a case, investigates the impact of campus soundscapes on students’ emotional perception and restorative effects. Four typical functional areas (academic zone (ACZ), residential zone (RDZ), recreational zone (RCZ), and administrative zone (ADZ)) were selected to analyze the effects of natural and artificial sounds on students’ emotions and physiological states. Based on EEG, eye tracking, sound level measurements, and questionnaire surveys, a one-way repeated measures ANOVA was used to assess students’ emotional arousal, valence, and physiological restoration under different soundscape conditions. The results showed that natural sounds, such as the sound of wind-blown leaves and flowing water, significantly improved students’ emotions and restorative effects, while artificial noises like construction sounds and traffic noise had negative impacts. Additionally, subjective perceptions of soundscape restoration were positively correlated with arousal, valence, and acoustic comfort, and negatively correlated with gaze frequency and pupil size. The findings provide a theoretical foundation for optimizing campus soundscape design and highlight the importance of natural sounds in enhancing students’ mental health and academic environment. Full article

The technological leap in the digital age has triggered a higher demand for emotional experiences. Since vision has long been recognized as the most important source of information for people to perceive the city, the visual characteristics of the urban built environment have an important impact on the emotional experience it creates. This study takes the facades and external environments of the representative urban public building category, museums, as the research objects, to explore how different types of built environment elements that make up the museum’s facade and surrounding environment affect the people’s emotional experience by affecting the urban visual quality. Tobii Pro Fusion devices and emotion scales are used for the collection of multimodal data. A total of 298 participants aged between 20 and 25 were recruited to participate in the experiment voluntarily and 229 valid data were finally obtained. The results show that different types of museum facades and external environmental elements have different effects on visual quality and people’s emotional experience: (1) Interactive elements show the most significant impact on visual quality and emotional experience. (2) The impact of artificial elements on visual quality is related to their size and spatial composition on the museum facade. When artificial elements have uniqueness, regionality, and symbolism associated with the museum, they are more likely to trigger people’s emotional experiences. (3) Visual quality is significantly correlated with people’s emotional experience through both preconscious and conscious emotional cognition. The results reveal the impact of different types and characteristics of built environment elements on the visual quality of the urban environment and proves the important role of visual quality in students’ emotional experience, further illustrating that designing and creating a good visual environment is conducive to promoting a humanistic urban environment. Meanwhile, this study also promotes a method of urban visual quality research and evaluation from an emotional perspective, providing a more scientific and objective way for the intervention of “emotions” in built environment research. Full article

The visual perception of interior architecture plays a crucial role in real estate marketing, influencing the decisions of buyers, interior architects, and real estate agents. These professionals rely on personal assessments of space, often drawing from their experience of using décor to influence how interiors are perceived. While intuition may validate some approaches, this study explores an under-examined aspect of interior design using a mobile eye-tracking device. It investigates how decorative elements affect spatial perception and offers insights into how individuals visually engage with interior environments. By integrating décor into the analysis of interior architecture, this study broadens the traditional scope of the field, demonstrating how décor composition can modulate spatial perception using eye-tracking technology. Results show that effective styling can redirect attention from key architectural elements, sometimes causing them to be overlooked during the critical first moments of observation commonly known as the “first impression”. These findings have important implications for interior design practice and architectural education. Full article

This study examines the relationship between cosmetic packaging color and consumer attention by analyzing changes in pupil size using eye-tracking technology. A controlled experiment with 25 participants (mean age: 24.7 ± 3 years, 14 males and 11 females) was conducted to investigate the impact of eight packaging colors (black, white, blue, yellow, orange, turquoise, pink, and sky blue) on pupil dilation during gaze fixation and movement. Pupil size data were analyzed using SAS 9.4, with T-tests used to determine significant differences across colors. The results revealed that pink packaging elicited significantly larger pupil sizes during fixation, indicating heightened attention, while black, white, blue, and orange led to smaller pupil sizes when fixated, suggesting greater focus on the surrounding environment rather than the packaging. In contrast, yellow and turquoise exhibited no significant differences in pupil size during fixation and movement. Additionally, the study highlights that gaze fixation is a more meaningful indicator of attention than gaze movement, as fixation reflects focused interest in specific stimuli. The findings suggest that pink packaging is most effective in attracting consumer attention, while black, white, blue, and orange are better suited for enhancing focus on the surrounding environment. These insights emphasize the growing importance of packaging design in influencing consumer behavior, particularly through color selection. This study contributes to marketing practices by providing empirical evidence for the visual impact of packaging colors, offering valuable guidance for cosmetic industry practitioners. Future research should expand sample sizes and explore additional packaging attributes, such as shape and material, to derive more comprehensive insights. Full article