Introduction: The incorporation of information technology into teaching has gradually increased the diversity and feasibility of using extended reality (XR) in learning. This study explored professionals’ intention of integrating XR to train vocational skills of individuals with ID by using the technology acceptance model framework.

Methods: This study recruited 44 professionals working in the field of vocational training for individuals with ID. The study utilized the “Extended Reality Vocational Skills Training System”, which was designed by the research team. Participants were first introduced to the system, completed the task of product arrangement, and filled out the questionnaire.

Results: The mean score of each concept was from 3.34 to 4.01. The scores are ranked in descending order as perceived usefulness (PU), attitude to use (AT), behavior intention (BI), and perceived ease of use (PEOU). Based on the PLS analysis, PU and PEOU explained 68.8% variance in AT, and the overall model explained 66.3% of the total variance of BI.

Conclusion: According to the results, the professionals expressed a positive attitude toward using XR and agreed that using XR to train the vocational skills of individuals with ID is a great idea. AT is an important factor which not only affects BI directly, but also serves as a mediating factor of PU and PEOU to BI. In addition, PU and PEOU had positive effects on AT. When designing new technology, it is essential to consider the needs of users.

Our project aims to create a panic diary that not only records panic attacks but also serves as a journal for applying breathing exercises, mindfulness and distraction techniques, and reviewing existing diaries. Anxiety problems are becoming increasingly common in our fast-paced world, which can significantly impact quality of life. The exercises included in the application are designed to help manage stress. The program is accessible to all Android phone users as panic attacks can affect anyone, regardless of gender or age. It was developed using the Java programming language in Android Studio. During the development process, we consulted with individuals who have anxiety disorders, as well as psychiatrists.

Training individuals with special needs for cleaning activities presents unique challenges due to diverse learning styles and accessibility requirements. Augmented Reality (AR) technology offers a promising solution by providing interactive, immersive, and customizable training experiences. This paper presents the development and evaluation of an AR application tailored for training cleaning activities specifically designed to accommodate the needs of individuals with special needs. The application utilizes AR to provide personalized guidance, adapt training content to individual capabilities, and enhance engagement through interactive simulations. We discuss the design considerations, implementation details, and user feedback gathered through a pilot study involving individuals with various special needs. Results indicate that the AR application significantly improves the accessibility and effectiveness of training for cleaning activities, thereby empowering individuals with special needs to develop essential life skills and achieve greater independence.

The paper describes a low-cost system incorporating galvanic skin response, heart rate, and respiratory rate sensors, allowing for emotion classification based on the valence-arousal model. The system lays the groundwork for an innovative device capable of detecting fear during aggressive situations and automatically triggering an SOS. Tests in a controlled environment by visually stimulating emotions demonstrate the reliability of the low-cost sensors.

Operating a motorized wheelchair poses inherent risks and demands substantial cognitive effort to achieve effective environmental awareness. Consequently, individuals with severe disabilities face heightened risk, leading to diminished social engagement which impacts their overall well-being. Therefore, we have developed a collaborative driving system for obstacle avoidance based on a trained reinforcement learning (RL) algorithm. The RL is based on a TD3 agent which has been trained in a simulated environment. The system interfaces with the user through a joystick, capturing the desired direction and speed, while a lidar positioned in front of the wheelchair provides information about obstacle distribution. Taking both inputs into account, the system generates a pair of forward and rotational speeds that prioritize obstacle avoidance while closely aligning with the user's commands. Preliminary validation through simulations involved comparing the RL algorithm with the absence of an assistive system. The results are promising, showcasing that the RL algorithm reduces collisions without imposing constraints on the desired speed. Ongoing research is dedicated to expanding tests and conducting comparisons with traditional obstacle avoidance algorithms.

Focused work on computers takes a central role in today’s workplace. Concentration is often disturbed, especially in offices with a high noise level. For this reason, ambient noise is often suppressed by using headphones with ANC or masking, thus masking disturbing conversations from colleagues, for example. This leads to isolation in the workplace and, at the same time, people with headphones are often perceived as isolating themselves. In contrast, EN ISO 10075-2:2000 describes that social interaction plays an important role in the workplace, for example, to avoid monotony. Effective solutions need to be found to build bridges between these opposites, allowing both focused work and the opportunity for social interaction. To achieve this and to be able to mediate effectively between the person addressing and the person being addressed, it is essential to analyze the context. We approach this analysis within the paper based on observations and interviews in the training context of autistic people. The resulting contextual information forms a first step towards the development of systems that support communication reception for further elaboration.