Search Results (461)

Adaptive technologies have become more sophisticated with Artificial Intelligence (AI) and the Internet of Things (IoT), providing world-changing solutions to help people living with disabilities live better lives. In this article, we discuss the potential of AI and IoT to address issues related to Down Syndrome (DS), Autism Spectrum Disorder (ASD), Mobility Impairment (MI), Hearing Impairment (HI), Attention-Deficit/Hyperactivity Disorder (ADHD), and Visual Impairment (VI). In addition, we propose an analytical framework for evaluating AI and IoT disability assistance prototypes. The framework consists of three different layers: Disability Monitoring, Disability Analysis, and Disability Assistance layers. In each layer, a set of dimensions are identified (e.g., technology, data, security, customization, and response time) and used as criteria to evaluate the research prototypes. Moreover, we evaluate 30 representative AI and IoT disability assistance research prototypes published from 2020 to 2024. The evaluation offers valuable insights into the new strategies, technologies, and approaches that will define AI and IoT disability support in the future. While these technologies have promise in enabling access, autonomy, and interfacing, there remain major open research issues such as data privacy, security, cost, scalability, and real-time response. Furthermore, we discuss future research directions to tackle these issues and allow the people with disabilities community to enhance their quality of life and be more independent. Full article

People with visual impairments (VIPs) can participate in orientation and mobility (O&M) training to learn how to navigate to their desired goal locations. During O&M training, personal wayfinding preferences with regard to cue use and wayfinding strategy choice are taken into account. However, there is still a lack of clarity about which factors shape VIPs’ wayfinding experiences and how. Background/Objectives: In this study, we mapped individual differences in preferred sensory modality (both orientation- and mobility-related), and classified which personal and environmental factors are relevant for these preferences. Methods: To this end, interviews were conducted with eleven Dutch VIPs whose impairment varied in onset, ontology, and severity. Results: We concluded from our thematic analysis that hearing is the most important sensory modality to VIPs for orientation purposes, although it varies per person how and how often other resources are relied upon (i.e., other sensory modalities, existing knowledge of an environment, help from others, or navigational aids). Additionally, environmental factors such as weather conditions, crowdedness, and familiarity of the environment influence if, how, and which sensory modalities are employed. These preferences and strategies might be mediated by individual differences in priorities and needs pertaining to energy management. Conclusions: We discuss how the current findings could be of interest to orientation and mobility instructors when choosing a training strategy for individual clients. Full article

Background/Objectives: People with visual impairments can participate in orientation and mobility (O&M) training to learn how to navigate to their desired destinations. Instructors adapt their approach to each individual client. However, assessments of client characteristics and resulting instructional adaptations are not standardised and may therefore vary. This study aimed to identify which individual differences instructors consider during O&M training and why. Methods: We conducted semi-structured qualitative interviews with 10 O&M instructors. Participants were asked to describe how they prepare for a training trajectory, and to describe a route they taught a specific client. Thematic analysis was used to determine instructional choices and the relevant client-specific factors. Results: We observed a common four-step instructional process in which clients are taught to notice, interpret, act upon, and anticipate relevant sensory cues until a destination is reached. Four main themes captured the individual differences impacting this process: Sensory modalities, Capacities and limits, Personal contextual characteristics, and Training approach. Conclusions: Instructors perceive route learning to be shaped by clients’ sensory abilities (even fluctuating within sensory modalities), mental and physical capacities (especially concentration and energy), and personal characteristics (especially age and anxiety). The dynamic social context in which training takes place (e.g., the instructor–client relationship) is shaped by individual differences between both clients and instructors. We speculate that trust-related themes (e.g., building confidence) may explain why certain client characteristics are emphasised by instructors, as they are associated with training outcomes. Full article

One of the key goals of the 2030 Agenda for Sustainable Development is to create inclusive, safe, resilient, and sustainable cities. A fundamental aspect of this goal is ensuring barrier-free mobility and access to public spaces, particularly for people with physical and visual impairments, seniors, and others with limited mobility. This paper discusses the statistical background of persons with disabilities in the Czech Republic and identifies the main obstacles they face in independent movement and spatial orientation. Based on current data, regulations, and practical observations, the paper outlines principles and design recommendations that support accessible and inclusive public environments. These include both physical modifications for mobility and tactile or visual systems that assist in independent navigation for visually impaired users. Full article

Neurofibromatosis type 1 (NF1) is an inherited, autosomal dominant syndrome that affects about 1 in every 3000 people worldwide. Early tumor detection is crucial for surveillance and intervention, especially given the potential for serious complications, including visual impairment, skeletal deformities, and malignancy. Therefore, it is essential for pediatricians and other healthcare professionals who provide care to these patients to be aware of all signs, treatments, and management strategies to deliver the best possible care. This study aims to develop a consensus for the diagnosis, treatment, and management of benign and malignant tumors associated with pediatric patients with NF1. Delphi methodology was used to achieve consensus among experts on the diagnostic accuracy, therapeutic efficacy, safety, and surveillance of pediatric patients with NF1. The consensus made 24 recommendations: gliomas in the optic pathway—6 statements, non-optical gliomas—2 statements, plexiform neurofibromas—5 statements, malignant peripheral nerve sheath tumors (MPNST)—6 statements, melanoma—1 statement, juvenile myelomonocytic leukemia (JMML)—1 statement, pheochromocytoma and paraganglioma—2 statements, and gastrointestinal stromal tumors (GIST)—1 statement. This consensus represents the first Brazilian recommendations on malignant and benign tumors in pediatric patients with NF1, providing a framework to standardize and optimize the clinical application for this disease. Full article

Visual impairment (VI) affects over two billion people globally, with prevalence increasing due to preventable conditions. To address mobility and navigation challenges, this study presents a multi-platform, multi-sensor Electronic Travel Aid (ETA) integrating a combination of ultrasonic, LiDAR, and vision-based sensing across head-, torso-, and cane-mounted nodes. Grounded in orientation and mobility (OM) principles, the system delivers context-aware haptic and auditory feedback to enhance perception and independence for users with VI. The ETA employs a hardware–software co-design approach guided by proxemic theory, comprising three autonomous components—Glasses, Belt, and Cane nodes—each optimized for a distinct spatial zone while maintaining overlap for redundancy. Embedded ESP32 microcontrollers enable low-latency sensor fusion providing real-time multi-modal user feedback. Static and dynamic experiments using a custom-built motion rig evaluated detection accuracy and feedback latency under repeatable laboratory conditions. Results demonstrate millimetre-level accuracy and sub-30 ms proximity-to-feedback latency across all nodes. The Cane node’s dual LiDAR achieved a coefficient of variation at most 0.04%, while the Belt and Glasses nodes maintained mean detection errors below 1%. The validated tri-modal ETA architecture establishes a scalable, resilient framework for safe, real-time navigation—advancing sensory augmentation for individuals with VI. Full article

This paper presents a systematic literature review on the use of machine learning (ML) for developing adaptive accessible user interfaces (AUI) with emphasis on applications in emerging technologies such as augmented and virtual reality (AR/VR). The review, conducted according to the PRISMA 2020 methodology, included 57 studies published between 2018 and 2025. Among them we identified 24 papers explicitly describing ML-based adaptive interface solutions. Supervised learning was dominant (83% of studies) with only isolated cases of reinforcement, generative AI, and fuzzy–NLP hybrid paradigms. The analysis of all 57 papers included in review revealed that adaptive interfaces dominate current research (65%), while intelligent or hybrid systems remain less explored. Mobile platforms were the most prevalent implementation environment (25%), followed by web-based (19%) and multi-platform systems (11%), with immersive (VR/XR) and IoT contexts still emerging. Among 43 studies addressing accessibility, the most were focused on visual impairments (33%), followed by cognitive and learning disorders (25%). The results of this review can inform the creation of accessibility guidelines in emerging AR and VR applications and support the development of inclusive solutions that benefit people with disabilities, older adults, and the general population. The main contribution of this paper lies in identifying existing gaps in the integration of accessibility and Universal Design principles into ML-based adaptive systems and in proposing a new AUI model that enables user-approved, time-delayed adaptations through machine learning, balancing autonomy, personalization, and user control. Full article

Human social life is dependent on the ability of individuals to understand other people as separate cognitive agents, capable of thought independent from themselves. This understanding and the attribution of mental states to others, often called Theory of Mind (ToM), is a naturally developing ability. Individuals with Autism Spectrum Disorder (ASD) seem to experience difficulty in attributing mental states to others, and this may explain impaired social interaction and communication behaviors. The Frith-Happé animations are short videos designed to test ToM development by varying the degree of intentionality present and asking viewers to describe their interpretation. The present study recorded eye movements and verbal descriptions in 15 children and 23 young adults with ASD and 20 and 15 typically developing (TD) peers, respectively. The results showed eye movement patterns in ASD and TD children did not differ significantly, but both groups differed from adults in their verbal responses. Children with Autism Spectrum Disorder (ASD) produced shorter (F(1,60) = 5.8, p = 0.019) and less appropriate (F(1,60) = 4.4, p = 0.04) ToM descriptions than TD peers, although their eye movement patterns were comparable to those of TD children. While low-level visual processing may be intact in individuals with ASD, challenges with social cognition and verbal expression may remain. Full article

The PATCULT 3D project was developed during the 2024–2025 academic year as part of the Degree in Geoinformation and Geomatics at the University of Salamanca (Spain) as a service-learning initiative designed to integrate technical training with social commitment. The main objective was to provide students with practical experience in photogrammetry, 3D laser scanning, and additive manufacturing applied to the documentation and reproduction of cultural heritage. A particular feature of the project was its collaboration with the Spanish National Organization of the Blind (ONCE), placing accessibility for people with visual impairments as a central methodological tenet. Students developed tactile replicas of heritage assets from the province of Ávila, applying universal design principles and implementing Braille-based information systems to ensure fully inclusive modes of cultural engagement. In addition to the digital preservation of heritage, the activity reinforced students’ technical skills (covering data acquisition, 3D modeling, mesh refinement, and digital fabrication workflows) while fostering transversal competences such as teamwork, communication, critical reflection, and social awareness. The evaluation instruments demonstrated high levels of motivation and satisfaction, as well as a growing sensitivity to the social responsibilities of geomatics. The project is explicitly aligned with Sustainable Development Goals 4, 9, 10, and 11, thereby contributing to quality education, technological innovation, the reduction in structural inequalities, and the fostering of inclusive and sustainable communities. Overall, the experience illustrates how the integration of digital technologies with service-learning can strengthen academic training and, at the same time, generate measurable social value by making cultural heritage more accessible. Full article

Safe and efficient building evacuation for heterogeneous populations, particularly individuals with disabilities, remains a critical challenge in emergency management. This study proposes a hybrid evacuation framework that integrates Floor Field Cellular Automaton (FFCA) with reinforcement learning, specifically a Deep Q-Network (DQN), to enhance adaptive decision-making in dynamic and complex environments. The model incorporates velocity heterogeneity, friction-based conflict resolution, and real-time path planning to capture diverse mobility capabilities and interactions among evacuees. Simulation experiments were conducted under varying population densities, walking speeds, and exit configurations, considering four types of occupant groups: able-bodied individuals, wheelchair users, and people with visual or hearing impairments. The results demonstrate that the DQN-enhanced model consistently outperforms the conventional SFF + DFF approach, achieving significant reductions in evacuation time, particularly under high-density and reduced-speed scenarios. Notably, the DQN dynamically adapts evacuation paths to mitigate congestion, thereby improving both system efficiency and the safety of vulnerable groups. These findings highlight the potential of combining CA-based environmental modeling with reinforcement learning to develop adaptive and inclusive evacuation strategies. The proposed framework provides practical insights for designing evacuation protocols and intelligent navigation systems in public buildings. Future work will extend the proposed FFCA + DQN framework to more complex and realistic environments, including multi-exit and multi-level buildings, and further integrate multi-agent reinforcement learning (MARL) architectures to enable decentralized adaptation among heterogeneous evacuees. Furthermore, lightweight DQN variants and distributed training schemes will be explored to enhance computational scalability, while empirical data from evacuation drills and real-world case studies will be used for model calibration and validation, thereby improving predictive accuracy and generalizability. Full article

In recent decades, various assistive technologies have emerged to support visually impaired individuals. However, there remains a gap in terms of solutions that provide efficient, universal, and real-time capabilities by combining robust object detection, robust communication, continuous data processing, and emergency signaling in dynamic environments. In many existing systems, trade-offs are made in range, latency, or reliability when applied in changing outdoor or indoor scenarios. In this study, we propose a comprehensive framework specifically tailored for visually impaired people, integrating computer vision, edge computing, and a dual-channel communication architecture including low-power wide-area network (LPWAN) technology. The system utilizes the YOLOv5 deep-learning model for the real-time detection of obstacles, paths, and assistive tools (such as the white cane) with high performance: precision 0.988, recall 0.969, and mAP 0.985. Implementation of edge-computing devices is introduced to offload computational load from central servers, enabling fast local processing and decision-making. The communications subsystem uses Wi-Fi as the primary link, while a LoRaWAN channel acts as a fail-safe emergency alert network. An IoT-based panic button is incorporated to transmit immediate location-tagged alerts, enabling rapid response by authorities or caregivers. The experimental results demonstrate the system’s low latency and reliable operations under varied real-world conditions, indicating significant potential to improve independent mobility and quality of life for visually impaired people. The proposed solution offers cost-effective and scalable architecture suitable for deployment in complex and challenging environments where real-time assistance is essential. Full article

Visual impairment impacts nearly half a billion people globally. Corrective glasses, artificial lens replacement, and medical management have markedly improved the management of diseases inherent to the eye, such as refractive errors, cataracts, and glaucoma. However, therapeutic strategies for retinopathies, optic nerve damage, and distal optic pathways remain limited. The complex optic apparatus comprises multiple neural structures that transmit information from the retina to the diencephalon to the cortex. Over the last few decades, innovations have emerged to address the loss of function at each step of this pathway. Given the retina’s lack of regenerative potential, novel treatment options have focused on replacing lost retinal cell types through cellular replacement with stem cells, restoring lost gene function with genetic engineering, and imparting new light sensation capabilities with optogenetics. Additionally, retinal neuroprosthetics have shown efficacy in restoring functional vision, and neuroprosthetic devices targeting the optic nerve, thalamus, and cortex are in early stages of development. Non-invasive neuromodulation has also shown some promise in modulating the visual cortex. Recently, the first in-human whole-eye transplant was performed. While functional vision was not restored, the feasibility of such a transplant with viable tissue graft at one year was demonstrated. Subsequent studies are now focused on guidance cues for axonal regeneration past the graft site to reach the lateral geniculate nucleus. Although the methods discussed above have shown promise individually, improvements in vision have been modest at best. Achieving the goal of restoration of functional vision will clearly require further development of cellular therapies, genetic engineering, transplantation, and neuromodulation. A concerted multidisciplinary effort involving scientists, engineers, ophthalmologists, neurosurgeons, and reconstructive surgeons will be necessary to restore vision for patients with vision loss from these challenging pathologies. In this expert review article, we describe the current literature in visual neurorestoration with respect to cellular therapeutics, genetic therapies, optogenetics, neuroprosthetics, non-invasive neuromodulation, and whole-eye transplant. Full article

Due to a complex of factors, visually impaired people are facing difficulties and increased risks during fire emergencies and evacuations from different types of buildings. Even if a lot of studies have been conducted to improve the mobility and autonomy of people with visual impairment during emergency evacuation processes, these offer only partial solutions, especially in the presence of uncertainties characteristic of fire evolution. Aiming for a more comprehensive approach to the safe evacuation of people with visual impairments, this paper proposes a support system that integrates innovative aspects related to the architecture of the application, modeling and simulation methods, and experimental realization. The system is decentralized, capable of anticipating possible fire extensions and determining, in real-time, new corresponding evacuation routes. The overall design complies with the standard norms in emergency situations. Two models, one developed in Stateflow and the other based on Delay Time Petri Nets (DTPN), were constructed to describe the dynamic behavior of the system in the presence of unexpected events that can change the initial recommended evacuation path. To test the functionality and efficiency of the proposed system, the conditions created by potential fire sources were simulated as a part of realistic scenarios. Tests were conducted with visually impaired people. Simulation and prototype testing showed that the presented system can improve evacuation times, achieving a measurable gain compared to scenarios where there is no information regarding fire evolution. Full article

Background/Objectives: Nutritional disorders are common conditions in older people. This study aimed to determine nutritional disorders in a Mediterranean cohort of nursing home residents without cognitive or functional impairment. Methods: A multicentre cross-sectional observational study was conducted in 10 Spanish geriatric centres. Socio-health, clinical, and laboratory data were recorded from the participants’ medical records. The Mini-Nutritional Assessment (MNA) and Global Leadership Initiative in Nutrition (GLIM) diagnostic criteria [weight loss and serum C-reactive protein (CRP)] were used. Frailty risk was assessed using the FRAIL questionnaire. Anthropometric parameters [body mass index, weight loss, triceps skinfold thickness (TSF), muscle mass circumference (MAMC), and calf-circumference] were evaluated. Body composition [hydration pattern, fat-free mass, muscle mass (MM), fat mass, and phase angle (PhA)] was measured by bioelectrical impedance analysis. Laboratory parameters, such as haemoglobin, total lymphocyte count, serum albumin, transferrin, and CRP, were recorded. Participants were classified into two groups: the disease-related malnutrition (DRM) group and the no-DRM group. Using multivariate regression analysis, predictive factors for nutritional status were tested. Results: Among 340 participants, 63.2% were over 85 years old, 28.2% were men, and the median length of stay was 24 months (range: 6–119). Nutritional risk or malnutrition, as assessed by the MNA, was present in 60.8% of the residents. DRM was diagnosed in 39.4%, and frailty risk was diagnosed in 57.6%. Older adults with DRM had significantly lower MAMC, calfcircumference, MM, and serum albumin, as well as higher CRP concentrations compared with their No-DRM counterparts (all, at least, p < 0.05). The frailty risk (OR = 3.317), MM (OR = 0.732), PhA (OR = 0.033), serum albumin (OR = 0.070), and EuroQol visual analogue scale (OR = 0.961) were risk predictors of DRM in nursing home residents. Conclusions: This study supports the importance of conducting comprehensive nutritional assessments to ensure the earliest recognition of nutrition disorders in nursing homes. Older adults with DRM had greater unintentional weight loss, inflammation, and a high risk of frailty, as well as reduced MM, compared to those without DRM. Subclinical low-grade systemic inflammation is a risk factor for DRE and functional decline in older adults living in nursing homes. The generalisation of the study results is limited to institutionalised older adults without cognitive impairment who are clinically stable and functionally independent. Full article

People with intellectual disability and visual impairment often have difficulties in accessing leisure events, engaging in cognitive activities, and performing physical exercise. The present study assessed a program aimed at helping six adults with moderate or moderate-to-mild intellectual disability and blindness in each of the aforementioned areas. The program relied on the use of a technology system involving a smartphone, which was supplied with Internet connection and fitted with the Live Transcribe and MacroDroid applications. These applications were set up to (a) enable the participants to use verbal utterances to successfully access preferred songs and comic sketches (leisure events) and answer series of verbal questions (cognitive activity) automatically presented to them, and (b) enable the smartphone to verbally guide the participants’ performance of series of body movements (physical exercise). The program was introduced according to a nonconcurrent multiple baseline design across participants. The intervention was divided into two phases, which included 17–33 and 39–48 sessions, respectively. The results showed that the participants’ baseline performance (without the support of the system) was generally poor. During the intervention with the system, all participants succeeded in accessing the music or comic events available, satisfactorily answering series of questions, and performing series of body movements. The Percentage of Nonoverlapping Data and the Tau (novlap) methods used to compare baseline and intervention performance produced indices of 1 for all participants (confirming the strong impact of the intervention). These results, which need replication to establish their generality, suggest that the technology system might represent a useful tool for helping people like the participants of this study. Full article