NeoSLAM: Long-Term SLAM Using Computational Models of the Brain.

Simultaneous Localization and Mapping (SLAM) is a fundamental problem in the field of robotics, enabling autonomous robots to navigate and create maps of unknown environments. Nevertheless, the SLAM methods that use cameras face problems in maintaining accurate localization over extended periods across various challenging conditions and scenarios. Following advances in neuroscience, we propose NeoSLAM, a novel long-term visual SLAM, which uses computational models of the brain to deal with this problem. Inspired by the human neocortex, NeoSLAM is based on a hierarchical temporal memory model that has the potential to identify temporal sequences of spatial patterns using sparse distributed representations. Being known to have a high representational capacity and high tolerance to noise, sparse distributed representations have several properties, enabling the development of a novel neuroscience-based loop-closure detector that allows for real-time performance, especially in resource-constrained robotic systems. The proposed method has been thoroughly evaluated in terms of environmental complexity by using a wheeled robot deployed in the field and demonstrated that the accuracy of loop-closure detection was improved compared with the traditional RatSLAM system.

Epigenetic repression of Wnt receptors in AD: a role for Sirtuin2-induced H4K16ac deacetylation of Frizzled1 and Frizzled7 promoters.

Growing evidence supports a role for deficient Wnt signalling in Alzheimer's disease (AD). First, the Wnt antagonist DKK1 is elevated in AD brains and is required for amyloid-ß-induced synapse loss. Second, LRP6 Wnt co-receptor is required for synapse integrity and three variants of this receptor are linked to late-onset AD. However, the expression/role of other Wnt signalling components remain poorly explored in AD. Wnt receptors Frizzled1 (Fzd1), Fzd5, Fzd7 and Fzd9 are of interest due to their role in synapse formation/plasticity. Our analyses showed reduced FZD1 and FZD7 mRNA levels in the hippocampus of human early AD stages and in the hAPPNLGF/NLGF mouse model. This transcriptional downregulation was accompanied by reduced levels of the pro-transcriptional histone mark H4K16ac and a concomitant increase of its deacetylase Sirt2 at Fzd1 and Fzd7 promoters in AD. In vitro and in vivo inhibition of Sirt2 rescued Fzd1 and Fzd7 mRNA expression and H4K16ac levels at their promoters. In addition, we showed that Sirt2 recruitment to Fzd1 and Fzd7 promoters is dependent on FoxO1 activity in AD, thus acting as a co-repressor. Finally, we found reduced levels of SIRT2 inhibitory phosphorylation in nuclear samples from human early AD stages with a concomitant increase in the SIRT2 phosphatase PP2C. This results in hyperactive nuclear Sirt2 and favours Fzd1 and Fzd7 repression in AD. Collectively, our findings define a novel role for nuclear hyperactivated SIRT2 in repressing Fzd1 and Fzd7 expression via H4K16ac deacetylation in AD. We propose SIRT2 as an attractive target to ameliorate AD pathology.

Inertial Sensors for Hip Arthroplasty Rehabilitation: A Scoping Review.

The objective of this scoping review is to characterize the current panorama of inertia sensors for the rehabilitation of hip arthroplasty. In this context, the most widely used sensors are IMUs, which combine accelerometers and gyroscopes to measure acceleration and angular velocity in three axes. We found that data collected by the IMU sensors are used to analyze and detect any deviation from the normal to measure the position and movement of the hip joint. The main functions of inertial sensors are to measure various aspects of training, such as speed, acceleration, and body orientation. The reviewers extracted the most relevant articles published between 2010 and 2023 in the ACM Digital Library, PubMed, ScienceDirect, Scopus, and Web of Science. In this scoping review, the PRISMA-ScR checklist was used, and a Cohen's kappa coefficient of 0.4866 was applied, implying moderate agreement between reviewers; 23 primary studies were extracted from a total of 681. In the future, it will be an excellent challenge for experts in inertial sensors with medical applications to provide access codes for other researchers, which will be one of the most critical trends in the advancement of applications of portable inertial sensors for biomechanics.

Activity Recognition for Ambient Assisted Living with Videos, Inertial Units and Ambient Sensors.

Worldwide demographic projections point to a progressively older population. This fact has fostered research on Ambient Assisted Living, which includes developments on smart homes and social robots. To endow such environments with truly autonomous behaviours, algorithms must extract semantically meaningful information from whichever sensor data is available. Human activity recognition is one of the most active fields of research within this context. Proposed approaches vary according to the input modality and the environments considered. Different from others, this paper addresses the problem of recognising heterogeneous activities of daily living centred in home environments considering simultaneously data from videos, wearable IMUs and ambient sensors. For this, two contributions are presented. The first is the creation of the Heriot-Watt University/University of Sao Paulo (HWU-USP) activities dataset, which was recorded at the Robotic Assisted Living Testbed at Heriot-Watt University. This dataset differs from other multimodal datasets due to the fact that it consists of daily living activities with either periodical patterns or long-term dependencies, which are captured in a very rich and heterogeneous sensing environment. In particular, this dataset combines data from a humanoid robot's RGBD (RGB + depth) camera, with inertial sensors from wearable devices, and ambient sensors from a smart home. The second contribution is the proposal of a Deep Learning (DL) framework, which provides multimodal activity recognition based on videos, inertial sensors and ambient sensors from the smart home, on their own or fused to each other. The classification DL framework has also validated on our dataset and on the University of Texas at Dallas Multimodal Human Activities Dataset (UTD-MHAD), a widely used benchmark for activity recognition based on videos and inertial sensors, providing a comparative analysis between the results on the two datasets considered. Results demonstrate that the introduction of data from ambient sensors expressively improved the accuracy results.

Swarm Robotics: A Perspective on the Latest Reviewed Concepts and Applications.

Known as an artificial intelligence subarea, Swarm Robotics is a developing study field investigating bio-inspired collaborative control approaches and integrates a huge collection of agents, reasonably plain robots, in a distributed and decentralized manner. It offers an inspiring essential platform for new researchers to be engaged and share new knowledge to examine their concepts in analytical and heuristic strategies. This paper introduces an overview of current activities in Swarm Robotics and examines the present literature in this area to establish to approach between a realistic swarm robotic system and real-world enforcements. First, we review several Swarm Intelligence concepts to define Swarm Robotics systems, reporting their essential qualities and features and contrast them to generic multi-robotic systems. Second, we report a review of the principal projects that allow realistic study of Swarm Robotics. We demonstrate knowledge regarding current hardware platforms and multi-robot simulators. Finally, the forthcoming promissory applications and the troubles to surpass with a view to achieving them have been described and analyzed.

Natural α,ß-unsaturated lactones inhibit neuropeptide-induced mast cell activation in an in vitro model of neurogenic inflammation.

INTRODUCTION: Mast cells are involved in not only inducing, but also maintaining neurogenic inflammation and neuropathic pain. In previous work, we have demonstrated that dehydroleucodine, xanthatin and 3-benzyloxymethyl-5H-furan-2-one inhibit rat peritoneal and human LAD2 mast cell degranulation induced by compound 48/80 and calcium ionophore A23187. However, the effect of these molecules on neuropeptide-induced mast cell activation has not been studied so far. OBJECTIVE: The aim of this study was to determine whether dehydroleucodine, xanthatin, and 3-benzyloxymethyl-5H-furan-2-one inhibit neuropeptide-induced mast cell activation. METHODS: This work is based on in vitro simulation of a neurogenic inflammation scenario involving neuropeptides and mast cells, to subsequently analyze potential therapeutic strategies for neuropathic pain. RESULTS: Neuromedin-N did not stimulate mast cell serotonin release but substance P and neurotensin did induce serotonin release from peritoneal mast cells in a dose-dependent manner. Mast cell serotonin release induced by substance P and neurotensin was inhibited by dehydroleucodine and xanthatin, but not by 3-benzyloxymethyl-5H-furan-2-one. The inhibitory potency of dehydroleucodine and xanthatin was higher than that obtained with the reference compounds, ketotifen and sodium chromoglycate, when mast cells were preincubated with dehydroleucodine before substance P incubation, and with dehydroleucodine or xanthatin before neurotensin incubation. CONCLUSIONS: These results are the first strong evidence supporting the hypothesis that dehydroleucodine and xanthatin inhibit substance P- and neurotensin-induced serotonin release from rat peritoneal mast cells. Our findings suggest, additionally, that these α,ß-unsaturated lactones could be of value in future pharmacological research related to inappropriate mast cell activation conditions such as neurogenic inflammation and neuropathic pain.

The first Portuguese National Health Examination Survey (2015): design, planning and implementation.

BACKGROUND: In Health Examination Surveys interview information is complemented with objective information, providing more accurate indicators than self-reported data. We report the study design, planning and implementation of the first Portuguese Health Examination Survey (INSEF). METHODS: INSEF was a cross-sectional population-based study representative at regional and national level. Individuals aged between 25 and 74 years old, residing in Portugal were selected from the national health users' registry through multi-stage stratified probabilistic sampling. Sample size was set at 4200 individuals. Data was collected in primary care units and included blood pressure, height, weight, hip and waist measurements, blood collection for lipid profile, HbA1c and blood count and a general health questionnaire. European HES procedures were followed. RESULTS: A total of 4911 individuals agreed to participate (43.9% participation rate). Participation rate varied by region, sex and age group, being lower in Lisbon and Tagus Valley (32.8%), for men (41.8%) and for those aged 25-34 years old (36%). CONCLUSIONS: INSEF has set up an experienced national and regional structure for HES implementation. Nationally representative quality epidemiological data is now available for public health monitoring, planning and research.

Serum surfactant protein D (SP-D) is a prognostic marker of poor outcome in patients with A/H1N1 virus infection.

INTRODUCTION: Surfactant protein D (SP-D) plays an important role in the innate responses against pathogens and its production is altered in lung disorders. METHODS: We studied the circulating levels of SP-D in 37 patients with acute respiratory distress syndrome due to the A/H1N1 virus infection and in 40 healthy controls. Cox logistic regression models were constructed to explore the association of SP-D levels and risk of death. RESULTS: Mortality rate after a 28-day was 32.42 %. Significant higher levels of SP-D were detected in A/H1N1 patients with fatal outcome (p < 0.05). After adjusting for confounding variables, levels of SP-D ≥250 ng/mL were associated with increased the risk of death (HR = 8.27, 95 % CI 1.1-64.1, p = 0.043). CONCLUSIONS: Our results revealed that higher circulating levels of SP-D are associated with higher mortality risk in critically ill A/H1N1 patients. SP-D might be a predictive factor of poor outcomes in viral pneumonia.

[Work activity of medical graduates at the University of Chile: Analysis per campus and graduation year]. / Actividad laboral de médicos egresados de la Universidad de Chile generaciones 2007 a 2010: análisis según sede y año de egreso.

BACKGROUND: The University promotes practices and values that influence their students in the pursuit of their occupational interests. AIM: To determine working activity features of medical graduates from the University of Chile and their relationship with undergraduate characteristics. MATERIAL AND METHODS: Medical graduates of the University of Chile were invited to complete a survey using a virtual server. The survey collected demographic, socioeconomic, work and guild characteristics. Undergraduate data, as campus and graduation years were obtained. RESULTS: The survey was completed by 333 physicians (167 men) aged 29 ± 2 years, graduated from 2007 to 2010. Ninety four percent had a paid work, 59% were employed in public hospitals and 28% in primary care health centers. The predominant type of work activity was performed in the public health service (55%), while 17% worked in private health services. Activity in public health services or primary care were significantly associated with the pursuit of undergraduate clinical activities in specific campuses of the University. CONCLUSIONS: The employment rate of medical graduates was high. Differences observed by graduation campus and type of work may be due to the modeling that students receive from teachers.

Integrating electro-Fenton and microalgae for the sustainable management of real food processing wastewater.

The present study demonstrates, for the first time, the feasibility of a two-step process consisting of Electro-Fenton (EF) followed by microalgae to treat highly loaded real food processing wastewater along with resource recovery. In the first step, EF with a carbon felt cathode and Ti/RuO2-IrO2 anode was applied at different current densities (3.16 mA cm-2, 4.74 mA cm-2 and 6.32 mA cm-2) to decrease the amount of organic matter and turbidity and enhance biodegradability. In the second step, the EF effluents were submitted to microalgal treatment for 15 days using a mixed culture dominated by Scenedesmus sp., Chlorosarcinopsis sp., and Coelastrum sp. Results showed that current density impacted the amount of COD removed by EF, achieving the highest COD removal of 77.5% at 6.32 mA cm-2 with >95% and 74.3% of TSS and PO43- removal, respectively. With respect to microalgae, the highest COD removal of 85% was obtained by the culture in the EF effluent treated at 6.32 mA cm-2. Remarkably, not only 85% of the remaining organic matter was removed by microalgae, but also the totality of inorganic N and P compounds, as well as 65% of the Fe catalyst that was left after EF. The removal of inorganic species also demonstrates the high complementarity of both processes, since EF does not have the capacity to remove such compounds, while microalgae do not grow in the raw wastewater. Furthermore, a maximum of 0.8 g L-1 of biomass was produced after cultivation, with an accumulation of 32.2% of carbohydrates and 25.9% of lipids. The implementation of the two processes represents a promising sustainable approach for the management of industrial effluents, incorporating EF in a water and nutrient recycling system to produce biomass that could be valorized into clean fuels.

YAP activation is robust to dilution.

The concentration of many transcription factors exhibits high cell-to-cell variability due to differences in synthesis, degradation, and cell size. Whether the functions of these factors are robust to fluctuations in concentration, and how this may be achieved, is poorly understood. Across two independent panels of breast cancer cells, we show that the average whole cell concentration of YAP decreases as a function of cell area. However, the nuclear concentration distribution remains constant across cells grouped by size, across a 4-8 fold size range, implying unperturbed nuclear translocation despite the falling cell wide concentration. Both the whole cell and nuclear concentration was higher in cells with more DNA and CycA/PCNA expression suggesting periodic synthesis of YAP across the cell cycle offsets dilution due to cell growth and/or cell spreading. The cell area - YAP scaling relationship extended to melanoma and RPE cells. Integrative analysis of imaging and phospho-proteomic data showed the average nuclear YAP concentration across cell lines was predicted by differences in RAS/MAPK signalling, focal adhesion maturation, and nuclear transport processes. Validating the idea that RAS/MAPK and cell cycle regulate YAP translocation, chemical inhibition of MEK or CDK4/6 increased the average nuclear YAP concentration. Together, this study provides an example case, where cytoplasmic dilution of a protein, for example through cell growth, does not limit a cognate cellular function. Here, that same proteins translocation into the nucleus.

Implementing a Pulmonary Telerehabilitation Program for Young Adults with Post-COVID-19 Conditions: A Pilot Study.

BACKGROUND: Several studies have shown that pulmonary telerehabilitation (PTR) improves respiratory capacity. However, there is little evidence of its effectiveness in youth with post-COVID-19 conditions (PCC). This study analyzed the effects of a PTR program on young adults with PCC. METHODS: Sixteen youths were randomly assigned to a control group (CG) or an experimental group (EG), with eight participants each. The EG participated in a PTR program that included twelve remote, asynchronous four-week sessions with diaphragmatic breathing and aerobic exercises. Vital signs (SpO2, HR, RR, BP), physical capacity (sit-to-stand test), cardiorespiratory capacity (6-Minute Walk Test), and perceived exertion (Borg scale) were assessed in both groups. RESULTS: Statistical analyses showed a significant decrease in RR and HR (p < 0.012) and an increase in SpO2 (p < 0.042), physical (p < 0.012), and respiratory (p < 0.028) capacity. Perceived effort decreased significantly in both groups (CG: p < 0.006; EG: p < 0.001) only for physical but not for cardiorespiratory capacity (p < 0.106). There were no statistical changes registered in BP (p > 0.05). CONCLUSIONS: The PTR program, which includes respiratory and aerobic exercises, is feasible and effective in improving physical and cardiorespiratory capacity in young people with PCC, as well as reducing HR, RR, and dyspnea.

Assessment of corticospinal tract (CST) damage in acute stroke patients: comparison of tract-specific analysis versus segmentation of a CST template.

PURPOSE: To compare two techniques to assess corticospinal tract (CST) damage in stroke patients: tract-specific analysis by probabilistic tractography and segmentation using a CST template. MATERIALS AND METHODS: We extracted fractional anisotropy (FA) values, the FA ratio, and mean diffusivity (MD) in 18 stroke patients and 21 healthy volunteers matched for age and sex. We compared the two methods in order to determine their ability to detect 1) differences between diffusion tensor imaging (DTI) parameters of healthy volunteers and stroke patients, 2) the correlation between DTI parameters and clinical scores, and 3) the correlation between DTI parameters and blood oxygen level-dependent (BOLD) signals in a fist-closure task. RESULTS: FA values were higher with the tractography approach than with the segmentation method, but differences between the ipsilesional CST and the homologous region in healthy subjects were detected using both methods. In patients, clinical scores were significantly correlated with FA values and FA ratios with both methods. The BOLD signal was positively correlated with FA values for CST with the segmentation but not with the tractography approach. CONCLUSION: CST damage in stroke patients can be assessed by either probabilistic tractography or segmentation of a CST template. Although each method has advantages and limitations, both are sensitive enough to detect differences among stroke patients and identify specific correlations with clinical scores.

A neurorobotics approach to behaviour selection based on human activity recognition.

Behaviour selection has been an active research topic for robotics, in particular in the field of human-robot interaction. For a robot to interact autonomously and effectively with humans, the coupling between techniques for human activity recognition and robot behaviour selection is of paramount importance. However, most approaches to date consist of deterministic associations between the recognised activities and the robot behaviours, neglecting the uncertainty inherent to sequential predictions in real-time applications. In this paper, we address this gap by presenting an initial neurorobotics model that embeds, in a simulated robot, computational models of parts of the mammalian brain that resembles neurophysiological aspects of the basal ganglia-thalamus-cortex (BG-T-C) circuit, coupled with human activity recognition techniques. A robotics simulation environment was developed for assessing the model, where a mobile robot accomplished tasks by using behaviour selection in accordance with the activity being performed by the inhabitant of an intelligent home. Initial results revealed that the initial neurorobotics model is advantageous, especially considering the coupling between the most accurate activity recognition approaches and the computational models of more complex animals.

An Integrated Neurorobotics Model of the Cerebellar-Basal Ganglia Circuitry.

This work presents a neurorobotics model of the brain that integrates the cerebellum and the basal ganglia regions to coordinate movements in a humanoid robot. This cerebellar-basal ganglia circuitry is well known for its relevance to the motor control used by most mammals. Other computational models have been designed for similar applications in the robotics field. However, most of them completely ignore the interplay between neurons from the basal ganglia and cerebellum. Recently, neuroscientists indicated that neurons from both regions communicate not only at the level of the cerebral cortex but also at the subcortical level. In this work, we built an integrated neurorobotics model to assess the capacity of the network to predict and adjust the motion of the hands of a robot in real time. Our model was capable of performing different movements in a humanoid robot by respecting the sensorimotor loop of the robot and the biophysical features of the neuronal circuitry. The experiments were executed in simulation and the real world. We believe that our proposed neurorobotics model can be an important tool for new studies on the brain and a reference toward new robot motor controllers.

Dehydroleucodine and xanthatin, two natural anti-inflammatory lactones, inhibit mast cell degranulation by affecting the actin cytoskeleton.

Actin remodeling is a critical regulator of mast cell secretion. In previous work, we have shown that dehydroleucodine and xanthatin, two natural α,ß-unsaturated lactones, exhibit anti-inflammatory and mast cell stabilizing properties. Based on this background, this study aimed to determine whether the mast cell stabilizing action of these lactones is associated with changes in the actin cytoskeleton. Rat peritoneal mast cells were preincubated in the presence of dehydroleucodine or xanthatin before incubation with compound 48/80. Comparative studies with sodium cromoglycate and latrunculin B were also made. After treatments, different assays were performed on mast cell samples: ß-hexosaminidase release, cell viability studies, quantification of mast cells and their state of degranulation by light microscopy, transmission electron microscopy, and actin staining for microscopy observation. Results showed that dehydroleucodine and xanthatin inhibited mast cell degranulation, evidenced by the inhibition of ß-hexosaminidase release and decreased degranulated mast cell percentage. At the same time, both lactones altered the F-actin cytoskeleton in mast cells resulting, similarly to Latrunculin B, in a higher concentration of nuclear F-actin when activated by compound 48/80. For the first time, this study describes the biological properties of dehydroleucodine and xanthatin concerning to the rearrangement of actin filaments during stimulated exocytosis in mast cells. These data have important implications for developing new anti-inflammatory and mast cell stabilizing drugs and for designing new small molecules that may interact with the actin cytoskeleton.

Exoskeletons: Contribution to Occupational Health and Safety.

This review aims to characterize the current landscape of exoskeletons designed to promote medical care and occupational safety in industrial settings. Extensive exploration of scientific databases spanning industries, health, and medicine informs the classification of exoskeletons according to their distinctive attributes and specific footholds on the human physique. Within the scope of this review, a comprehensive analysis is presented, contextualizing the integration of exoskeletons based on different work activities. The reviewers extracted the most relevant articles published between 2008 and 2023 from IEEE, Proquest, PubMed, Science Direct, Scopus, Web of Science, and other databases. In this review, the PRISMA-ScR checklist was used, and a Cohen's kappa coefficient of 0.642 was applied, implying moderate agreement among the reviewers; 75 primary studies were extracted from a total of 344. The future of exoskeletons in contributing to occupational health and safety will depend on continued collaboration between researchers, designers, healthcare professionals, and industries. With the continued development of technologies and an increasing understanding of how these devices interact with the human body, exoskeletons will likely remain valuable for improving working conditions and safety in various work environments.

S-acylation of the Wnt receptor Frizzled-5 by zDHHC5 controls its cellular localization and synaptogenic activity in the rodent hippocampus.

Proper localization of receptors for synaptic organizing factors is crucial for synapse formation. Wnt proteins promote synapse assembly through Frizzled (Fz) receptors. In hippocampal neurons, the surface and synaptic localization of Fz5 is regulated by neuronal activity, but the mechanisms involved remain poorly understood. Here, we report that all Fz receptors can be post-translationally modified by S-acylation and that Fz5 is S-acylated on three C-terminal cysteines by zDHHC5. S-acylation is essential for Fz5 localization to the cell surface, axons, and presynaptic sites. Notably, S-acylation-deficient Fz5 is internalized faster, affecting its association with signalosome components at the cell surface. S-acylation-deficient Fz5 also fails to activate canonical and divergent canonical Wnt pathways. Fz5 S-acylation levels are regulated by the pattern of neuronal activity. In vivo studies demonstrate that S-acylation-deficient Fz5 expression fails to induce presynaptic assembly. Our studies show that S-acylation of Frizzled receptors is a mechanism controlling their localization and function.

Synchronisation effects on the behavioural performance and information dynamics of a simulated minimally cognitive robotic agent.

Oscillatory activity is ubiquitous in nervous systems, with solid evidence that synchronisation mechanisms underpin cognitive processes. Nevertheless, its informational content and relationship with behaviour are still to be fully understood. In addition, cognitive systems cannot be properly appreciated without taking into account brain-body- environment interactions. In this paper, we developed a model based on the Kuramoto Model of coupled phase oscillators to explore the role of neural synchronisation in the performance of a simulated robotic agent in two different minimally cognitive tasks. We show that there is a statistically significant difference in performance and evolvability depending on the synchronisation regime of the network. In both tasks, a combination of information flow and dynamical analyses show that networks with a definite, but not too strong, propensity for synchronisation are more able to reconfigure, to organise themselves functionally and to adapt to different behavioural conditions. The results highlight the asymmetry of information flow and its behavioural correspondence. Importantly, it also shows that neural synchronisation dynamics, when suitably flexible and reconfigurable, can generate minimally cognitive embodied behaviour.

Accessibility challenges of e-commerce websites.

Today, there are many e-commerce websites, but not all of them are accessible. Accessibility is a crucial element that can make a difference and determine the success or failure of a digital business. The study was applied to 50 e-commerce sites in the top rankings according to the classification proposed by ecommerceDB. In evaluating the web accessibility of e-commerce sites, we applied an automatic review method based on a modification of Website Accessibility Conformance Evaluation Methodology (WCAG-EM) 1.0. To evaluate accessibility, we used Web Accessibility Evaluation Tool (WAVE) with the extension for Google Chrome, which helps verify password-protected, locally stored, or highly dynamic pages. The study found that the correlation between the ranking of e-commerce websites and accessibility barriers is 0.329, indicating that the correlation is low positive according to Spearman's Rho. According to the WAVE analysis, the research results reveal that the top 10 most accessible websites are Sainsbury's Supermarkets, Walmart, Target Corporation, Macy's, IKEA, H&M Hennes, Chewy, Kroger, QVC, and Nike. The most significant number of accessibility barriers relate to contrast errors that must be corrected for e-commerce websites to reach an acceptable level of accessibility. The most neglected accessibility principle is perceivable, representing 83.1%, followed by operable with 13.7%, in third place is robust with 1.7% and finally understandable with 1.5%. Future work suggests constructing a software tool that includes artificial intelligence algorithms that help the software identify accessibility barriers.