Cognitive-motor interventions based on virtual reality and instrumental activities of daily living (iADL): an overview

Non-invasive, non-pharmacological interventions utilizing virtual reality (VR) represent a promising approach to enhancing cognitive function in patients with degenerative cognitive disorders. Traditional “pen and paper” therapies often lack the practical engagement in everyday activities that older individuals encounter in their environment. These activities pose both cognitive and motor challenges, underscoring the necessity of understanding the outcomes of such combined interventions. This review aimed to assess the advantages of VR applications that integrate cognitive-motor tasks, simulating instrumental activities of daily living (iADLs). We systematically searched five databases–Scopus, Web of Science, Springer Link, IEEE Xplore, and PubMed, from their inception until January 31, 2023. Our review revealed that motor movements, coupled with VR-based cognitive-motor interventions, activate specific brain areas and foster improvements in general cognition, executive function, attention, and memory. VR applications that meld cognitive-motor tasks and simulate iADLs can offer significant benefits to older adults. Enhanced cognitive and motor performance can promote increased independence in daily activities, thereby contributing to improved quality of life

A New Online Tool to Evaluate Transferable Skills in the European Framework

According to the European classification of skills, competencies, qualifications, and occupations (ESCO), transversal knowledge, skills, and competencies are pertinent to a wide array of occupations and sectors. Transversal knowledge, skills, and competencies are the foundational elements for developing the “hard” skills and competencies necessary for success in the labor market. In this paper, we introduce an online platform for assessing the attainment of transversal and soft skills. This tool allows us to define levels of competency acquisition and measure students’ development. The use of these competency levels helps improve the understanding of these skills and the evaluation process. The tool also enhances coordination among courses and teachers. The evaluation process can be established on three different levels: self-evaluation, peer evaluation, and teacher assessment. Developers, students, and teachers have assessed the tool has been developed following a lifecycle of evolutionary prototypes with successive refinements

A ROS-Based Open Tool for Controlling an Educational Mobile Robot

Commercial educational robots provide an accessible entry point into the world of robotics. However, their programming is often limited to specific platforms, which can make it challenging to acquire the skills necessary for industry and research. In this study, we introduce an open-access tool developed using C++ and Arduino IDE that enables us to manage a commercial mobile robot through the Robot Operating System (ROS) middleware. This provides programmers with the ability to work in a powerful programming environment, such as Python. The robot used is the CrowBot BOLT, a kit based on ESP32 that enables wireless communication and includes various peripherals for application development. The mobile robot topics include robot velocities, RGB LEDs, a buzzer, a programmable button, and proximity, light, and line sensors. The proposal is assessed using two controllers: one for proximity and the other for tracking angular light. Both controllers are developed using Visual Studio Code. The experimental results demonstrated the proper functioning of the tool. Additionally, the response time was evaluated, and it was found that optimal performance is achieved at a frequency of 10 Hz. In summary, this proposal provides an accessible option for students and developers seeking to gain skills in robotics using ROS. The project’s repository is located at https://github.com/joseVarelaAldas/ROS-Crowbot

IoT-Based Alternating Current Electrical Parameters Monitoring System

Energy monitors are indispensable for achieving efficient electrical grids and even more so in the age of the Internet of Things (IoT), where electrical system data are monitored from anywhere in the world. This paper presents the development of a two-channel electrical parameter-monitoring system based on the M5 Stack Core2 kit. The acquisition of variables is done through PZEM 004T V3.0 sensors, and the data are sent to the ThingSpeak cloud database. Local readings are done through the LCD, and data re stored on a micro SD card. Remote monitoring is done through two applications, namely a web application and a mobile application, each designed for different purposes. To validate this proposal, a commercial device with IoT features (Gen 2 Vue Energy Monitor) is used, comparing the active power and active energy readings recorded continuously for 7 days. The results indicate an accuracy of up to 1.95% in power and 0.81% in energy, obtaining a low-cost compact product with multiple features

TABSAOND: A technique for developing agent-based simulation apps and online tools with nondeterministic decisions

Agent-based simulators (ABSs) have successfully allowed practitioners to estimate the outcomes of certain input circumstances in several domains. Although some techniques and processes provide hints about the construction of these systems, some aspects have not been discussed yet in the literature. In this context, the current approach presents a technique for developing ABSs. Its focus is to guide practitioners in designing and implementing the decision-making processes of agents in nondeterministic scenarios. As an additional technological innovation, the ABSs are deployed as both mobile apps and online tools. This work illustrates the current approach with two case studies in the fields of (a) health and welfare and (b) tourism. These case studies have also been developed with the most similar technique from the literature for comparing both techniques. The presented technique improved the simulated outcomes in terms of their similarity with the real ones. The obtained ABSs were more efficient and reliable for large amounts of agents (e.g. 10,000 – 400,000 agents). The development time was lower. Both the framework and the implementation of a case study are freely distributed as open-source to facilitate the reproducibility of the experiments and to assist practitioners in applying the current approach

Immersive virtual reality app for mild cognitive impairment

A characteristic symptom of neurodegenerative diseases is the deterioration of the memory. These problems usually worsen with the progression of the disease, being the cognitive rehabilitation an important tool in order to slow down the progress of the disease in the patient. This work presents the development of a mobile virtual reality application through a serious game to boost the memory by solving mazes in three levels of difficulty. The application uses the Gear VR glasses to provide the user with an immersive experience. The results present the proposed application, showing the components of the virtual environment

Influence of hand tracking in immersive virtual reality for memory assessment

Few works analyze the parameters inherent to immersive virtual reality (IVR) in applications for memory evaluation. Specifically, hand tracking adds to the immersion of the system, placing the user in the first person with full awareness of the position of their hands. Thus, this work addresses the influence of hand tracking in memory assessment with IVR systems. For this, an application based on activities of daily living was developed, where the user must remember the location of the elements. The data collected by the application are the accuracy of the answers and the response time; the participants are 20 healthy subjects who pass the MoCA test with an age range between 18 to 60 years of age; the application was evaluated with classic controllers and with the hand tracking of the Oculus Quest 2. After the experimentation, the participants carried out presence (PQ), usability (UMUX), and satisfaction (USEQ) tests. The results indicate no difference with statistical significance between both experiments; controller experiments have 7.08% higher accuracy and 0.27 ys. faster response time. Contrary to expectations, presence was 1.3% lower for hand tracking, and usability (0.18%) and satisfaction (1.43%) had similar results. The findings indicate no evidence to determine better conditions in the evaluation of memory in this case of IVR with hand tracking

ABSCEV: An agent-based simulation framework about smart transportation for reducing waiting times in charging electric vehicles

[EN] Fuel has been the main source of energy for cars for many years, but the non-renewable resources are limited in the planet. In this context, electric vehicles (EVs) are increasingly replacing the previous kind of cars. However, as the number of EVs increases, some challenges arise such as the reduction of waiting times in the queues of fast charging stations. The current work addresses this challenge by means of social coordination mechanisms. In particular, this work presents an agent-based simulation framework for simulating the effects of different coordination policies in the route planning of EV drivers for charging their vehicles on their trips. In this manner, researchers and professionals can test different coordination mechanisms for this purpose. This framework has been experienced by simulating an adaptive strategy based on the implicit communication through booking systems in the charging stations. This strategy was compared with another common strategy, which was used as the control mechanism. This comparison was done by simulating several scenarios in two Spanish cities (i.e. Madrid and Zaragoza). The experimental results show that the current approach was useful to propose a route planning strategy that had statistically significant improvements in the reduction of waiting times in charging stations and also in the global trip times. In addition, the evolutions of pathfinding execution times and the numbers of interchanged messages did not show any overloading pattern over the time. (C) 2018 Elsevier B.V. All rights reservedWe acknowledge the research project "Construccion de un framework para agilizar el desarrollo de aplicaciones mviles en el ambito de la salud" funded by University of Zaragoza and Foundation Ibercaja with grant reference JIUZ-2017-TEC-03. This work has been supported by the program "Estancias de movilidad en el extranjero Jose Castillejo para jovenes doctores" funded by the Spanish Ministry of Education, Culture and Sport with reference CAS17/00005. We also acknowledge support from "Universidad de Zaragoza", "Fundacion Bancaria Ibercaja" and "Fundacion CAI" in the "Programa Ibercaja-CAI de Estancias de Investigacion" with reference IT1/18. This work acknowledges the research project "Desarrollo Colaborativo de Soluciones AAL" with reference TIN2014-57028-R funded by the Spanish Ministry of Economy and Competitiveness. It has also been supported by "Organismo Autonomo Programas Educativos Europeos" with reference 2013-1-CZ1-GRU06-14277. We also acknowledge support from project "Sensores vestibles y tecnologa movil como apoyo en la formacin y practica de mindfulness: prototipo previo aplicado a bienestar" funded by University of Zaragoza with grant number UZ2017-TEC-02.García-Magariño, I.; Palacios-Navarro, G.; Lacuesta Gilaberte, R.; Lloret, J. (2018). ABSCEV: An agent-based simulation framework about smart transportation for reducing waiting times in charging electric vehicles. Computer Networks. 138:119-135. https://doi.org/10.1016/j.comnet.2018.03.01411913513

The cupboard task: An immersive virtual reality-based system for everyday memory assessment

Background and objective Virtual Reality (VR) has the capacity to be used in cognitive rehabilitation interventions for diagnostic and training purposes. This technology allows the development of proposals that traditionally have been only implemented using physical elements that imply greater resources and a lesser degree of automation. This work presents an immersive virtual reality (IVR) application (the Cupboard task) for the evaluation of memory in a more ecological way and based on an activity of daily living (ADL). Methods To appraise its construct validity, we have carried out a comparative study with a traditional method of memory assessment (method of loci). To check for any association between performance and age, performance with years of education, and reaction time with age, the Pearson's correlation was used. One-way ANOVA was used to check for differences in performance by gender. We also performed a reliability analysis with a two way mixed effects model where people effects are random and measures effects are fixed. Therefore, intra-class correlation coefficient with absolute agreement was reckoned to assess the consistency or concordance of the measures made by both the method of loci and the cupboard IVR task. Results Both tasks were evaluated on a sample of 22 healthy participants who voluntarily took part in the experiment. The results obtained showed a high degree of concordance between both memory performance measures, which assumes good clinical relevance. In addition, other age-related effects were found, common to memory assessment tasks. Conclusions This work showed that it is possible to use an IVR application to successfully assess everyday memory. We have also demonstrated the potential of IVR to develop valid tests that assess memory functions reliably and efficiently and within ecologically valid contexts. The results obtained open the door to its use in clinical settings for cognitive training (and promoting cognitive health) of patients with mild cognitive impairment (MCI), severe cognitive impairment (SCI) such as Alzheimer or Dementia, etc., with full guarantees of application, although it must first be validated through a randomized control trial (RCT). The degree of usability of the Cupboard task was very high according to the test carried out by the participants

Comparison of Errors Produced by ABA and ITC Methods for the Estimation of Forest Inventory Attributes at Stand and Tree Level in Pinus radiata Plantations in Chile

Airborne laser scanning (ALS) technology is fully implemented in forest resource assessment processes, providing highly accurate and spatially continuous results throughout the area of interest, thus reducing inventory costs when compared with traditional sampling inventories. Several approaches have been employed to estimate forest parameters using ALS data, such as the Area-Based Approach (ABA) and Individual Tree Crown (ITC). These two methodologies use different information processing and field data collection approaches; thus, it is important to have a selection criterion for the method to be used based on the expected results and admissible errors. The objective of this study was to compare the prediction errors of forest inventory attributes in the functioning of ABA and ITC approaches. A plantation of 500 ha of Pinus radiata (400–600 trees ha−1) in Chile was selected; a forest inventory was conducted using the ABA and ITC methods and the accuracy of both methods was analyzed. The ITC models performed better than the ABA models at low tree densities for all forest inventory attributes (15% MAPE in tree density—N—and 11% in volume—V). There was no significant difference in precision regarding the volume and basal area (G) estimations at medium densities, although ITC obtained better results for density and dominant height (Ho). At high densities, ABA performed better for all the attributes except for height (6.5% MAPE in N, 8.7% in G, and 8.9% in V). Our results showed that the precision of forest inventories based on ALS data can be adjusted depending on tree density to optimize the selected approach (ABA and ITC), thus reducing the inventory costs. Hence, field efforts can be greatly decreased while achieving better prediction accuracies