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Abstract Background The increase in cases of mild cognitive impairment (MCI) underlines the urgency of finding effective methods to slow its progression. Given the limited effectiveness of current pharmacological options to prevent or treat the early stages of this deterioration, non-pharmacological alternatives are especially relevant. Objective To assess the effectiveness of a cognitive-motor intervention based on immersive virtual reality (VR) that simulates an activity of daily living (ADL) on cognitive functions and its impact on depression and the ability to perform such activities in patients with MCI. Methods Thirty-four older adults (men, women) with MCI were randomized to the experimental group (n = 17; 75.41 ± 5.76) or control (n = 17; 77.35 ± 6.75) group. Both groups received motor training, through aerobic, balance and resistance activities in group. Subsequently, the experimental group received cognitive training based on VR, while the control group received traditional cognitive training. Cognitive functions, depression, and the ability to perform activities of daily living (ADLs) were assessed using the Spanish versions of the Montreal Cognitive Assessment (MoCA-S), the Short Geriatric Depression Scale (SGDS-S), and the of Instrumental Activities of Daily Living (IADL-S) before and after 6-week intervention (a total of twelve 40-minutes sessions). Results Between groups comparison did not reveal significant differences in either cognitive function or geriatric depression. The intragroup effect of cognitive function and geriatric depression was significant in both groups (p

Abstract Background In recent years, the use of virtual reality (VR) as a complementary intervention in treating cognitive impairment has significantly increased. VR applications based on instrumental activities of daily living (iADL-VR) could offer a promising approach with greater ecological validity for intervention in groups with cognitive impairments. However, the effectiveness of this approach is still debated. Objective This systematic review aims to synthesize the effects of iADL-VR interventions to rehabilitate, train, or stimulate cognitive functions in healthy adults and people with mild cognitive impairment (MCI) and different types of dementia. Methods A systematic search was performed in the Scopus, PubMed, IEEE Xplore, Web of Science, and APA PsycNet databases until September 2022 and repeated in April 2023. The selected studies met the search terms, were peer-reviewed, included an iADL-VR intervention, and were written in English. Descriptive, qualitative studies, reviews, cognitive assessment, non-intervention studies, those unrelated to VR or iADL, those focused on motor aspects, and non-degenerative disorders were excluded. The PEDro scale was used to assess the methodological quality of the controlled studies. To present and synthesize the results, we organized the extracted data into three tables, including PEDro scores, participant characteristics, and study characteristics. Results Nineteen studies that met the inclusion and exclusion criteria were included. The total sample reached 590 participants, mostly women (72.67%). Approximately 30% were diagnosed with Alzheimer’s disease or dementia, and 20% had mild cognitive impairment. Variables such as authors and year of publication, study design, type of intervention and VR applied, duration of the intervention, main findings, and conclusions were extracted. Regarding demographic characteristics, the sample size, age, sex, years of education, neurological diagnosis, dropouts, and the city and country where the intervention took place were recorded. Almost all studies showed improvements in some or all the outcomes after the intervention, generally greater in the iADL-VR group than in the control group. Conclusion iADL-VR interventions could be beneficial in improving the performance of cognitive functions in older adults and people with MCI and different types of dementia. The ecological component of these tasks makes them very suitable for transferring what has been learned to the real world. However, such transfer needs to be confirmed by further studies with larger and more homogeneous samples and longer follow-up periods. This review had no primary funding source and was registered with PROSPERO under registration ID: 375166.

Abstract Background Loss of cognitive and executive functions is a problem that affects people of all ages. That is why it is important to perform exercises for memory training and prevent early cognitive deterioration. The aim of this work was to compare the cognitive performance of the participants after an intervention by using two mnemonic techniques to exercise memory functions (paired-associate learning and method of loci). Methods A longitudinal study was conducted with 21 healthy participants aged 18 to 55 years over a 2-month period. To assess the impact of this proposal, the NEUROPSI brief battery cognitive assessment test was applied before and after the intervention. In each session, a previous cognitive training was carried out using the paired-associate learning technique, to later perform a task based on the loci method, all from a smart device-based application. The accuracy response and reaction times were automatically collected in the app. Results After the intervention, a statistically significant improvement was obtained in the neuropsychological assessment (NEUROPSI neuropsychological battery) reflected by the Wilcoxon paired signed-rank test (P

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.

Abstract Background Celiac disease (CD) is an autoimmune chronic enteropathy of the small intestine caused by exposure to gluten in genetically predisposed individuals. CD is not easy to diagnose due to its unspecific symptomatology, especially in adults, a diagnosed/undiagnosed ratio of 1:7 is estimated. CD does not have its own code in the International Classification of Primary Care (ICPC) but it is coded under code D99 “Disease digestive system, other”, which hinders diagnosis, intervention and research. The aim of this study is to investigate the prevalence of CD in Aragón, Spain, using the information available from Primary Care, as well as to discuss the difficulties involved in determining prevalence of CD from data collected at this level of medical intervention. Methods We designed an epidemiological cross-sectional study and analysed 26,964 electronic clinical records from the Aragonese Health Service under code ICPC D99 collected up to December 31st, 2016. The clinical records were classified by their editable field “descriptor” according to their probability of being related to CD. Analyses of gender, age, age at diagnosis, province and health sector were carried out. Results We found 4534 clinical records under 293 different descriptors with a high probability of referring to CD. Prevalence in Aragón was estimated to be 0.35% ranging from 0.24 to 0.81% with important differences among health sectors. Conclusions The prevalence of 0.35% is a long way from the generally accepted 1% but within the usually considered ratio 1:7 of diagnosed:undiagnosed cases. Differences among sectors should be carefully analysed. Lacking its own ICPC code, diagnosis of CD in Primary Care Services is not included in a single category, but it is distributed under several descriptors, which makes it difficult to offer any firm diagnosis for treatment and hinders research. Finally, the high prevalence of CD justifies its own ICPC code and the need to withdraw CD from the generic D99 code “Disease digestive system other”.

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.

The implementation of control algorithms oriented to robotic assistance and rehabilitation tasks for people with motor disabilities has been of increasing interest in recent years. However, practical implementation cannot be carried out unless one has the real robotic system availability. To overcome this drawback, this article presents the development of an interactive virtual reality (VR)-based framework that allows one to simulate the execution of rehabilitation tasks and robotic assistance through a robotic standing wheelchair. The virtual environment developed considers the kinematic and dynamic model of the standing human–wheelchair system with a displaced center of mass, since it can be displaced for different reasons, e.g.,: bad posture, limb amputations, obesity, etc. The standing wheelchair autonomous control scheme has been implemented through the Full Simulation (FS) and Hardware in the Loop (HIL) techniques. Finally, the performance of the virtual control schemes has been shown by means of several experiments based on robotic assistance and rehabilitation for people with motor disabilities.

Partial updates (PU) of adaptive filters have been successfully applied in different contexts to lower the computational costs of many control systems. In a PU adaptive algorithm, only a fraction of the coefficients is updated per iteration. Particularly, this idea has been proved as a valid strategy in the active control of periodic noise consisting of a sum of harmonics. The convergence analysis carried out here is based on the periodic nature of the input signal, which makes it possible to formulate the adaptive process with a matrix-based approach, the periodic least-mean-square (P-LMS) algorithm In this paper, we obtain the upper bound that limits the step-size parameter of the sequential PU P-LMS algorithm and compare it to the bound of the full-update P-LMS algorithm. Thus, the limiting value for the step-size parameter is expressed in terms of the step-size gain of the PU algorithm. This gain in step-size is the quotient between the upper bounds ensuring convergence in the following two scenarios: first, when PU are carried out and, second, when every coefficient is updated during every cycle. This step-size gain gives the factor by which the step-size can be multiplied so as to compensate for the convergence speed reduction of the sequential PU algorithm, which is an inherently slower strategy. Results are compared with previous results based on the standard sequential PU LMS formulation. Frequency-dependent notches in the step-size gain are not present with the matrix-based formulation of the P-LMS. Simulated results confirm the expected behavior.

In this work, a novel LAMDA (Learning Algorithm for Multivariable Data Analysis) control strategy for trajectory tracking for an aerial manipulator is presented. Four control strategies are developed: Kinematic, Inverse Dynamics, Sliding Mode (SMC), and LAMDA. These are compared with each other in order to verify their performance to fulfill the control objective. Experimental tests were also carried out to validate the developed controllers. In addition, a study of stability has been also performed for all the controllers. The results obtained by the LAMDA controller demonstrated the good performance of the controller in the aerial manipulator robot. To the best of our knowledge, this is the first time a LAMDA controller has been applied to an aerial robotic manipulator.

The objective of this study was to evaluate the performance of the different systems and techniques aimed at suppressing vibrations on optical ground-based telescopes. We identified the studies by searching three electronic databases (Science Direct, IEEE library and Web of Science) from the year 2000 to December 2020. The studies were eligible if they proposed systems focused on mitigating the effects of vibrations in optical telescopes and brought performance data. A total of nine studies met our eligibility criteria. Current evidence confirms the feasibility of adaptative optics (AO) systems based on closed-loop control to mitigate vibrations, although variations and additions should be made depending on their nature and characteristics in order to improve the performance of the proposed techniques. This systematic review was conducted to provide a state-of-the-art of the methods and techniques that have been developed over the past two decades. The review also points out some issues that demand future research.

Technological advances in recent years have shown interest in the development of robots in the medical field. The integration of robotic systems in areas of assistance and rehabilitation improves the user’s quality of life. In this context, this article presents a proposal for the unified control of a robotic standing wheelchair. Considering primary and secondary tasks as control objectives, the system performs tasks autonomously and the change of position and orientation can be performed at any time. The development of the control scheme was divided in two parts: (i) kinematic controller to solve the desired motion problem; and (ii) dynamic compensation of the standing wheelchair–human system. The design of the two controllers considers the theory of linear algebra, proposing a low computational cost and an asymptotically stable algorithm, without disturbances. The stability and robustness analysis of the system is performed by analyzing the evolution of the control errors in each sampling period. Finally, real experiments of the performance of the developed controller are performed using a built and instrumented standing wheelchair.

Immersive virtual reality techniques have been applied to the rehabilitation of patients after stroke, but evidence of its clinical effectiveness is scarce. The present review aims to find studies that evaluate the effects of immersive virtual reality (VR) therapies intended for motor function rehabilitation compared to conventional rehabilitation in people after stroke and make recommendations for future studies. Data from different databases were searched from inception until October 2020. Studies that investigated the effects of immersive VR interventions on post-stroke adult subjects via a head-mounted display (HMD) were included. These studies included a control group that received conventional therapy or another non-immersive VR intervention. The studies reported statistical data for the groups involved in at least the posttest as well as relevant outcomes measuring functional or motor recovery of either lower or upper limbs. Most of the studies found significant improvements in some outcomes after the intervention in favor of the virtual rehabilitation group. Although evidence is limited, immersive VR therapies constitute an interesting tool to improve motor learning when used in conjunction with traditional rehabilitation therapies, providing a non-pharmacological therapeutic pathway for people after stroke.

In the field of active noise control (ANC), a popular method is the modified filtered-x LMS algorithm. However, it has two drawbacks: its computational complexity higher than that of the conventional FxLMS, and its convergence rate that could still be improved. Therefore, we propose an adaptive strategy which aims at speeding up the convergence rate of an ANC system dealing with periodic disturbances. This algorithm consists in combining the organization of the filter weights in a hierarchy of subfilters of shorter length and their sequential partial updates (PU). Our contribution is threefold: (1) we provide the theoretical basis of the existence of a frequency-dependent parameter, called gain in step-size. (2) The theoretical upper bound of the step-size is compared with the limit obtained from simulations. (3) Additional experiments show that this strategy results in a fast algorithm with a computational complexity close to that of the conventional FxLMS.

The location of large telescopes, generally far from the data processing centers, represents a logistical problem for the supervision of the capture of images. In this work, we carried out a preliminary study of the vibration signature of the T80 telescope at the Javalambre Astrophysical Observatory (JAO). The study analyzed the process of calculating the displacement that occurs because of the vibration in each of the frequencies in the range of interest. We analyzed the problems associated with very low frequencies by means of simulation, finding the most critical vibrations below 20 Hz, since they are the ones that generate greater displacements. The work also relates previous studies based on simulation with the real measurements of the vibration of the telescope taken remotely when it is subjected to different positioning movements (right ascension and/or declination) or when it performs movement actions such as those related to filter trays or mirror cover. The obtained results allow us to design a remote alarm system to detect invalid images (taken with excess vibration).

Virtual Reality (VR) has had significant advances in rehabilitation, due to the gamification of cognitive activities that facilitate treatment. On the other hand, Immersive Virtual Reality (IVR) produces outstanding results due to the interactive features with the user. This work introduces a VR application for memory rehabilitation by walking through a maze and using the Oculus Go head-mounted display (HMD) technology. The mechanics of the game require memorizing geometric shapes while the player progresses in two modes, autonomous or manual, with two levels of difficulty depending on the number of elements to remember. The application is developed in the Unity 3D video game engine considering the optimization of computational resources to improve the performance in the processing and maintaining adequate benefits for the user, while the generated data is stored and sent to a remote server. The maze task was assessed with 29 subjects in a controlled environment. The obtained results show a significant correlation between participants’ response accuracy in both the maze task and a face–pair test. Thus, the proposed task is able to perform memory assessments.

The aim of this study was to develop a scale to assess the levels of specific self-efficacy in order to enhance adherence to a gluten-free diet and the life quality of celiac patients. Celiac disease is a chronic small intestinal immune-mediated enteropathy precipitated by exposure to dietary gluten in genetically predisposed people. The only treatment is a strict lifelong gluten-free diet. Within the framework of Social Cognitive Theory, expectation of self-efficacy is understood as the degree in which a person believes himself to be capable of performing a certain task (e.g., adhering to a gluten-free diet), a construct which has been widely studied in its relation with adopting healthy behaviors, but scarcely in relation to celiac disease. A validation study was carried out in various stages: preparation of the protocol; construction of the questionnaire and a pilot run with 20 patients; validation of the scale with 563 patients and statistical analysis. A 25-item scale was developed. Feasibility was excellent (99.82% of participants completed all the questions). Factorial analysis pointed to the existence of five factors that explained 70.98% of the variance with a Cronbach alpha of 0.81 for the scale overall and between 0.64 and 0.90 for each factor. The scale showed a Spearman's Rho coefficient of 0.279 with the General self-efficacy Scale. This easily administered scale provides good psychometric properties for evaluating specific self-efficacy of celiac patients in adhering to treatment. It seeks to be the first scale that provides not only a measurement of specific self-efficacy in celiac disease, but also to determine its levels for each of the areas as a first step toward designing interventions of self-management and empowerment programs to cope with the disease.