The ever-evolving landscape of healthcare demands innovative solutions, particularly in light of the global health crisis of 2020 and the aging global population. Technological advancements and new approaches in remote health monitoring systems have helped to bridge the gap for vulnerable individuals such as older adults. This review explores methods for the analysis of physiological signals using remote and intelligent systems and mobile and web-based applications, mostly linked to wearable devices, focusing primarily on the elderly population. The main objective is to identify crucial advancements in the development or integration of technology applied to addressing challenges of this magnitude. The research is structured following the PRISMA-ScR guidelines. The search strategy was implemented in databases such as the ACM Digital Library, IEEE Xplore, PubMed, Science Direct, Scopus, and Springer Link. A total of 411 articles were collected, and inclusion and exclusion criteria were applied to focus on studies published between 2020 and 2024. Ultimately, 100 articles from 35 countries were selected for data extraction. The findings reveal significant progress in remote monitoring technologies but emphasize the need for rigorous validation to ensure accuracy and reliability across diverse populations. To develop robust systems that provide equitable and high-quality healthcare, it is essential to address critical challenges such as data privacy, security, accessibility, and ethical considerations.

Every computer task generates response times depending on the computer hardware and software. The response times of tasks executed in real-time operating systems such as RT-Linux can vary as their instances evolve even though they always execute the same algorithm. This variation decreases as the priority of the tasks increases; however, the minimum and maximum response times are still present in the same task, and this complicates its monitoring, decreasing its level of predictability in case of contingency or overload, as well as making resource sizing difficult. Therefore, the need arises to propose a model capable of reconstructing the dynamics of response times for the instances of a task with high priority in order to analyze their offline behavior under specific working conditions. For this purpose, we develop the necessary theory to build the response time reconstruction model. Then, to test the proposed model, we set up a workbench consisting of a single board computer, PREEMPT_RT, and a high priority task generated by the execution of a matrix inversion algorithm. This work demonstrates the application of the theory in an experimental process, presenting a way to model and reconstruct the dynamics of response times by a high-priority task on RT-Linux.

Cuando inició la pandemia por COVID-19 y en marzo de 2020 se suspendieron las clases presenciales, se presentó un forzado acercamiento al modelo en línea, rompiendo con el paradigma vigente. No Fue hasta la etapa de post pandemia que donde surge la necesidad de presentar una evolución de los modelos educativos; esto sirvió de motivación para crear una propuesta de un Modelo Hibrido. Este modelo está conformado por tres modelos de aprendizaje: 1) aprendizaje presencial a través de la Andragogía, 2) aprendizaje auto dirigido a través de a Heutagogía y 3) aprendizaje en línea a través de un modelo Rizomático Conectivista. En este contexto, En el presente artículo se propone la integración del Aprendizaje Presencial, que en caso de la educación superior debe sustentarse en un modelo Andragógico (y no Pedagógico que se refiere a la educación de menores); Aprendizaje en línea basada en un modelo de Aprendizaje Rizomático y por ende conectivista; Aprendizaje Auto dirigido (Heutagógico) para aprendices de toda la vida (Life Long Learner) como el modelo de la nueva normalidad para el aprendizaje de Educación Superior.

Nowadays, various systems were developed in the telecommunications field which make use of technologies for the transmission and reception of information. One of these technologies is the Internet, which was developed in tandem with scientific growth. Therefore, its application in the control of various industrial processes has a notable influence. In this context, there are industrial processes that, due to the potential danger they represent to human beings, must be controlled by means of a remote control system. Such systems can be implemented through client–server communication schemes, which form a network of computers to exchange information. In the exchange of information, delay times are generated. These inactivity times have a close relationship with the latency in the communication network and have a negative impact on the performance of closed-loop control systems. In this sense, for physical implementation, it is essential to measure and mathematically characterize their magnitudes in order to know their variability and thus be able to design control strategies that compensate for their effects. Hence, this research paper presents the reconstruction of the communication times measured from a telecontrol system, where it is assumed that only one subsystem acts as the controller and the other one acts as the controlled. In other words, this paper addresses a control scheme type of single-input-single-output system (SISO). This reconstruction is based on the Kalman filter, which estimates the communication times that are measured on an experimental test bench with a client–server communication scheme. Communication times are characterized as stochastic processes. So, in order to validate the reconstruction presented, the level of dependence between the random processes is evaluated by analyzing their moments of probability as well as their covariance moments. Finally, an analysis based on the mean square error is presented, through which it can be concluded that the reconstruction technique used allows one to know the dynamics of the communication times generated by the remote control process presented in this research.

The acquisition, processing, and monitoring of biomechanical variables in dynamic environments require sensor network architectures capable of handling high concurrency and large data volumes. This study aims to develop, validate, and deploy a robust asynchronous network architecture of Inertial Measurement Units (IMUs) utilizing Bluetooth Low Energy (BLE) 5.0 for real-time biomechanical signal acquisition, overcoming the range, speed, and stability limitations of prior implementations. A network of six IMUs was implemented, with communication managed by a hybrid Python 3.10–LabVIEW 2022 Q3 framework. This architecture ensures concurrent, asynchronous data acquisition while maintaining stable sensor interconnection through virtual port emulation. System evaluation demonstrated superior technical performance, exhibiting high acquisition efficiency (close to 100%) and data loss below ±2% across 75 assessments per sensor. These assessments were obtained by evaluating the posture of 25 participants during three postural experiments, with a maximum indoor range of 40 m and an outdoor range of 105 m, validating the system’s scalability and robustness for motion capture. The approach was applied in a case study using a Fuzzy Inference System (FIS) to assess the upper limb via the Rapid Upper Limb Assessment (RULA) method. The system successfully quantified the temporal distribution of injury risk bilaterally, overcoming the limitations of observational methods and providing objective metrics crucial for occupational health in seated tasks.

A lo largo del tiempo, desde la prehistoria hasta la actual posmodernidad incluyendo la pandemia vigente, el ser humano tiene necesidad de expresar y transmitir ideas, interrogantes, pensamientos, hallazgos, sentimientos, emociones, experiencias y vivencias, y comunicarlas en su entorno. Esto es necesario para la progresión del origen de la educación y del ingenio humano para crear, inventar e innovar todo tipo de recursos para resolver problemas, dilemas y retos que han permitido generar nuevos conocimientos y avanzar en la ciencia y la tecnología de la cultura universal; esto generó la necesidad de educar y no solo de manera presencial, sino también educar a distancia. Esto motivó el desarrollo del presente trabajo, que tiene el propósito de conformar una síntesis sobre los inicios de la educación a distancia y su evolución tecnológica, abordando diferentes formas de modalidad no escolarizada y su impacto en el aprendizaje de los alumnos de todos los niveles educativos y particularmente durante el escenario provocado por el COVID-19.