Internet of Things (IoT) technologies allow building a digital representation of people, objects, or physical phenomena to be available on the Internet. Thus, stakeholders can access this information from remote places or computational systems could analyze this data to find patterns, make decisions, or execute actions. For instance, a doctor could diagnose patients by analyzing the received data from an IoT system even when patients are located in a remote place. This article proposes an IoT system for monitoring electrocardiogram (ECG) signal and processing heart data in order to generate an alert when an arrhythmia is present. This system involves a Polar H10 heart sensor, machine‐learning models to classify heart events, and communication technology to share and store patient’s information. In the first place, the architecture of the IoT monitoring system and the communication between the components are described by discussing the designing criteria. Second, the experimentation process performs the training and the assessment of three classification algorithms, random forest, convolutional neural network, and k‐nearest neighbors. The results show that k‐nearest neighbor has the best accuracy percentage classifying the arrhythmias under study (premature ventricular contraction 94%, fusion of ventricular beat 81%, and supraventricular premature beat 82%); also, it is able to discern normal and unclassifiable beats with 93% and 97%, respectively.

Background: Our aim was to determine the differences in short-term heart rate variability (HRV) between patients with metabolic syndrome (MS) and healthy controls. Methods: We searched electronic databases for primary works with short-term HRV recordings (≤30 min) that made comparisons between individuals with MS versus healthy controls. This systematic review and meta-analysis (MA) was performed according to PRISMA guidelines and registered at PROSPERO (CRD42022358975). Results: Twenty-eight articles were included in the qualitative synthesis and nineteen met the criteria for the MA. Patients with MS showed decreased SDNN (−0.36 [−0.44, −0.28], p < 0.001), rMSSD (−7.59 [−9.98, −5.19], p < 0.001), HF (−0.36 [−0.51, −0.20], p < 0.00001) and LF (−0.24 [−0.38, −0.1], p = 0.001). In subsequent subanalyses, we found a decrease in SDNN (−0.99 (−1.45, −0.52], p < 0.001), rMSSD (−10.18 [−16.85, −3.52], p < 0.01) and HF (−1.04 [−1.97, −0.1] p < 0.05) in women. In men, only LF showed a significant lower value (−0.26 [−0.5, −0.02], p < 0.05). We could not perform MA for non-linear variables. Conclusions: Patients with MS showed changes in time-domain analyses, with lower values in SDNN and rMSSD. Regarding frequency-domain analyses, MS patients showed a decrease in HF and LF When sex was used as a grouping variable, the MA was only possible in one of both sexes (men or women) in rMSSD and LF/HF. Lastly, when data for both men and women were available, subanalyses showed a different behavior compared to mixed analyses for SDNN, HF and LF, which might point towards a different impact of MS in men and women.

Background: Our aim was to determine the impact that metabolic syndrome (MS) produces in long-term heart rate variability (HRV), quantitatively synthesizing the results of published studies to characterize the cardiac autonomic dysfunction in MS. Methods: We searched electronic databases for original research works with long-term HRV recordings (24 h) that compared people with MS (MS+) versus healthy people as a control group (MS−). This systematic review and meta-analysis (MA) was performed according to PRISMA guidelines and registered at PROSPERO (CRD42022358975). Results: A total of 13 articles were included in the qualitative synthesis, and 7 of them met the required criteria to be included in the MA. SDNN (−0.33 [−0.57, 0.09], p = 0.008), LF (−0.32 [−0.41, −0.23], p < 0.00001), VLF (−0.21 [−0.31, −0.10], p = 0.0001) and TP (−0.20 [−0.33, −0.07], p = 0.002) decreased in patients with MS. The rMSSD (p = 0.41), HF (p = 0.06) and LF/HF ratio (p = 0.64) were not modified. Conclusions: In long-term recordings (24 h), SDNN, LF, VLF and TP were consistently decreased in patients with MS. Other parameters that could be included in the quantitative analysis were not modified in MS+ patients (rMSSD, HF, ratio LF/HF). Regarding non-linear analyses, the results are not conclusive due to the low number of datasets found, which prevented us from conducting an MA.

El Objetivo de este trabajo fue determinar la importancia de la práctica de actividad física (AF) durante el tiempo de aislamiento social y confinamiento, y sus efectos positivos para enfrentar las consecuencias sobre la salud física y mental, ocasionadas por el COVID-19. Para ello, se realizó una revisión sistemática de la literatura disponible en bases de datos especializadas PUBMED, SCIELO, EBSCO y OVID, la cual se ajustó a las directrices enmarcadas en la metodología PRISMA. Se definieron ecuaciones de búsqueda bajo los términos MESH: physical activity, exercise, sport, covid 19, sars cov 2 y utilizando caracteres booleanos AND y OR. Con estas ecuaciones se buscaron artículos publicados entre febrero y mayo de 2020, recuperando 53 registros en total e incluyendo en la revisión final 16 de ellos que cumplían con todos los criterios de inclusión y de exclusión definidos. Los resultados sugieren que la práctica regular de AF podría ser una herramienta importante para combatir los efectos adversos ocasionados sobre el organismo debido a la infección por COVID-19 y esto porque: a) mejora la respuesta del sistema inmunológico ante una posible infección por COVID-19; b) aumenta la acción del eje ECA2-Ang.1,7-Rec.Mas., el cual favorece estadios antiinflamatorios, antitrombóticos y disminuye el estrés oxidativo; c) disminuye la incidencia o ayuda en el control de las principales comorbilidades que predisponen al desarrollo de síntomas más severos y que aumentan el riesgo de mortalidad ante la infección por COVID-19. Con estos hallazgos se concluye que la práctica regular de AF es necesaria para enfrentar la actual situación de pandemia, ya que ayuda, no solo al mantenimiento de la buena condición de salud física y mental durante el periodo de aislamiento social y confinamiento, sino que también parece ofrecer una mejor respuesta ante la infección por COVID-19, disminuyendo el riesgo de mortalidad.

Metabolic syndrome (MetS) has been associated with an increased prevalence of cardiac arrhythmias and sudden cardiac death caused by ventricular fibrillation (VF), but the exact underlying mechanisms are not known. Our aim here was to study the effects that diet‐induced MetS produces on ventricular remodelling and its potential electrophysiological arrhythmogenic mechanisms. Thirty‐five male NZW rabbits were assigned to a control (n = 16) or MetS group (n = 19), fed for 28 weeks with a high‐fat and high‐sucrose diet. Echocardiography and electrocardiography were performed before diet and at weeks 14 and 28. Hearts were isolated and perfused in a Langendorff system and epicardial optical mapping was performed using two EMCCD cameras focused on the left (LV) and right (RV) ventricles. mRNA expression levels for ion channel proteins were examined by quantitative RT‐PCR. A mixed‐model ANOVA and unpaired t test were used for statistical analysis. MetS animals showed LV hypertrophy and electrophysiological abnormalities (increased PQ, QRS, QTc and T wave). In isolated hearts, MetS animals had shorter optical APD90 (action potential duration at 90% repolarization), increased restitution slope and alternans, and faster frequency of activation during VF in the RV, whereas no difference was observed in the LV. The mRNA expression for KvLQT1 and KChIP2 increased in the RV. MetS produced LV hypertrophy, and altered atrioventricular and ventricular conduction and repolarization abnormalities. In isolated hearts, the physiological gradients of refractoriness and frequency of activation during VF were abolished in MetS animals, with fast activation rates in both ventricles, which could be explained, at least in part, by upregulation of KvLQT1 and KChIP2 in the RV. image Key points: Metabolic syndrome (MetS) has been associated with ventricular arrhythmias and sudden cardiac death, but the exact underlying mechanisms are not known. Previous studies have addressed the effects that individual components of MetS exert, individually, upon electrical cardiac remodelling, but the results obtained in some cases prove inconclusive or contradictory. We investigated the effects of diet‐induced MetS on ventricular remodelling and its potential electrophysiological arrhythmogenic mechanisms. We found that diet‐induced MetS produced altered activation–repolarization abnormalities as well as fast‐activation non‐stable flattening of the spatial distribution of dominant frequencies driving ventricular fibrillation, which might be explained, at least in part, due to increased expression of potassium channels in the right ventricle.

Background/Objectives: Heart rate variability (HRV) is a reliable, non-invasive marker of autonomic nervous system function and is often impaired in individuals with metabolic syndrome (MetS). Physical exercise has emerged as an effective strategy to improve autonomic modulation; however, the comparative effects of different training modalities on HRV in individuals with MetS remain unclear. This systematic review and meta-analysis aimed to evaluate the impact of various exercise interventions on HRV and to identify which training types yield the most significant improvements. Methods: A systematic search was conducted in PubMed and Scopus up to April 2025. Eligible studies (n = 16) included adults with obesity and MetS (n = 752) who underwent structured exercise interventions with HRV assessments pre- and post-intervention. Standardized mean differences were calculated using random effects models. Subgroup analyses were performed based on training modality (endurance training [ET], resistance training [RT], high-intensity interval training [HIIT], and concurrent training [CT]). Results: Sixteen studies of moderate to high quality were included, with eleven studies eligible for meta-analysis. ET and HIIT significantly improved time-domain indices (Root mean square of differences of successive R-R intervals —rMSSD—, Standard deviation of the R-R interval series —SDNN—) and frequency-domain parameters (high-frequency —HF—), suggesting enhanced parasympathetic activity. RT showed inconsistent effects, while CT improved long-term HF and total power (TP). Non-linear indices were the least reported due to insufficient data. Conclusions: Physical exercise—particularly ET and HIIT—appears to enhance cardiac autonomic modulation in individuals with obesity and MetS. These findings support incorporating targeted training strategies into clinical practice to optimize cardiovascular health in these populations.