Failure Monitoring Research Articles

Ag-Au bimetallic nanoparticle-based electrochemical sensing platform for quantification of B-type natriuretic peptide

A highly responsive and specific electrochemical biosensor utilizing Ag-Au bimetallic nanoparticles was engineered for the measurement of B-type natriuretic peptide (BNP), serving as an indicator for heart failure. The sensor was fabricated by modifying a glassy carbon electrode with Ag-Au bimetallic nanoparticles (average diameter: 20 ± 3 nm) and immobilizing anti-BNP antibodies. The sensor exhibited a wide linear range (0.0001–100 ng/mL), low limit of detection (0.03 pg/mL), and excellent specificity towards BNP, with minimal interference from other proteins (< 5 %). The practicality of the sensor was demonstrated by analyzing spiked serum samples, with recoveries ranging from 96.4 % to 103.5 % and relative standard deviations less than 4.5 %. The superior analytical property of the sensor is due to the synergistic effect of Ag and Au in enhancing electron transfer and antigen-antibody binding. The suggested biosensor holds significant promise for the early detection and monitoring of heart failure in medical environments.

Integrated biomarker profiling for enhanced heart failure management: a comprehensive study on the application of chemiluminescence detection of GDF-15 and multi-index models.

Growth differentiation factor 15 (GDF-15) holds promise as a novel marker for heart failure. However, current detection methods fall short of meeting essential clinical requirements. The aim of this investigation was to assess the clinical significance of serum GDF-15 detection through the chemiluminescence method and to enhance its clinical application for predicting and evaluating heart failure in patients. A total of 122 patients were included in the study. Serum GDF-15 levels were assessed using the chemiluminescence method and compared with results for NT-proBNP, N-terminal pro-brain natriuretic peptide (NT-proBNP), growth stimulation expressed gene 2 (ST2), high-sensitivity C-reactive protein (hs-CRP), and left ventricular ejection fraction (LVEF). Additionally, we conducted an analysis to evaluate the correlation between these indicators and heart failure events. LVEF, ST2, NT-proBNP, and GDF-15 exhibited significant associations with heart failure. In the multivariate proportional hazard analysis, subsequent to adjusting for the effects of other markers, however, only LVEF and GDF-15 retained their associations with heart failure events. Notably, GDF-15 emerged as the exclusive marker suitable for diagnosing heart failure with preserved ejection fraction. The chemiluminescence method proved efficient in the rapid and sensitive detection of GDF-15 in patients with heart failure. Additionally, GDF-15 combined with other markers created a robust multi-index model. This model is valuable for heart failure diagnosis, treatment, and monitoring, with broad clinical applicability.

Microfluidic Digital Immunoassay for Point-of-Care Detection of NT-proBNP from Whole Blood.

The high prevalence and economic burden of heart failure remain a challenge to global health. This lifelong disease leads to a buildup of permanent heart damage, making early detection and frequent monitoring crucial for effective treatment. N-terminal proBNP (NT-proBNP) is an important biomarker for monitoring the disease state, but current commercial and research NT-proBNP assays require phlebotomy and bulky equipment or do not satisfy clinical requirements such as sensitivity and detection thresholds. Here, we report a point-of-care (POC) compatible microfluidic digital immunoassay that can quantify the NT-proBNP concentration in a small volume of whole blood. Our automated microfluidic device takes whole blood samples mixed with biotinylated detection antibodies and passes through a plasma filter to react with a capture antibody-functionalized sensor surface. Streptavidin-coated gold nanoparticles (GNPs) are then released to mark the surface-bound single NT-proBNP immunocomplexes and recorded with bright-field microscopy. NT-proBNP concentrations in the sample are quantified via a hybrid digital/analog calibration curve. Digital counts of bound GNPs are used as readout signal at low concentrations for high sensitivity detection, and GNP pixel occupancies are used at high concentrations for extended dynamic range. With this approach, we detected NT-proBNP in the range of 8.24-10 000 pg/mL from 7 μL of whole blood in 10 min, with a limit of detection of 0.94 pg/mL. Finally, the method was validated with 15 clinical serum samples, showing excellent linear correlation (r = 0.998) with Roche's Elecsys proBNP II assay. This evidence indicates that this method holds promise for decentralized monitoring of heart failure.

Revealing evolution law and failure mechanism of interface damage in concrete-encased CFST columns by acoustic emission technology

Concrete-Encased Concrete-Filled Steel Tubular (CFST) has extensive applications in high-rise buildings and bridge engineering as a high-performance composite structure. The severe bond failure between Concrete-Filled Steel Tubular and the outer concrete poses a significant threat to the integrity and safety of the structure. Considering the concealed and random nature of interface damage, this study proposes a real-time monitoring and evaluation method for Concrete-Encased CFST interface damage based on acoustic emission (AE) technology. Four groups of experiments on Concrete-Encased CFST column interface shear was conducted to investigate the influence of the number of shear connectors on the bond failure mechanism between CFST and the outer concrete. The signal characteristics of three kinds of AE sensors with different operating frequency ranges were analyzed to guide the selection of sensors according to the monitoring targets. The structural damage development trend has been recognized by analyzing the change rule of AE feature parameters. RA-AF correlation analysis has been used to identify the evolution law of cracks and the failure mechanism of the structure. The b-value analysis has been used to evaluate the damage severity of the structure. From the above three aspects, the damage evolution law and failure mechanism of the interface can be revealed. The results indicate that the R3α sensor is suitable for early warning of damage, the R15α sensor can be used for monitoring and warning of structural failure, and the R6α sensor can be used to describe and evaluate the whole process of damage. Based on the features of AE hit rate, cumulative hits, and cumulative energy, the damage process of Concrete-Encased CFST column interface can be accurately divided into the elastic stage, local slip stage, shear connector fracture stage, and slip stage. The RA-AF correlation analysis showed that the shear cracks were detected to develop rapidly before the peak load, and a significant number of tensile cracks caused by cracking of the outer concrete appear around the peak load. The changes of b-value can effectively reflect the magnitude of damage and record the occurrence of major damage.

Construction of a Near-Infrared Fluorescent Probe for Dynamic Monitoring and Early Diagnosis of Heart Failure.

Cardiac hypertrophy characterized by abnormal cardiomyocyte viscosity is a typical sign of heart failure (HF) with vital importance for early diagnosis. However, current biochemical and imaging diagnostic methods are unable to detect this subclinical manifestation. In this work, we developed a series of NIR-I fluorescence probes for detecting myocardial viscosity based on the pyridazinone scaffold. The probes showed weak fluorescence due to free intramolecular rotation under low-viscosity conditions, while they displayed strong fluorescence with limited intramolecular rotation in response to a high-viscosity environment. Among them, CarVis2 exhibited higher stability and photobleaching resistance than commercial dyes. Its specific response to viscosity was not influenced by the pH and biological species. Furthermore, CarVis2 showed rapid and accurate responses to the viscosity of isoproterenol (ISO)-treated H9C2 cardiomyocytes with good biocompatibility. More importantly, CarVis2 demonstrated excellent sensitivity in monitoring myocardial viscosity variation in HF mice in vivo, potentially enabling earlier noninvasive identification of myocardial abnormalities compared to traditional clinical imaging and biomarkers. These findings revealed that CarVis2 can serve as a powerful tool to monitor myocardial viscosity, providing the potential to advance insights into a pathophysiological mechanism and offering a new reference strategy for early visual diagnosis of HF.

A Comprehensive Review on Low-Cost MEMS Accelerometers for Vibration Measurement: Types, Novel Designs, Performance Evaluation, and Applications

Maintenance of mechanical elements is considered to be the most crucial task in industry and affects the economics, predominantly. There are many techniques available for fault diagnosis and condition monitoring of rotatory machine elements and one of the popular tools is vibration monitoring. Analyzing vibrations would be useful in supervising equipment/machine components in an attempt to detect the significant change which is the cause of growing failures or faults. Broadly speaking, it comes under prognostics and health monitoring (PHM) and prevents unexpected failure and costly repair. Proficient predictive monitoring and on-board recognition of failures is a need of the Fourth Industrial Revolution. Several types of vibration analyzers and sensors are commercially available, however, their total budget is not affordable. This motivates reviewing the suitability of low-cost sensors for vibration monitoring. An inclusive review of a variety of applications wherein microelectromechanical system (MEMS)-based accelerometer is used is presented in this paper. This would support an open-design movement for creating open.

Prediction of heart failure patients with distinct left ventricular ejection fraction levels using circadian ECG features and machine learning.

Heart failure (HF) encompasses a diverse clinical spectrum, including instances of transient HF or HF with recovered ejection fraction, alongside persistent cases. This dynamic condition exhibits a growing prevalence and entails substantial healthcare expenditures, with anticipated escalation in the future. It is essential to classify HF patients into three groups based on their ejection fraction: reduced (HFrEF), mid-range (HFmEF), and preserved (HFpEF), such as for diagnosis, risk assessment, treatment choice, and the ongoing monitoring of heart failure. Nevertheless, obtaining a definitive prediction poses challenges, requiring the reliance on echocardiography. On the contrary, an electrocardiogram (ECG) provides a straightforward, quick, continuous assessment of the patient's cardiac rhythm, serving as a cost-effective adjunct to echocardiography. In this research, we evaluate several machine learning (ML)-based classification models, such as K-nearest neighbors (KNN), neural networks (NN), support vector machines (SVM), and decision trees (TREE), to classify left ventricular ejection fraction (LVEF) for three categories of HF patients at hourly intervals, using 24-hour ECG recordings. Information from heterogeneous group of 303 heart failure patients, encompassing HFpEF, HFmEF, or HFrEF classes, was acquired from a multicenter dataset involving both American and Greek populations. Features extracted from ECG data were employed to train the aforementioned ML classification models, with the training occurring in one-hour intervals. To optimize the classification of LVEF levels in coronary artery disease (CAD) patients, a nested cross-validation approach was employed for hyperparameter tuning. HF patients were best classified using TREE and KNN models, with an overall accuracy of 91.2% and 90.9%, and average area under the curve of the receiver operating characteristics (AUROC) of 0.98, and 0.99, respectively. Furthermore, according to the experimental findings, the time periods of midnight-1 am, 8-9 am, and 10-11 pm were the ones that contributed to the highest classification accuracy. The results pave the way for creating an automated screening system tailored for patients with CAD, utilizing optimal measurement timings aligned with their circadian cycles.

Infrared temperature evolution law and thermal effect mechanism of concrete impact failure

Concrete impact failure can occur quickly and cause severe failure, which is of great significance for effective monitoring of concrete impact failure. Infrared thermal imaging technology possesses the merits of high sensitivity, noncontact, and nondestructive monitoring, rendering it extensively employed in monitoring the stability of concrete structures. However, the infrared radiation temperature (IRT) evolution law and thermal effect mechanism of concrete impact failure are not clear at present. In this study, infrared monitoring experiments were conducted on concrete impact failure and static load failure using drop hammer (DH) testing machines, pressure testing machines, and infrared thermal imagers. The infrared thermal images and the IRT change law of concrete subjected to DH impact failure were analysed. The infrared thermal effect difference and mechanism between DH impact and static load failure were compared. The results indicate that there is an infrared high-temperature point at the impact location of concrete DH impact failure, and both average infrared radiation temperature (AIRT) and maximum infrared radiation temperature (MIRT) increase suddenly. The increase in the MIRT is tens of times that of the AIRT. Compared with that of static load failure, the infrared high-temperature area of concrete DH impact failure is concentrated, while the IRT of static load failure increases overall, and the heating area is large. Moreover, the change in the IRT under DH impact failure is much greater than that under static load failure. The infrared thermal effect of concrete under DH impact failure was mainly composed of the thermoelastic effect, frictional thermal effect and tensile failure endothermic effect. The infrared data obtained for concrete impact failure should focus on the highest and lowest IRT change indicators. The highest IRT corresponds to the impact failure point, and the lowest IRT corresponds to the tensile failure position. The research results provide a new infrared thermal effect approach for monitoring the stability of concrete under impact failure.

The Future of Telemedicine for Obstructive Sleep Apnea Treatment: A Narrative Review.

Obstructive sleep apnea is a common type of sleep-disordered breathing associated with multiple comorbidities. Nearly a billion people are estimated to have obstructive sleep apnea, which carries a substantial economic burden, but under-diagnosis is still a problem. Continuous positive airway pressure (CPAP) is the first-line treatment for OSAS. Telemedicine-based interventions (TM) have been evaluated to improve access to diagnosis, increase CPAP adherence, and contribute to easing the follow-up process, allowing healthcare facilities to provide patient-centered care. This narrative review summarizes the evidence available regarding the potential future of telemedicine in the management pathway of OSA. The potential of home sleep studies to improve OSA diagnosis and the importance of remote monitoring for tracking treatment adherence and failure and to contribute to developing patient engagement tools will be presented. Further studies are needed to explore the impact of shifting from teleconsultations to collaborative care models where patients are placed at the center of their care.

Experimental study of the “AE quiet period” on the eve of brittle failure in hard rock

Acoustic emission (AE) signals on the eve of brittle failure in hard rock often indicate a quiet period, i.e., a significant decrease in the number of AE signals. To address the current problem of the poor understanding of the quiet period, the failure process of hard rock was simulated by tests and acquired the AE signals. The AE signal during the quiet period were analyzed. First, compared with the AE signals in other loading periods, the AE signals during the quiet period are characterized by a greater hit amplitude, a greater rise time and ring count, a sudden increase in the cumulative absolute energy, a greater amplitude of the signals in the main frequency band and so on. Second, the inhomogeneity of rock grains, stress level and loading rate all have a nonnegligible influence. The more inhomogeneous the rock grains are, the higher the stress level is, or the larger the loading rate is, the longer the duration of the quiet period is. Third, a hard rock damage evolution equation based on AE considering the effect of the quiet period is proposed, which can reasonably reflect the objective fact of accelerating damage during this period. Finally, the quiet period is due to the brittle failure of hard rock with inhomogeneous grains under high stress conditions, so identifying the quiet period is important for AE-based monitoring and warning of hard rock failure.

Virtual Simulation Design and Debugging of Lift-and-Transverse Stereo Garage Based on the Digital Twin

In the face of the challenges of limited urban space and the continuous increase of vehicles, stereo garages have been widely used as a solution in cities. In order to improve the automation and intelligence level of the stereo garage, this paper applies the digital twin technology to the lift-and-transverse stereo garage. A five-dimensional model of a digital twin has been developed based on an actual stereo garage. Combined with S7-PLCSIM Advanced, Botu TIA Portal, and NX MCD to build a virtual simulation platform, realizing the virtual simulation design and debugging of the digital twin-based stereo garage. This approach allows to test and optimize operational processes without relying on physical equipment, reducing labor and field debugging costs, shortening deployment cycles, and significantly reducing development costs. In addition, MCD allows real-time monitoring and control of security risks and failures detected. Finally, the feasibility of the virtual simulation and debugging scheme based on digital twin is verified by comparing the operation data of the virtual model and the actual stereo garage, which provides new ideas for the intelligent development of stereo garage but also can be used as an important reference for the development of equipment in other areas.

Experimental study on response and precursor of pressure stimulated currents of combined coal-rock under cycling stress

The coal-rock combination body is prone to rock burst and surface subsidence under loading, and adopting effective monitoring methods are valuable. In this paper, cyclic loading and unloading (CLU) tests were conducted to investigate the response and precursor of pressure stimulated currents (PSCs) in coal-rock combination samples. The results indicate that the PSCs of the coal-rock combination samples have good response characteristics to stress. Furthermore, the PSCs between the two components are significantly larger and more stable than those of the coal body, which can clearly reflect the failure under a progressive failure mechanism and are related to the difference in the resistivities and microstructures of the components. During the CLU tests, the PSCs of each cycle are well fitted by the Gaussian distribution and have a memory effect. During the loading or unloading process of each cycle, the variation in PSCs with stress conforms to the power function relationship with exponent k. As the cycle number increases, the rates of increase in PSC under stress are gradually weakened, and the indexes of PSCs including exponent k increase or decrease sharply first and then remain stable or even decrease, which is due to the loading history. The stable state of these indexes with obvious inflection points in later cycles of CLU tests can be considered a precursor of coal-rock failure. The PSC flow direction between the two components is exactly opposite to that in the coal body. The results provide new ideas for the monitoring and prediction of coal-rock combination body failure, which is helpful for the prevention of geological disasters in mines.

Study on the method of transfer alignment based on the distributed inertial network of guided submunition

Aiming at the problem of poor transfer alignment accuracy between missiles with a high length-to-diameter ratio as a carrier missile and the internally carried guided submunition, this study proposes a transfer alignment method based on the distributed inertial network of the guided submunition. Initially, considering the influence of the deflection deformation of the carrier missile body and the dynamic nonlinear deformation of the lever arm on the transfer alignment accuracy, the corresponding error model is established and compensated for the sub-inertial guide velocity to improve the accuracy of the observed quantities. Additionally, in response to the high failure rate of low-cost inertial guidance systems equipped with guided submunition, we used an inertial network data fusion architecture based on the isolation of device failure monitoring, which effectively isolates the faulty data through the fusion of inertial measurements at the sensor level and optimal fusion of filtering to further improve the reliability of transmission alignment. The effectiveness of the method proposed in this paper is verified through a large number of simulation experiments. Compared with the traditional transfer alignment method between a single master inertial guide and a sub inertial guide, the method in the paper has obvious improvement in the transfer alignment accuracy. In addition, this method is not affected by the failure of inertial devices in the distributed inertial network, and can continuously maintain a high transfer alignment accuracy. For this kind of missile-borne distributed inertial network with a sub-node sets layer, it is found after comparison that: the transmission alignment error is basically the same for different slave nodes in the same sub-node sets; between different sub-node sets, the closer to the master inertial guide the transmission alignment error is smaller. This study provides a new solution idea and certain reference value for solving the problem of poor transfer alignment accuracy between missiles with a high length-to-diameter ratio as a carrier missile and the internally carried guided submunition.

Combined acoustic methods in monitoring the crack development in granite

Detecting cracks of various sizes is crucial for monitoring and predicting rock failure. This study combines two acoustic methods—the passive acoustic emission (AE) and the active ultrasonic P-wave velocity to investigate the cracking process from initiation to propagation and coalescence of rocks containing pre-existing flaws, which simulate the intrinsic defects in natural rocks or rock masses, across different scales in three-dimensional space. The resultant AE activity is found sensitive to microcracks even in the early loading stage and can be divided into three stages: quiet, stable, and high growth periods. The positions of the microcracks can be obtained with the assistance of several AE sensors. It is also found that the P-wave velocity attenuation is more sensitive to macrocracks but less sensitive to microcracks. The results indicate that combining the AE and active ultrasonic-wave methods can provide comprehensive information to evaluate the damage levels and localize the internal cracks with multiple scales in the entire cracking process of rocks. The study also indicates the potential for predicting crack coalescence and failure based on the combination of these two nondestructive methods. In addition, the findings can also be applicable in the monitoring and prediction of failure in other brittle materials.

Remote monitoring of severe heart failure.

Patients with advanced heart failure, due to the instability of their clinical conditions, need close surveillance to avoid dangerous exacerbations or sudden events. Digital technology can be of great help in this contest, thanks to remote monitoring, made possible with the use of wearable or implantable instruments. The latter are currently generally inserted inside defibrillators or resynchronization systems, or inserted inside the pulmonary circulation for monitoring pulmonary pressure. Parameters such as thoracic impedance, physical activity, heart rate variability, atrial and ventricular arrhythmias, blood pressure, and O2 saturation can be controlled remotely. The data relating to the actual benefit in terms of avoidable events (death and hospitalizations) are not definitive, but certainly from an organizational point of view, the benefit is evident, both on the part of the patient and of the organization of care. The latter, provided in the form of televisits, requires a re-modulation of the system, making use of trained personnel, a well-structured network, and digital technologies (platforms, electronic health records) that are not yet perfectly developed. The evolution of the solutions offered by artificial intelligence guarantees a rapid and progressive refinement of telemedicine in this sector.

Co-design with affect stories and applied ethics for health technologies

The integration of digital health technologies in clinical practices and everyday lives of patients raises several issues. Some of them are related to applied ethics. Co-design with patients and, more generally, participatory approaches are increasingly seen as a way to tackle these issues early in the innovation process. This opens the way to an “ethics by co-design.” In this article, we will present the high ambitions of this approach and discuss three challenges raised by ethics by co-design. We will argue that a co-design approach based on affect stories is a way to address these challenges. Then we will focus on a concrete example of a European research project, to discuss the gap between these ethical and theoretical ambitions and what can be achieved in practice. This project aimed at developing an implantable connected device for the monitoring of heart failure, while addressing the ethical, legal and social issues raised by this new technology. However, co-design with patient representatives was in fact limited to a small part of the project: the design of an information module. Based on 18 meetings with a team of 4 patient partners, and 26 additional interviews with patients, we were able to better understand patients’ experiences and priorities in terms of ethics. Together, we co-designed an information module that embodies a vision of the device negotiated between the patients and the technology designers.

Photoplethysmography and intracardiac pressures: early insights from a pilot study.

Invasive haemodynamic monitoring of heart failure (HF) is used to detect deterioration in an early phase thereby preventing hospitalizations. However, this invasive approach is costly and presently lacks widespread accessibility. Hence, there is a pressing need to identify an alternative non-invasive method that is reliable and more readily available. In this pilot study, we investigated the relation between wrist-derived photoplethysmography (PPG) signals and the invasively measured pulmonary capillary wedge pressure (PCWP). Fourteen patients with aortic valve stenosis who underwent transcatheter aortic valve replacement with concomitant right heart catheterization and PPG measurements were included. Six unique features of the PPG signals [heart rate, heart rate variability, systolic amplitude (SA), diastolic amplitude, crest time (CT), and large artery stiffness index (LASI)] were extracted. These features were used to estimate the continuous PCWP values and the categorized PCWP (low < 12 mmHg vs. high ≥ 12 mmHg). All PPG features resulted in regression models that showed low correlations with the invasively measured PCWP. Classification models resulted in higher performances: the model based on the SA and the model based on the LASI both resulted in an area under the curve (AUC) of 0.86 and the model based on the CT resulted in an AUC of 0.72. These results demonstrate the capability to non-invasively classify patients into clinically meaningful categories of PCWP using PPG signals from a wrist-worn wearable device. To enhance and fully explore its potential, the relationship between PPG and PCWP should be further investigated in a larger cohort of HF patients.

Combined ambient vibration and surface displacement measurements for improved progressive failure monitoring at a toppling rock slab in Utah, USA

Seismic resonance and surface displacement measurements can be implemented in tandem to improve landslide characterization and progressive failure monitoring. Crack aperture data are frequently used in rock slope stability monitoring and often exhibit recognizable trends prior to failure, such as accelerated crack opening. Alternatively, ambient resonance data offer multiple parameters including modal frequencies, damping, and polarization that can be monitored alongside crack aperture and may respond differently to environmental forcings and complex failure evolution. We analyzed data from continuous ambient vibration monitoring and concomitant crack aperture measurements at the Courthouse Mesa instability, a large toppling sandstone slab in Utah, USA. Three years of data revealed crack aperture increases of 2–4 mm/year with no clearly detectable irreversible changes in modal parameters, including frequency. Annually, frequency and displacement varied by 29% and 19% of the mean, respectively, with average and maximum daily frequency fluctuations of 6.5% and 16%, respectively. These reversible cyclic changes were primarily temperature-driven, but annually, frequency was in-phase with temperature whereas crack aperture lagged temperature changes by ∼37 days. Polarization and damping also varied seasonally but were less strongly correlated with temperature. Conceptual 3D finite element modeling demonstrated consistent frequency decreases associated with crack propagation but variable changes in crack aperture measured at a single point; i.e., crack propagation did not always result in increased crack opening but always generated a resonance frequency decrease. Taken together, our data suggest a possible thermal wedging-ratcheting mechanism at the Courthouse Mesa instability, where annual thermoelastic crack closure is impeded by debris infill but the absence of downward crack propagation during the monitoring period is evidenced by no permanent resonance frequency changes. Our study demonstrates that combined seismic resonance and crack aperture data provide an improved description of rock slope instability behavior, supporting refined characterization and monitoring of changes accompanying progressive failure.

Failure monitoring of rubber products reinforced with waste fibers of tire recycling process

Failure monitoring of rubber products reinforced with waste fibers of tire recycling process

A Set of Possible Markers for Monitoring Heart Failure and Cognitive Impairment Associated: A Review of Literature from the Past 5 Years.

Heart failure is an epidemiologically relevant disease because of the aging population and widespread lifestyles that promote it. In addition to the acute event, it is possible for the disease to become chronic with periodic flare-ups. It is essential to study pathology from a diagnostic and prognostic point of view and to identify parameters for effective monitoring. In addition, heart failure is associated with multiple comorbidities, including cognitive impairment, which is monitored clinically but not through specific biomarkers in these patients. The purpose of this review is to gather the most recent scientific evidence on a few possible biomarkers previously identified for monitoring heart failure and associated cognitive impairment. We surveyed studies inherent to a set of previously identified markers, evaluating English-language articles from the past five years conducted in adult heart failure patient populations. We used the databases PubMed, Web of Sciences, and Cochrane Library for search studies, and we considered articles published in journals with an impact factor greater than five in the publication year. Among the biomarkers evaluated, a concordant indication for serial measurements for heart failure monitoring emerged only for interleukin-6. For the other markers, there is still little evidence available, which is interesting but sometimes conflicting. Interesting studies have also emerged for biomarkers of cognitive decline assessed in patients with heart failure, confirming the hypotheses of the increasingly studied heart-brain correlation. Certainly, further studies in large populations are needed to identify effective biomarkers for monitoring heart failure and associated cognitive impairment.