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As the population of older adults increases worldwide, the number of individuals afflicted with cardiovascular issues and diseases is also increasing. The rate at which individuals worldwide succumb to cardiovascular disease (CVD) is rising as well. That is, the World Health Organization (WHO) reports that the number one cause of death globally is from CVD either in the form of myocardial infarctions or strokes. The primary ways of assisting individuals with CVD are from either improved treatments, monitoring research, or primary and secondary prevention measures. In the form of cardiovascular structural monitoring, ultrasonography is very prevalent and allows for multiple configurations, is the least expensive, and has no detrimental side effects to the patient.

This is the proof of concept study that investigates how we can combine a wearable ultrasound vest of multiple 2D transducers to create a 3D model of the heart for continuous monitoring. Furthermore, we create functional models to represent the states the heart can be in both respect to normal operations as well as Atrial Fibrillation.

Using the wearable ultrasound vest created in our previous work, a 3D model is created via a structure from motion approach with synthetic data. Also, a denoising process is created to assist the modeling process. The 3D model is constructed with up to three views. That is, via the parasternal, frontal, and apical views where the frontal view is the halfway point between the apical and parasternal views. Furthermore, stochastic petri nets (SPN) are created to represent the cyclic states of the heart.

The experimental results show a 3D model of the synthetic heart constructed from a point cloud created by the structure from the motion approach. Then, it is successfully denoised with our outlier detection and removal process. The resulting 3D model allows us to calculate surface areas and perform the continuous monitoring we initially set out to do. Finally, multiple SPN models are created for functional feature extraction as well as to assist medical professionals in continuous cardiovascular monitoring.

In this paper, we demonstrated the structure from the motion approach to create a 3D model of the heart with our wearable ultrasound vest construction. Furthermore, we provided multiple SPN models for functional feature extraction and to monitor a normal heart and a heart affected by Atrial Fibrillation.

Cardiovascular disease (CVD) is the leading cause of global mortality in the modern world. This situation is difficult to predict and requires a combination of advanced techniques and specialist knowledge. Healthcare systems have recently adopted the Internet of Things (IoT) to collect critical sensor data to diagnose and predict CVD. Predictive models can be made more accurate and effective through such integration, which could radically change how we manage cardiovascular health. This study presents an improved squirrel search optimization algorithm for searching vital indications of CVD. To address the issue of low-cardiac diagnostic accuracy, the proposed IoT system uses enhanced squirrel search optimization with deep convolutional neural networks (SSO-DCNN). This new approach uses data from smartwatches and cardiac devices, which monitor patients’ electrocardiogram (ECG) and blood pressure readings. The proposed SSO-DCNN performs well compared to well-known deep learning networks such as logistic regression. The findings show an accuracy of 99.1% over current classifiers, suggesting effectiveness in the CVD prediction.

In recent decades, cardiovascular disease and stroke are recognized as the most important reason for the high death rate. Irregular bloodstream and the circulatory system are the main reason for this issue. In this paper, Computational Fluid dynamic method is employed to study the impacts of the flow pattern inside the cerebral aneurysm for detection of the hemorrhage of the aneurysm. To achieve a reliable outcome, blood flow is considered as a non-Newtonian fluid with a power-law model. In this study, the influence of the blood viscosity and velocity on the pressure distribution and average wall shear stress (AWSS) are comprehensively studied. Moreover, the flow pattern inside the aneurysm is investigated to obtain the high-risk regions for the rupture of the aneurysm. Our results indicate that the wall shear stress (WSS) increases with increasing blood flow velocity. Furthermore, the risk of aneurysm rupture is considerably increased when the AWSS increases more than 0.6. Indeed, the blood flow with high viscosity expands the high-risk region on the wall of the aneurysm. Blood flow indicates that the angle of the incoming bloodstream is substantially effective in the high-risk region on the aneurysm wall. The augmentation of the blood velocity and vortices considerably increases the risk of hemorrhage of the aneurysm.

In the recent decades, the main reason for the high death rate is related to cardiovascular disease and stroke. In this paper, numerical studies have been done to investigate the hemodynamic effects on the rupture of middle cerebral artery (MCA) in different working conditions. In this work, the effects of the blood viscosity and velocity on the pressure distribution and average wall shear stress (AWSS) are fully investigated. Also, the flow pattern inside the aneurysm is investigated to obtain the high-risk regions for the rupture of the aneurysm. Our findings show that the wall shear stress increases with increasing the blood flow velocity. Meanwhile, the risk of aneurysm rupture is considerably increased when the AWSS increases more than 0.6. In fact, the blood flow with high viscosity expands the high-risk region on the wall of the aneurysm. Blood flow indicates that the angle of the incoming bloodstream is substantially effective in the high-risk region on the aneurysm wall. The augmentation of the blood velocity and vortices considerably increases the risk of hemorrhage of the aneurysm.

Cardiovascular disease continues to be the leading cause of death in the US. Recent studies found that reactive oxygen species (ROS) have been incriminated in the pathogenesis of both acute and chronic heart diseas. Many botanicals possess antioxidant properties, and these herbal antioxidants may protect against cardiovascular diseases by contributing to the total antioxidant defense system of the human body. In this article, we reviewed the antioxidant components and properties of four putative antioxidant botanicals (i.e., grape seeds, green tea, Scutellaria baicalensis, and American ginseng), and their potential role in treating cardiovascular illness. The antioxidant activities of the herbal active constituents, and the relationship between their chemical structures and biological functions were also discussed. Further investigations are needed on the mechanisms of action of these botanicals as they affect salient cellular and molecular pathways involved in major diseases. Data obtained from future studies will have the potential for translation into practical benefits for human health.

Ischemic heart disease (IHD) is one of the leading causes of death in Western countries. Prevention rather than treatment of heart disease can significantly improve patients' quality of life and reduce health care costs. Flavonoids are widely distributed in vegetables, fruits and herbal medicines. Regularly consuming botanicals, especially those containing flavonoids, has been associated with a reduction in cardiovascualar disease; thus, it is important to investigate how flavonoids improve cardiac resistance to heart disease and their related mechanisms of action. It has been shown that cardiomyocyte injury and death can result from ischemia-reperfusion, which is pathognomonic of ischemic heart disease. Massive reactive oxygen species (ROS) release at the onset of reperfusion produces cell injury and death. "Programming" the heart to either generate less ROS or to increase strategic ROS removal could reduce reperfusion response. Additionally, profuse nitric oxide (NO) release at reperfusion could be protective in "preconditioning" models. Botanical flavonoids induce preconditioning of the heart, thereby protecting against ischemia-reperfusion injury. In this article, we will discuss two herbs containing potent flavonoids, Scutellaria baicalensis and grape seed proanthocyanidin, which can potentially offer cardiac protection against ischemic heart disease.

The aim of this study was to determine the effect of combination therapy consisting of acupuncture and traditional herbal medicine (Kampo medicine) for reducing the incidence rate of delirium in patients with cardiovascular (CV) disease in ICUs. Twenty-nine patients who had been urgently admitted to the ICU in the control period were treated with conventional intensive care. Thirty patients in the treatment period received conventional therapy plus a combination therapy consisting of acupuncture and herbal medicine. Acupuncture treatment was performed once a day, and the herbal formula was administered orally three times a day during the first week of the ICU stay. The standard acupuncture points were GV20, Ex-HN3, HT7, LI4, Liv3, and KI3, and the main herbal preparation was Kamikihito. The incident rates of delirium, assessed using the confusion assessment method for ICU, in the treatment and control period were compared. The incidence rate of delirium was significantly lower in the treatment group than in the control group (6.6% vs. 37.9%, $P<0.01$). Moreover, sedative drugs and non-pharmacological approaches against aggressive behavior of patients who were delirious were used less in the treatment group than in the control group. No serious adverse events were observed in the treatment group. Combination therapy consisting of acupuncture and herbal medicine was found to be effective in lowering the incidence of delirium in patients with CV disease in ICUs. Further studies with a large sample size and parallel randomized controlled design would be required to establish the effects of this therapy.

Autophagy refers to the process in which the cellular lysosome degrades the cell’s own damaged organelles and related macromolecule substances. It plays important roles in the homeostasis of organs, cell survival, and stable development. Previous studies indicate that the process of cardiopathology is closely associated with autophagy and some of Chinese medicines (active compounds and formulae) are found to have beneficial effects on injured cardiomyocytes via the modulation of autophagy. This review highlights the efficacy of the action of Chinese medicine on the regulation of myocardial autophagy and summarizes the related molecular and signal mechanisms. Our study discovers that some active compounds and formulae of Chinese medicines react on the specific targets of autophagy in related signal pathways to exert protective effects in the processes of ischemia and reperfusion, as well as, in other cardiopathological models. Parts of these compounds even have the characteristics of multiple targets in autophagic signal pathways and dual-directional regulated actions on autophagy, suggesting that Chinese medicines, which possess the ability to modulate autophagy, might improve effective cardio protection in the treatment of cardiovascular disease.

Many cultivated and wild plants are used for the management of various diseases, specifically renal and hepatic diseases and those of the immune and cardiovascular systems. In China, medicinal plants from ancient to modern history have been used in patients with angina pectoris, congestive heart failure (CHF), systolic hypertension, arrhythmia, and venous insufficiency for centuries. The latest increase in the fame of natural products and alternative medicine has revived interest in conventional remedies that have been consumed in the management of CVD. The cardio-protective properties of the various herbs are possibly due to their anti-oxidative, antihypercholesterolemic, anti-ischemic activities, and inhibition of platelet aggregation that reduce the risk of CVD. Ethno-pharmacological and biological properties of these plants are explored, based upon published scientific literature. Although a majority of medicinal plants having a biological mechanism that linked with CVD management, to date, published literature pertaining to their promising scientific properties are still poorly understood. Compared with synthetic medicines, alternative medicines do not need scientific studies before their formal approval from the government sector and due to this purpose; their safety, as well as efficacy, still remain elusive. Taken together, we addressed all accessible evidence on alternative medicines commonly consumed in CVD management. Our comprehensive analysis of the scientific literature indicated that many TCMs are available and valuable herbal medication would be the best alternative for the management of CVD as a complementary therapy. Furthermore, practitioners should always discuss possible benefits–risks of alternative medicines with patients so that they are aware of the consumption of alternative medications.

Healthcare is indeed an inevitable part of life for everyone. In recent days, most of the deaths have been happening because of noncommunicable diseases. Despite the significant advancements in medical diagnosis, cardiovascular diseases are still the most prominent cause of mortality worldwide. With recent innovations in Machine Learning (ML) and Deep Learning (DL) techniques, there has been an enormous surge in the clinical field, especially in cardiology. Several ML and DL algorithms are useful for predicting cardiovascular diseases. The predictive capability of these algorithms is promising for various cardiovascular diseases like coronary artery disease, arrhythmia, heart failure, and others. We also review the lung interactions during heart disease. After the study of various ML and DL models with different datasets, the performance of the various strategies is analyzed. In this study, we focused on the analysis of various ML and DL algorithms to diagnose cardiovascular disease. In this paper, we also presented a detailed analysis of heart failure detection and various risk factors. This paper may be helpful to researchers in studying various algorithms and finding an optimal algorithm for their dataset.

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