Advancement in the Cuffless and Noninvasive Measurement of Blood Pressure: A Review of the Literature and Open Challenges

Cuffless Blood Pressure in clinical practice: challenges, opportunities and current limits

Background: Cuffless blood pressure measurement technologies have attracted significant attention for their potential to transform cardiovascular monitoring.Methods: This updated narrative review thoroughly examines the challenges, opportunities, and limitations associated with the implementation of cuffless blood pressure monitoring systems.Results: Diverse technologies, including photoplethysmography, tonometry, and ECG analysis, enable cuffless blood pressure measurement and are integrated into devices like smartphones and smartwatches. Signal processing emerges as a critical aspect, dictating the accuracy and reliability of readings. Despite its potential, the integration of cuffless technologies into clinical practice faces obstacles, including the need to address concerns related to accuracy, calibration, and standardization across diverse devices and patient populations. The development of robust algorithms to mitigate artifacts and environmental disturbances is essential for extracting clear physiological signals. Based on extensive research, this review emphasizes the necessity for standardized protocols, validation studies, and regulatory frameworks to ensure the reliability and safety of cuffless blood pressure monitoring devices and their implementation in mainstream medical practice. Interdisciplinary collaborations between engineers, clinicians, and regulatory bodies are crucial to address technical, clinical, and regulatory complexities during implementation. In conclusion, while cuffless blood pressure monitoring holds immense potential to transform cardiovascular care. The resolution of existing challenges and the establishment of rigorous standards are imperative for its seamless incorporation into routine clinical practice.Conclusion: The emergence of these new technologies shifts the paradigm of cardiovascular health management, presenting a new possibility for non-invasive continuous and dynamic monitoring. The concept of cuffless blood pressure measurement is viable and more finely tuned devices are expected to enter the market, which could redefine our understanding of blood pressure and hypertension.

Can Currently Available Non-invasive Continuous Blood Pressure Monitors Replace Invasive Measurement With an Arterial Catheter?

Deviations from normal blood pressure (BP) during general anesthesia have been clearly linked to several adverse outcomes. Measuring BP accurately is therefore critically important for producing excellent outcomes in health care. Normal BP does not necessarily guarantee adequate organ perfusion however and adverse events have occurred even when BP seemed adequate. Invasive blood pressure monitoring has recently evolved beyond merely measuring BP. Arterial line-derived pulse contour analysis is used now to assess both cardiac output and stroke volume variation as indices of adequate intravascular volume. Confirmation of acceptable cardiac output with data derived from invasive intra-arterial catheters has become very important when managing high-risk patients. Newer devices that measure BP continuously and non-invasively in the digital arteries via a finger cuff have also become available. Many clinicians contemplate now if these new devices are ready to replace invasive monitoring with an arterial catheter. Unlike non-invasive devices, intra-arterial catheters allow frequent blood sampling. This makes it possible to assess vital parameters like pH, hemoglobin concentration, ionized calcium, potassium, glucose, and arterial partial pressure of oxygen and carbon dioxide frequently. Non-invasive continuous BP measurement has been found to be unreliable in critically ill patients, the elderly, and patients with calcified arteries. Pulse contour-derived estimates of cardiac output and stroke volume variation have been validated better with data derived from arterial lines than that from the newer finger cuff monitors. Significant advances have been recently made with non-invasive continuous BP monitors. Invasive monitoring with an arterial line however remains the gold standard for measuring BP and assessing pulse contour analysis-derived hemodynamic variables in critically ill patients. In the future, non-invasive continuous BP monitors will likely replace intermittent oscillometers in the operating room and the postoperative period. They will however not eliminate the need for arterial catheterization in critically ill patients.

New technologies for the diagnosis, treatment, and monitoring of cardiovascular diseases

Telemedicine enables the remote provision of medical care through information and communication technologies, facilitating data transmission, patient participation, promotion of heart-healthy habits, diagnosis, early detection of acute decompensation, and monitoring and follow-up of cardiovascular diseases. Wearable devices have multiple clinical applications, ranging from arrhythmia detection to remote monitoring of chronic diseases and risk factors. Integrating these technologies safely and effectively into routine clinical practice will require a multidisciplinary approach. Technological advances and data management will increase telemonitoring strategies, which will allow greater accessibility and equity, as well as more efficient and accurate patient care. However, there are still unresolved issues, such as identifying the most appropriate technological infrastructure, integrating these data into medical records, and addressing the digital divide, which can hamper patients' adoption of remote care. This article provides an updated overview of digital tools for a more comprehensive approach to atrial fibrillation, heart failure, risk factors, and treatment adherence.

Detection of Cardiovascular Disease from Clinical Parameters Using a One-Dimensional Convolutional Neural Network

Heart disease is a significant public health problem, and early detection is crucial for effective treatment and management. Conventional and noninvasive techniques are cumbersome, time-consuming, inconvenient, expensive, and unsuitable for frequent measurement or diagnosis. With the advance of artificial intelligence (AI), new invasive techniques emerging in research are detecting heart conditions using machine learning (ML) and deep learning (DL). Machine learning models have been used with the publicly available dataset from the internet about heart health; in contrast, deep learning techniques have recently been applied to analyze electrocardiograms (ECG) or similar vital data to detect heart diseases. Significant limitations of these datasets are their small size regarding the number of patients and features and the fact that many are imbalanced datasets. Furthermore, the trained models must be more reliable and accurate in medical settings. This study proposes a hybrid one-dimensional convolutional neural network (1D CNN), which uses a large dataset accumulated from online survey data and selected features using feature selection algorithms. The 1D CNN proved to show better accuracy compared to contemporary machine learning algorithms and artificial neural networks. The non-coronary heart disease (no-CHD) and CHD validation data showed an accuracy of 80.1% and 76.9%, respectively. The model was compared with an artificial neural network, random forest, AdaBoost, and a support vector machine. Overall, 1D CNN proved to show better performance in terms of accuracy, false negative rates, and false positive rates. Similar strategies were applied for four more heart conditions, and the analysis proved that using the hybrid 1D CNN produced better accuracy.