Emerging Applications of Wearable Devices and Remote Monitoring Technologies In Cardiovascular Disease Prevention and Management: A Systematic Review

Abstract

Background: CVDs are the leading cause of mortality worldwide and they have been a burden to healthcare systems in terms of late diagnosis and lack of long-term monitoring interventions. New technologies in wearable technologies such as smartwatches, ECG patches, cuffless blood pressure monitoring, and heart-failure remote-sensing platforms have also brought new possibilities of continuous and real-time cardiovascular monitoring. Improved with the help of artificial intelligence (AI) and machine-learning-based algorithms, the devices will provide a more accurate interpretation of physiological patterns and can enhance the field of early detection, risk stratification, and clinical management. This system review is an inquiry into the emerging evidence of wearable and remote monitoring in the prevention and management of major cardiovascular conditions.

Objectives: This review aims to assess the quality of: diagnosis, clinical utility, and methodology of modern wearable devices and remote monitoring technologies to determine their use in atrial fibrillation, hypertension, heart failure, and other cardiovascular diseases.

Methods: The systematized search was performed according to the principles of PRISMA 2020 in relation to eight large databases between January 2010 and February 2025. The studies had to meet the following criteria: they had to evaluate wearable or remote monitoring technologies and provide cardiovascular-related diagnostic or clinical outcomes. Data that were extracted comprised sample features, the type of device, performance indicators, AI implementation, and validation methods. The risk of bias was evaluated with the help of ROBINS-I and QUADAS-2. Narrative and quantitative syntheses were conducted and pooled accuracy estimates, forest plots, as well as, correlation analyses to interpret device performance and methodological patterns were used.

Results: There were 58,740 participants that were included in 42 studies. The analysis has indicated that wearable devices possess great diagnostic potential, especially the devices that detect atrial fibrillation by the use of PPG- and ECG-based technologies, which had high sensitivity and specificity. Cuffless blood pressure devices demonstrated average accuracy, whereas heart-failure remote devices were always able to decrease hospitalization or give an early warning of decompensation. Signal processing with AI added value helped in enhancing the quality of diagnostic accuracy in several types of devices. There were also methodological weaknesses, though, since a smaller portion of the studies were external validation, and the problem of calibration of the devices was rather common. Correlation tests showed that the greater the sample size and the number of multi-sensor devices a higher the diagnostic accuracy and external validity.

Conclusion: The use of wearable devices and remote monitoring technologies has a lot of potential to revolutionize the process of cardiovascular disease detection and continuous management. Smartwatches, ECG patches and heart-failure monitoring systems have already shown clinically meaningful consequences, and the use of AI is still continuing to expand the level of accuracy or predictive ability of the devices. However, discrepancies in validation procedures, calibration difficulties of blood pressure in equipments, and study-to-study heterogeneity means that more standardization and stringent clinical testing is required, before a wide clinical integration is attained. To achieve the full potential of wearable cardiovascular technologies in preventative and personalized medicine, it will be crucial to persist in research in multi-sensor systems, transparent AI models, and limited clinical trials on a large scale.