Blood pressure (BP) monitoring is crucial for identifying high BP (hypertension) and is an important aspect of patient care. However, traditional cuff-based methods for BP monitoring are unsuitable for continuous monitoring and can cause discomfort to patients. This survey critically examines the emerging field of cuffless BP monitoring, highlighting advances beyond traditional cuff-based methods. Technologies such as radar, optical, acoustic, and capacitive sensors offer the potential for continuous, non-invasive BP estimation, enabling applications in remote health monitoring and ambient clinical intelligence. We introduce a unifying taxonomy covering sensing modalities, physiological measurement principles, signal processing techniques, and translational challenges. Emphasis is placed on methods that eliminate subject-specific calibration, overcome motion artifacts, and satisfy international validation standards. The review also analyses Machine Learning (ML) and sensor fusion approaches that enhance predictive accuracy. Despite encouraging results, challenges remain in achieving clinically acceptable accuracy across diverse populations and real-world conditions. This work delineates the current landscape, benchmarks performance against gold standards, and identifies key future directions for scalable, explainable, and regulatory-compliant BP monitoring systems.
Shafti et al. (Sat,) studied this question.