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This work examines non-invasive cuffless blood pressure monitoring technologies and their applications in healthcare.

February 16, 2026Open Access

Beyond the Cuff: State-of-the-Art on Cuffless Blood Pressure Monitoring

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Authors

YSYaheya Shafti SHSteven Hughes WTWilliam Taylor

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Overview

This review highlights continuous monitoring of blood pressure using machine learning and sensor fusion, suggesting improvements in hypertension management.

Key Points

This work examines non-invasive cuffless blood pressure monitoring technologies and their applications in healthcare.
Survey of cuffless blood pressure monitoring technologies
Evaluation of radar, optical, acoustic, and capacitive sensors
Analysis of machine learning and sensor fusion approaches
Introduction of a unifying taxonomy for sensing modalities and measurement principles
Challenges in achieving clinically acceptable accuracy identified
Continued emphasis on overcoming motion artifacts and the need for international validation standards
Potential applications in remote health monitoring and ambient clinical intelligence highlighted

Cite This Study

Shafti et al. (2026) studied this question.

synapsesocial.com/papers/69926552eb1f82dc367a12be https://doi.org/10.3390/s26041243

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February 16, 2026Open Access

Beyond the Cuff: State-of-the-Art on Cuffless Blood Pressure Monitoring

View Full Paper

Ask AI

Bookmark

Authors

YSYaheya Shafti SHSteven Hughes WTWilliam Taylor

Discussion

Member takes

Overview

This review highlights continuous monitoring of blood pressure using machine learning and sensor fusion, suggesting improvements in hypertension management.

Key Points

This work examines non-invasive cuffless blood pressure monitoring technologies and their applications in healthcare.
Survey of cuffless blood pressure monitoring technologies
Evaluation of radar, optical, acoustic, and capacitive sensors
Analysis of machine learning and sensor fusion approaches
Introduction of a unifying taxonomy for sensing modalities and measurement principles
Challenges in achieving clinically acceptable accuracy identified
Continued emphasis on overcoming motion artifacts and the need for international validation standards
Potential applications in remote health monitoring and ambient clinical intelligence highlighted

Cite This Study

Shafti et al. (2026) studied this question.

synapsesocial.com/papers/69926552eb1f82dc367a12be https://doi.org/10.3390/s26041243

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