Cuffless Blood Pressure Estimation Algorithms for Continuous Health-Care Monitoring
Abstract
GOAL: Continuous blood pressure (BP) monitoring can provide invaluable information about individuals' health conditions. However, BP is conventionally measured using inconvenient cuff-based instruments, which prevents continuous BP monitoring. This paper presents an efficient algorithm, based on the pulse arrival time (PAT), for the continuous and cuffless estimation of the systolic BP, diastolic blood pressure (DBP), and mean arterial pressure (MAP) values. METHODS: The proposed framework estimates the BP values through processing vital signals and extracting two types of features, which are based on either physiological parameters or whole-based representation of vital signals. Finally, the regression algorithms are employed for the BP estimation. Although the proposed algorithm works reliably without any need for calibration, an optional calibration procedure is also suggested, which can improve the system's accuracy even further. RESULTS: The proposed method is evaluated on about a thousand subjects using the Association for the Advancement of Medical Instrumentation (AAMI) and the British Hypertension Society (BHS) standards. The method complies with the AAMI standard in the estimation of DBP and MAP values. Regarding the BHS protocol, the results achieve grade A for the estimation of DBP and grade B for the estimation of MAP. CONCLUSION: We conclude that by using the PAT in combination with informative features from the vital signals, the BP can be accurately and reliably estimated in a noninvasive fashion. SIGNIFICANCE: The results indicate that the proposed algorithm for the cuffless estimation of the BP can potentially enable mobile health-care gadgets to monitor the BP continuously.
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In individuals with very large arm size, defined as arm circumference greater than 42 cm, the shape of the cuff is important because the large arm shape is troncoconical.
“In individuals with very large arm size (arm circumference >42 cm) the shape of the cuff is also important as the large arm shape is troncoconical [101,102].”
A rectangular or cylindrical shape cuff is unsuitable for very large arms because it cannot evenly compress the upper arm, and a troncoconical cuff shape seems more appropriate.
“Thus, a rectangular (cylindrical) shape cuff is unsuitable as it cannot evenly compress the upper arm and a troncoconical cuff shape seems to be more appropriate [101,102].”
There is still uncertainty on how to validate devices in people with a large arm size greater than 42 cm, as there are issues with the cuff size and shape of the reference auscultatory blood pressure measurement.
“However, there is still uncertainty on how to validate devices in people with a large arm size (i.e. >42 cm), as there are issues with the cuff size and shape of the reference (auscultatory) BP measurement as well [102].”
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- Authors
- Kachuee, M., Kiani, M. M., Mohammadzade, H., & Shabany, M.
- Affiliations
- Sharif University of Technology (IR)
- Venue
- IEEE Transactions on Biomedical Engineering
- Published
- 2017-04
- Volume
- 64
- Issue
- 4
- Pages
- 859-869
- ISSN
- 0018-9294 (ISSN-L)
- 1558-2531
- OpenAlex
- W2431637923
- Cited by
- 621
- References
- 7
- Citations by year
- 2026: 50 · 2025: 70 · 2024: 67 · 2023: 101 · 2022: 95 · 2021: 88 · 2020: 60 · 2019: 47 · 2018: 29 · 2017: 14
- FWCI
- 14.46
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Transactions on Biomedical Engineering (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Cardiovascular Health and Disease Prevention
- Health Sciences › Medicine › Surgery › Hemodynamic Monitoring and Therapy
- Keywords
- cuffless blood pressure measurement, pulse arrival time, continuous blood pressure monitoring, systolic blood pressure, diastolic blood pressure, mean arterial pressure, vital signs, regression estimation, calibration, non-invasive blood pressure measurement, mobile health monitoring
- MeSH terms
- Machine Learning, Algorithms, Blood Pressure, Blood Pressure Determination, Diagnosis, Computer-Assisted, Equipment Design, Humans, Sensitivity and Specificity, Reproducibility of Results, Blood Pressure Monitors, Monitoring, Ambulatory, Equipment Failure Analysis, Pulse Wave Analysis
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