On using maximum a posteriori probability based on a Bayesian model for oscillometric blood pressure estimation

Soojeong Lee; Gwanggil Jeon; Gangseong Lee

doi:10.3390/s131013609

On using maximum a posteriori probability based on a Bayesian model for oscillometric blood pressure estimation

Sensors (Basel). 2013 Oct 10;13(10):13609-23. doi: 10.3390/s131013609.

Authors

Soojeong Lee¹, Gwanggil Jeon, Gangseong Lee

Affiliation

¹ Department of Electronics and Computer Engineering, Hanyang University, 222 Wangsimni-ro, Seongdong-gu, Seoul 133-791, Korea. leesoo86@hanyang.ac.kr.

Abstract

The maximum amplitude algorithm (MAA) is generally utilized in the estimation of the pressure values, and it uses heuristically obtained ratios of systolic and diastolic oscillometric amplitude to the mean arterial pressure (known as systolic and diastolic ratios) in order to estimate the systolic and diastolic pressures. This paper proposes a Bayesian model to estimate the systolic and diastolic ratios. These ratios are an improvement over the single fixed systolic and diastolic ratios used in the algorithms that are available in the literature. The proposed method shows lower mean difference (MD) with standard deviation (SD) compared to the MAA for both SBP and DBP consistently in all the five measurements.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Algorithms*
Bayes Theorem
Blood Pressure / physiology*
Blood Pressure Determination / methods*
Data Interpretation, Statistical*
Diagnosis, Computer-Assisted / methods*
Humans
Oscillometry / methods*
Pattern Recognition, Automated / methods*
Reproducibility of Results
Sensitivity and Specificity
Transducers