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June 12, 2017IEEE Journal of Biomedical and Health Informatics91 citations

Cuff-Less Blood Pressure Estimation Using Pulse Waveform Analysis and Pulse Arrival Time

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YYYoung-Zoon YoonJKJae Min KangYKYongjoo Kwon

Key Result

Pulse wave analysis combined with pulse arrival time-driven information demonstrated the potential to continuously estimate blood pressure values over a 1-day period.

Study Design

Type

Observational (n=23)

Structured PICO

Does pulse wave analysis combined with pulse arrival time accurately estimate continuous blood pressure in subjects from the MIMIC database?

P
Population
23 subjects from the MIMIC physiological database evaluated over a 1-day period for continuous blood pressure estimation.
E
Exposure
Pulse wave analysis (PWA) based on multiparameters model using pulse arrival time (PAT) driven BP information to determine individual scale factors
O
Outcome
Accuracy of blood pressure estimation (error standard deviations for SBP and DBP)surrogate

Pulse wave analysis combined with pulse arrival time shows potential for continuous, cuff-less blood pressure estimation for home users.

Limitations

  • Insufficient data acquirement for home users
  • Required more than four times the 1 min data extracted over the 12 h calibration period to predict BP for 1 day

Abstract

Using the massive MIMIC physiological database, we tried to validate pulse wave analysis (PWA) based on multiparameters model whether it can continuously estimate blood pressure (BP) values on single site of one hand. In addition, to consider the limitation of insufficient data acquirement for home user, we used pulse arrival time (PAT) driven BP information to determine the individual scale factors of the PWA-BP estimation model. Experimental results indicate that the accuracy of the average regression model has error standard deviations of mmHg (PAT), mmHg (PWA) for SBP and mmHg (PAT), mmHg (PWA) for DBP on 23 subjects over a 1 day period. We defined a local-model which is extracted regression model from sparsely selected small dataset, contrast to full dataset for 24h (average-model). The limit of BP estimation accuracy from the local-model of PWA is lower than that of PAT-BP average-model. Whereas the error of the BP estimation local-model was reduced using more data for scaling, it required more than four times the 1 min data extracted over the 12 h calibration period to predict BP for 1 day. This study shows that PWA has possibility to estimate BP value and PAT-driven BP information could be used to determine the individual scale factors of the PWA-BP estimation model for home users.

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Cite This Study

Yoon et al. (2017) reported an observational. Pulse wave analysis (PWA) and pulse arrival time (PAT) was evaluated on Accuracy of blood pressure estimation (error standard deviations for SBP and DBP). Pulse wave analysis combined with pulse arrival time-driven information demonstrated the potential to continuously estimate blood pressure values over a 1-day period.

synapsesocial.com/papers/6a1f1ff0b0009ed3b15530a5https://doi.org/10.1109/jbhi.2017.2714674
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