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A blood pressure monitoring method for stroke management.

Ma HT - Biomed Res Int (2014)

Bottom Line: Variation and variability of pulse transit time were introduced to construct the compensation algorithm in the model.By comparing the estimated value to the measurement from an oscillometry, the result showed that the mean error of the estimated blood pressure was -0.2 ± 2.4 mmHg and 0.5 ± 3.9 mmHg for systolic and diastolic blood pressure, respectively.In addition, the estimation performance of the proposed model is better than the linear model, especially for the diastolic blood pressure.

View Article: PubMed Central - PubMed

Affiliation: Department of Electronic and Information Engineering, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen 518055, China.

ABSTRACT
Blood pressure is one important risk factor for stroke prognosis. Therefore, continuous monitoring of blood pressure is crucial for preventing and predicting stroke. However, current blood pressure devices are mainly air-cuff based, which only can provide measurements intermittently. This study proposed a new blood pressure estimation method based on the pulse transit time to realize continuous monitoring. The proposed method integrated a linear model with a compensation algorithm. A calibration method was further developed to guarantee that the model was personalized for individuals. Variation and variability of pulse transit time were introduced to construct the compensation algorithm in the model. The proposed method was validated by the data collected from 30 healthy subjects, aged from 23 to 25 years old. By comparing the estimated value to the measurement from an oscillometry, the result showed that the mean error of the estimated blood pressure was -0.2 ± 2.4 mmHg and 0.5 ± 3.9 mmHg for systolic and diastolic blood pressure, respectively. In addition, the estimation performance of the proposed model is better than the linear model, especially for the diastolic blood pressure. The results indicate that the proposed method has promising potential to realize continuous blood pressure measurement.

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Bland Altman plot of estimation error of diastolic blood pressure.
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fig4: Bland Altman plot of estimation error of diastolic blood pressure.

Mentions: The mean estimation error of the proposed model was −0.2 ± 2.4 mmHg and −0.5 ± 3.9 mmHg, while it was 0.1 ± 2.5 mmHg and 1.3 ± 7.4 mmHg from the linear model, for the SBP and DBP, respectively. The result again showed that the proposed method had a better performance on the DBP estimation. This is evident in the Bland Altman plot shown in Figures 3 and 4.


A blood pressure monitoring method for stroke management.

Ma HT - Biomed Res Int (2014)

Bland Altman plot of estimation error of diastolic blood pressure.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4150505&req=5

fig4: Bland Altman plot of estimation error of diastolic blood pressure.
Mentions: The mean estimation error of the proposed model was −0.2 ± 2.4 mmHg and −0.5 ± 3.9 mmHg, while it was 0.1 ± 2.5 mmHg and 1.3 ± 7.4 mmHg from the linear model, for the SBP and DBP, respectively. The result again showed that the proposed method had a better performance on the DBP estimation. This is evident in the Bland Altman plot shown in Figures 3 and 4.

Bottom Line: Variation and variability of pulse transit time were introduced to construct the compensation algorithm in the model.By comparing the estimated value to the measurement from an oscillometry, the result showed that the mean error of the estimated blood pressure was -0.2 ± 2.4 mmHg and 0.5 ± 3.9 mmHg for systolic and diastolic blood pressure, respectively.In addition, the estimation performance of the proposed model is better than the linear model, especially for the diastolic blood pressure.

View Article: PubMed Central - PubMed

Affiliation: Department of Electronic and Information Engineering, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen 518055, China.

ABSTRACT
Blood pressure is one important risk factor for stroke prognosis. Therefore, continuous monitoring of blood pressure is crucial for preventing and predicting stroke. However, current blood pressure devices are mainly air-cuff based, which only can provide measurements intermittently. This study proposed a new blood pressure estimation method based on the pulse transit time to realize continuous monitoring. The proposed method integrated a linear model with a compensation algorithm. A calibration method was further developed to guarantee that the model was personalized for individuals. Variation and variability of pulse transit time were introduced to construct the compensation algorithm in the model. The proposed method was validated by the data collected from 30 healthy subjects, aged from 23 to 25 years old. By comparing the estimated value to the measurement from an oscillometry, the result showed that the mean error of the estimated blood pressure was -0.2 ± 2.4 mmHg and 0.5 ± 3.9 mmHg for systolic and diastolic blood pressure, respectively. In addition, the estimation performance of the proposed model is better than the linear model, especially for the diastolic blood pressure. The results indicate that the proposed method has promising potential to realize continuous blood pressure measurement.

Show MeSH
Related in: MedlinePlus