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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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Correlation between the estimated blood pressure and the standard blood pressure for both linear model and the proposed model.
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fig2: Correlation between the estimated blood pressure and the standard blood pressure for both linear model and the proposed model.

Mentions: The blood pressure measured by the oscillometry was regarded as the standard value. Correlation between estimated blood pressure values from the two estimation models and the standard value was first analyzed, as shown in Figure 2. It appears that both estimation models could provide an acceptable estimation on SBP as the correlation coefficient R2 around 0.96 (P < 0.001) for the estimation results derived from two models. However, for the DBP, the proposed model showed a better performance with R2 of 0.71 (P < 0.001), while it is 0.27 (P < 0.01) for the linear model estimation results. The correlation analysis indicates that the proposed method provides better estimation performance on blood pressure especially for the DBP.


A blood pressure monitoring method for stroke management.

Ma HT - Biomed Res Int (2014)

Correlation between the estimated blood pressure and the standard blood pressure for both linear model and the proposed model.
© Copyright Policy
Related In: Results  -  Collection

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

fig2: Correlation between the estimated blood pressure and the standard blood pressure for both linear model and the proposed model.
Mentions: The blood pressure measured by the oscillometry was regarded as the standard value. Correlation between estimated blood pressure values from the two estimation models and the standard value was first analyzed, as shown in Figure 2. It appears that both estimation models could provide an acceptable estimation on SBP as the correlation coefficient R2 around 0.96 (P < 0.001) for the estimation results derived from two models. However, for the DBP, the proposed model showed a better performance with R2 of 0.71 (P < 0.001), while it is 0.27 (P < 0.01) for the linear model estimation results. The correlation analysis indicates that the proposed method provides better estimation performance on blood pressure especially for the DBP.

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