Digital Blood Pressure Estimation with the Differential Value of theArterial Pulse Waveform


KIPS Transactions on Computer and Communication Systems, Vol. 5, No. 6, pp. 135-142, Jun. 2016
10.3745/KTCCS.2016.5.6.135,   PDF Download:
Keywords: Digital Arterial Pulse Waveform, Blood Pressure Measurement, Differential Value, BP Relation Equation, Non-Kortokoff Method
Abstract

We proposed the new method to estimate the blood pressure with the differential value of the digital arterial pulse waveform and BP relation equation. To get the digital arterial pulse waveform, we use the arterial pulse waveform measurement system that has digital air-pressure sensor device and smart phone. The acquired digital arterial pulse waveforms are classified as hypertension group, normal group, and hypotension group, and we can derive the average differential value between the highest point and lowest point of a single waveform of individuals along with the group. In this study, we found the functional correlation between the blood pressure and differential value as a form of BP relation equation through the regression process on the average of differential value and blood pressure value from a tonometer. The Experimental results show the BP relation equation can give easy blood pressure estimation method with a high accuracy. Although this estimation method has over 66 % error rate and does not give the high level of the accuracy for the diastolic compares to the commercial tonometer, the estimation results for the systolic show the high accuracy that has less than 10 % error rate.


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Cite this article
[IEEE Style]
K. Boyeon and C. Yunseok, "Digital Blood Pressure Estimation with the Differential Value of theArterial Pulse Waveform," KIPS Transactions on Computer and Communication Systems, vol. 5, no. 6, pp. 135-142, 2016. DOI: 10.3745/KTCCS.2016.5.6.135.

[ACM Style]
Kim Boyeon and Chang Yunseok. 2016. Digital Blood Pressure Estimation with the Differential Value of theArterial Pulse Waveform. KIPS Transactions on Computer and Communication Systems, 5, 6, (2016), 135-142. DOI: 10.3745/KTCCS.2016.5.6.135.