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Wŏnju, South Korea

Song M.-H.,Yonsei University | Song M.-H.,MEZOO Co. and 808 | Cho S.-P.,MEZOO Co. and 808 | Kim W.,Yonsei University | Lee K.-J.,Yonsei University
Computers in Biology and Medicine | Year: 2015

This study presents a new real-time heartbeat detection algorithm using the geometric angle between two consecutive samples of single-lead electrocardiogram (ECG) signals. The angle was adopted as a new index representing the slope of ECG signal. The method consists of three steps: elimination of high-frequency noise, calculation of the angle of ECG signal, and detection of R-waves using a simple adaptive thresholding technique. The MIT-BIH arrhythmia database, QT database, European ST-T database, T-wave alternans database and synthesized ECG signals were used to evaluate the performance of the proposed algorithm and compare with the results of other methods suggested in literature. The proposed method shows a high detection rate-99.95% of the sensitivity, 99.95% of the positive predictivity, and 0.10% of the fail detection rate on the four databases. The result shows that the proposed method can yield better or comparable performance than other literature despite the relatively simple process. The proposed algorithm needs only a single-lead ECG, and involves a simple and quick calculation. Moreover, it does not require post-processing to enhance the detection. Thus, it can be effectively applied to various real-time healthcare and medical devices. © 2015 Elsevier Ltd. Source

Shin J.,Yonsei University | Shin J.,MEZOO Co. and 808 | Park H.,MEZOO Co. and 808 | Cho S.,MEZOO Co. and 808 | And 2 more authors.
Computers in Biology and Medicine | Year: 2014

Point-of-care testing glucose meters are widely used, important tools for determining the blood glucose levels of people with diabetes, patients in intensive care units, pregnant women, and newborn infants. However, a number of studies have concluded that a change in hematocrit (Hct) levels can seriously affect the accuracy of glucose measurements. The aim of this study was to develop an algorithm for glucose calculation with improved accuracy using the Hct compensation method that minimizes the effects of Hct on glucose measurements. The glucose concentrations in this study were calculated with an adaptive calibration curve using linear fitting prediction and a support vector machine, which minimized the bias in the glucose concentrations caused by the Hct interference. This was followed by an evaluation of performance according to the international organization for standardization (ISO) 15197:2013 based on bias with respect to the reference method, the coefficient of variation, and the valid blood samples/total blood samples within the ±20% and 15% error grids. Chronoamperometry was performed to verify the effect of Hct variation and to compare the proposed method. As a result, the average coefficients of variation for chronoamperometry and the Hct compensation method were 2.43% and 3.71%, respectively, while the average biases (%) for these methods were 12.08% and 5.69%, respectively. The results of chronoamperometry demonstrated that a decrease in Hct levels increases glucose concentrations, whereas an increase in Hct levels reduces glucose concentrations. Finally, the proposed method has improved the accuracy of glucose measurements compared to existing chronoamperometry methods. © 2014 Elsevier Ltd. Source

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