Background: Atrial fibrillation (AF), which contributes to an increased risk of stroke, frequently remains undetected, suggesting an unmet need for easier and more reliable AF screening. The reports on screening AF using an Omron blood pressure (BP) monitor with an irregular heartbeat (IHB) detector show inconsistent results, so the aim of this study was to develop a novel algorithm to accurately diagnose AF with 3 BP measurements using an Omron automated BP monitor with IHB detector. Methods and Results: In total, 303 general cardiac patients were included. Real-time single-lead ECG revealed AF in 44 patients. BP measurement was performed 3 times per patient using the Omron BP monitor HEM-907, and the number of IHBs detected was recorded. Based on these data, we developed the following algorithm: ≥1 IHB is detected during at least 2 of 3 BP measurements and the maximum number of IHBs detected is ≥2. Using this algorithm, we achieved a sensitivity of 95.5% and specificity of 96.5%, for diagnosing AF. Conclusions: The novel algorithm with 3 BP measurements using the Omron automated BP monitor with IHB detector showed high sensitivity and specificity for diagnosing AF in general cardiac patients.
:In the field of image processing, it is well known that the gray level transform by Histogram Equalization (HE) for gray scale image effectively enhances the intensity contrast, in general. For the case of color image, the HE processing can be regarded as an elastic transform on the lightness axis in the RGB attribute space of input color image. In this paper, from the expansion of this idea, we propose some elastic transforms based on the HE on Principal Component axis, as arrangement processing for color image that can bring about impressive feeling effects. Moreover, we show the questionnaire survey on the results of the arrangement processing, and discuss the effectiveness in feeling impression.
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