 
|
|
|
ヨシダ ミノル
Yoshida Minoru 吉田 稔 所属 神奈川大学 情報学部 システム数理学科 神奈川大学大学院 工学研究科 工学専攻（情報システム創成領域） 神奈川大学大学院 工学研究科 工学専攻（経営工学領域） 職種 教授 |
|
| 言語種別 | 英語 |
| 発行・発表の年月 | 2021/07 |
| 形態種別 | 学術雑誌 |
| 査読 | 査読あり |
| 標題 | An analysis of electrocardiograms through the wavelet
transform with pseudo differential operator like operators |
| 執筆形態 | 共著 |
| 掲載誌名 | Proceedings of 40th JSST Annual |
| 掲載区分 | 国内 |
| 出版社・発行元 | International Conference on Simulation Technology (JSST 2021) |
| 巻・号・頁 | 40(To aapare) |
| 著者・共著者 | Masudur Rahman |
| 概要 | A qualitative improvement of existing detection procedures for arrhythmias diagnosis system is proposed.Just by a standard application of the wavelet transform to electrocardiography (ECG),it is not easy to detect the difference, in the frequency levels, between some of the shockable and non-shockable arrhythmia in the class of abnormal signals. Here, we apply the {\it{wavelet transform of the image of the pseudo-differential operator like operators}} acted on the ECG signals and take, as statistics, the scalo-graphic representation of it and its histogram. As a result, significant difference between two abnormal classes of the signals, shockable
(known as VT and VF) and non-shockable arrhythmia (known as PEA), are manifested and presented graphically and numerically. |
Copyright © Kanagawa University. All Rights Reserved.