摘要
Cardiac arrhythmias are time-varying, non-period, irregular, or complex fluctuations in time-domain waveforms, revealing multiple morphologies, including supraventricular, junctional, and ventricular arrhythmias, and conduction abnormalities. Given that visual examinations are time-consuming, this study proposes a screening method for identifying the classes of multiple cardiac arrhythmias using the discrete fractional-order integration (DFOI) and the perceptual color representation-based intelligent classifier. The DFOI operation with the specific fractional order is employed to extract the QRS features with the finite computations and finite power series in a specific timing duration. DFOI can deal with the non-period and irregular time-varying signals. The proposed intelligent classifier consists of Bayesian network and color relation analysis (CRA). This classifier is employed to identify the ectopic classes with perceptual color representation. Using the arrhythmia database of Massachusetts Institute of Technology-Beth Israel Hospital database, the proposed intelligent classifier demonstrated high efficiency in recognizing electrocardiography signals.
| 原文 | English |
|---|---|
| 主出版物標題 | Proceedings - 2018 International Symposium on Computer, Consumer and Control, IS3C 2018 |
| 發行者 | Institute of Electrical and Electronics Engineers Inc. |
| 頁面 | 201-204 |
| 頁數 | 4 |
| ISBN（電子） | 9781538670361 |
| DOIs | |
| 出版狀態 | Published - 2019 二月 19 |
| 事件 | 4th International Symposium on Computer, Consumer and Control, IS3C 2018 - Taichung, Taiwan 持續時間: 2018 十二月 6 → 2018 十二月 8 |
出版系列
| 名字 | Proceedings - 2018 International Symposium on Computer, Consumer and Control, IS3C 2018 |
|---|
Conference
| Conference | 4th International Symposium on Computer, Consumer and Control, IS3C 2018 |
|---|---|
| 國家 | Taiwan |
| 城市 | Taichung |
| 期間 | 18-12-06 → 18-12-08 |
指紋
All Science Journal Classification (ASJC) codes
- Computer Networks and Communications
- Control and Systems Engineering
- Energy Engineering and Power Technology
- Computer Science Applications
- Control and Optimization
- Signal Processing
引用此文
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Automated screening of multiple cardiac arrhythmias using perceptual color representation-based intelligent classifier. / Lin, Chia Hung; Kan, Chung-Dann; Chen, Pi Yun; Lai, Hsiang Yueh; Chen, Wei Ling; Kuo, Ying Che.
Proceedings - 2018 International Symposium on Computer, Consumer and Control, IS3C 2018. Institute of Electrical and Electronics Engineers Inc., 2019. p. 201-204 8644756 (Proceedings - 2018 International Symposium on Computer, Consumer and Control, IS3C 2018).研究成果: Conference contribution
TY - GEN
T1 - Automated screening of multiple cardiac arrhythmias using perceptual color representation-based intelligent classifier
AU - Lin, Chia Hung
AU - Kan, Chung-Dann
AU - Chen, Pi Yun
AU - Lai, Hsiang Yueh
AU - Chen, Wei Ling
AU - Kuo, Ying Che
PY - 2019/2/19
Y1 - 2019/2/19
N2 - Cardiac arrhythmias are time-varying, non-period, irregular, or complex fluctuations in time-domain waveforms, revealing multiple morphologies, including supraventricular, junctional, and ventricular arrhythmias, and conduction abnormalities. Given that visual examinations are time-consuming, this study proposes a screening method for identifying the classes of multiple cardiac arrhythmias using the discrete fractional-order integration (DFOI) and the perceptual color representation-based intelligent classifier. The DFOI operation with the specific fractional order is employed to extract the QRS features with the finite computations and finite power series in a specific timing duration. DFOI can deal with the non-period and irregular time-varying signals. The proposed intelligent classifier consists of Bayesian network and color relation analysis (CRA). This classifier is employed to identify the ectopic classes with perceptual color representation. Using the arrhythmia database of Massachusetts Institute of Technology-Beth Israel Hospital database, the proposed intelligent classifier demonstrated high efficiency in recognizing electrocardiography signals.
AB - Cardiac arrhythmias are time-varying, non-period, irregular, or complex fluctuations in time-domain waveforms, revealing multiple morphologies, including supraventricular, junctional, and ventricular arrhythmias, and conduction abnormalities. Given that visual examinations are time-consuming, this study proposes a screening method for identifying the classes of multiple cardiac arrhythmias using the discrete fractional-order integration (DFOI) and the perceptual color representation-based intelligent classifier. The DFOI operation with the specific fractional order is employed to extract the QRS features with the finite computations and finite power series in a specific timing duration. DFOI can deal with the non-period and irregular time-varying signals. The proposed intelligent classifier consists of Bayesian network and color relation analysis (CRA). This classifier is employed to identify the ectopic classes with perceptual color representation. Using the arrhythmia database of Massachusetts Institute of Technology-Beth Israel Hospital database, the proposed intelligent classifier demonstrated high efficiency in recognizing electrocardiography signals.
UR - http://www.scopus.com/inward/record.url?scp=85063197870&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85063197870&partnerID=8YFLogxK
U2 - 10.1109/IS3C.2018.00058
DO - 10.1109/IS3C.2018.00058
M3 - Conference contribution
AN - SCOPUS:85063197870
T3 - Proceedings - 2018 International Symposium on Computer, Consumer and Control, IS3C 2018
SP - 201
EP - 204
BT - Proceedings - 2018 International Symposium on Computer, Consumer and Control, IS3C 2018
PB - Institute of Electrical and Electronics Engineers Inc.
ER -