TY - JOUR
T1 - An intelligent telecardiology system using a wearable and wireless ecg to detect atrial fibrillation
AU - Lin, Chin Teng
AU - Chang, Kuan Cheng
AU - Lin, Chun Ling
AU - Chiang, Chia Cheng
AU - Lu, Shao Wei
AU - Chang, Shih Sheng
AU - Lin, Bor Shyh
AU - Liang, Hsin Yueh
AU - Chen, Ray Jade
AU - Lee, Yuan Teh
AU - Ko, Li Wei
N1 - Funding Information:
Manuscript received July 6, 2009; revised October 21, 2009 and February 20, 2010. First published April 5, 2010; current version published June 3, 2010. This work was supported in part by the Aiming for the Top University Plan of National Chiao-Tung University, the Ministry of Education, Taiwan, under Contract 98W962, in part by the Ministry of Economic Affairs, Taiwan, under Contract 97-EC-17-A-03-S1–005, and Contract 98-EC-17-A-19-S2-0052, and in part by the National Science Council (NSC), Taiwan, under Contract NSC 97-2220-E-009-052 and Contract 98-2221-E-009-167.
PY - 2010/5
Y1 - 2010/5
N2 - This study presents a novel wireless, ambulatory, real-time, and autoalarm intelligent telecardiology system to improve healthcare for cardiovascular disease, which is one of the most prevalent and costly health problems in the world. This system consists of a lightweight and power-saving wireless ECG device equipped with a built-in automatic warning expert system. This device is connected to a mobile and ubiquitous real-time display platform. The acquired ECG signals are instantaneously transmitted to mobile devices, such as netbooks or mobile phones through Bluetooth, and then, processed by the expert system. An alert signal is sent to the remote database server, which can be accessed by an Internet browser, once an abnormal ECG is detected. The current version of the expert system can identify five types of abnormal cardiac rhythms in real-time, including sinus tachycardia, sinus bradycardia, wide QRS complex, atrial fibrillation (AF), and cardiac asystole, which is very important for both the subjects who are being monitored and the healthcare personnel tracking cardiac-rhythm disorders. The proposed system also activates an emergency medical alarm system when problems occur. Clinical testing reveals that the proposed system is approximately 94% accurate, with high sensitivity, specificity, and positive prediction rates for ten normal subjects and 20 AF patients. We believe that in the future a business-card-like ECG device, accompanied with a mobile phone, can make universal cardiac protection service possible.
AB - This study presents a novel wireless, ambulatory, real-time, and autoalarm intelligent telecardiology system to improve healthcare for cardiovascular disease, which is one of the most prevalent and costly health problems in the world. This system consists of a lightweight and power-saving wireless ECG device equipped with a built-in automatic warning expert system. This device is connected to a mobile and ubiquitous real-time display platform. The acquired ECG signals are instantaneously transmitted to mobile devices, such as netbooks or mobile phones through Bluetooth, and then, processed by the expert system. An alert signal is sent to the remote database server, which can be accessed by an Internet browser, once an abnormal ECG is detected. The current version of the expert system can identify five types of abnormal cardiac rhythms in real-time, including sinus tachycardia, sinus bradycardia, wide QRS complex, atrial fibrillation (AF), and cardiac asystole, which is very important for both the subjects who are being monitored and the healthcare personnel tracking cardiac-rhythm disorders. The proposed system also activates an emergency medical alarm system when problems occur. Clinical testing reveals that the proposed system is approximately 94% accurate, with high sensitivity, specificity, and positive prediction rates for ten normal subjects and 20 AF patients. We believe that in the future a business-card-like ECG device, accompanied with a mobile phone, can make universal cardiac protection service possible.
KW - Atrial fibrillation (AF)
KW - ECG
KW - Expert systems
KW - Mobile
KW - Wireless
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U2 - 10.1109/TITB.2010.2047401
DO - 10.1109/TITB.2010.2047401
M3 - Article
C2 - 20371411
AN - SCOPUS:77953157945
SN - 2168-2194
VL - 14
SP - 726
EP - 733
JO - IEEE Journal of Biomedical and Health Informatics
JF - IEEE Journal of Biomedical and Health Informatics
IS - 3
M1 - 5443463
ER -