title: An intelligent telecardiology system using a wearable and wireless ECG to detect atrial fibrillation.
abstract: 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.
authors.affiliation: Brain Research Center and the Department of Electrical Engineering, National Chiao-Tung University, Hsinchu 30010, Taiwan. lwko@mail.nctu.edu.tw
authors.forename: Chin-Teng
authors.initials: CT
authors.lastname: Lin
authors.forename: Kuan-Cheng
authors.initials: KC
authors.lastname: Chang
authors.forename: Chun-Ling
authors.initials: CL
authors.lastname: Lin
authors.forename: Chia-Cheng
authors.initials: CC
authors.lastname: Chiang
authors.forename: Shao-Wei
authors.initials: SW
authors.lastname: Lu
authors.forename: Shih-Sheng
authors.initials: SS
authors.lastname: Chang
authors.forename: Bor-Shyh
authors.initials: BS
authors.lastname: Lin
authors.forename: Hsin-Yueh
authors.initials: HY
authors.lastname: Liang
authors.forename: Ray-Jade
authors.initials: RJ
authors.lastname: Chen
authors.forename: Yuan-Teh
authors.initials: YT
authors.lastname: Lee
authors.forename: Li-Wei
authors.initials: LW
authors.lastname: Ko
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D001281:Atrial Fibrillation / Q000175:diagnosis*; D003020:Clothing; D003195:Computer Communication Networks; D004562:Electrocardiography / Q000295:instrumentation* / Q000379:methods; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D012815:Signal Processing, Computer-Assisted; D017216:Telemedicine / Q000295:instrumentation* / Q000379:methods; D013686:Telemetry / Q000295:instrumentation*