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http://dx.doi.org/10.9718/JBER.2014.35.4.87

Automatic Noise Removal and Peak Detection Algorithm for ECG Measured from Capacitively Coupled Electrodes Included within a Cloth Mattress Pad  

Lee, Won Kyu (Interdisciplinary Program for Bioengineering, Graduate School, Seoul National University)
Lee, Hong Ji (Interdisciplinary Program for Bioengineering, Graduate School, Seoul National University)
Yoon, Hee Nam (Interdisciplinary Program for Bioengineering, Graduate School, Seoul National University)
Chung, Gih Sung (Interdisciplinary Program for Bioengineering, Graduate School, Seoul National University)
Park, Kwang Suk (Interdisciplinary Program for Bioengineering, Graduate School, Seoul National University)
Publication Information
Journal of Biomedical Engineering Research / v.35, no.4, 2014 , pp. 87-94 More about this Journal
Abstract
Recent technological advances have increased interest in personal health monitoring. Electrocardiogram(ECG) monitoring is a basic healthcare activity and can provide decisive information regarding cardiovascular system status. In this study, we developed a capacitive ECG measurement system that can be included within a cloth mattress pad. The device permits ECG data to be obtained during sleep by using capacitive electrodes. However, it is difficult to detect R-wave peaks automatically because signals obtained from the system can include a high level of noise from various sources. Because R-peak detection is important in ECG applications, we developed an algorithm that can reduce noise and improve detection accuracy under noisy conditions. Algorithm reliability was evaluated by determining its sensitivity(Se), positive predictivity(+P), and error rate(Er) by using data from the MIT-BIH Polysomnographic Database and from our capacitive ECG system. The results showed that Se = 99.75%, +P = 99.77%, and Er = 0.47% for MIT-BIH Polysomnographic Database while Se = 96.47%, +P = 99.32%, and Er = 4.34% for our capacitive ECG system. Based on those results, we conclude that our R-peak detection method is capable of providing useful ECG information, even under noisy signal conditions.
Keywords
Capacitively Measured ECG; R-peak Detection; Ubiquitous Healthcare; Non-intrusive ECG Monitoring System; MIT-BIH Polysomnographic Database;
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