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

Recent technological advances have increased interest in personal health monitoring. Electrocardio-gram(ECG) monitoring is a basic healthcare activity and can provide decisive information regarding cardiovascularsystem status. In this study, we developed a capacitive ECG measurement system that can be included within a clothmattress 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 levelof noise from various sources. Because R-peak detection is important in ECG applications, we developed an algorithmthat can reduce noise and improve detection accuracy under noisy conditions. Algorithm reliability was evaluated bydetermining its sensitivity(Se), positive predictivity(+P), and error rate(Er) by using data from the MIT-BIH Poly-somnographic 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% forour capacitive ECG system. Based on those results, we conclude that our R-peak detection method is capable of pro-viding useful ECG information, even under noisy signal conditions.Key words: Capacitively Measured ECG, R-peak Detection, Ubiquitous Healthcare, Non-intrusive ECG MonitoringSystem, MIT-BIH Polysomnographic Database