지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록· 키워드
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Recent technological advances have increased interest in personal health monitoring. Electrocardiogram(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 PolysomnographicDatabase 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 providinguseful ECG information, even under noisy signal conditions
목차
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참고문헌 (12)
참고문헌 신청
A. R. Houghton. / 2008 / Making sense of the ECG: a hands-on guide. 3rd ed / Hodder Arnold : 1 ~ 7
G. M. Friesen. / 1990 / A Comparison of the Noise Sensitivity of Nine QRS Detection Algorithms / IEEE Trans. Biomed. Eng 37 (1) : 85 ~ 98
H. Zhu. / 2013 / An R-peak detection method based on peaks of Shannon energy envelope / Biomed. Signal Pro-cess. Control 8 (5) : 466 ~ 474
Kwang-Suk Park / 2011 / Monitoring Physiological Signals Using Nonintrusive Sensors Installed in Daily Life Equipment / Biomedical Engineering Letters (BMEL) 1 (1) : 11 ~ 20
M. Adnane. / 2009 / Development of QRS detection algorithm designed for wearable cardiorespiratory system / Comput. Meth. Programs Biomed 93 (1) : 20 ~ 31
G. M. Friesen. / 1990 / A Comparison of the Noise Sensitivity of Nine QRS Detection Algorithms / IEEE Trans. Biomed. Eng 37 (1) : 85 ~ 98
H. Zhu. / 2013 / An R-peak detection method based on peaks of Shannon energy envelope / Biomed. Signal Pro-cess. Control 8 (5) : 466 ~ 474
Kwang-Suk Park / 2011 / Monitoring Physiological Signals Using Nonintrusive Sensors Installed in Daily Life Equipment / Biomedical Engineering Letters (BMEL) 1 (1) : 11 ~ 20
M. Adnane. / 2009 / Development of QRS detection algorithm designed for wearable cardiorespiratory system / Comput. Meth. Programs Biomed 93 (1) : 20 ~ 31
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