원문정보
보안공학연구지원센터(IJBSBT)
International Journal of Bio-Science and Bio-Technology
Vol.7 No.3
2015.06
pp.33-42
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
Ventricular fibrillation (VF) and ventricular tachycardia (VT) are life-threatening signals. Automated external defibrillators can decrease the fatality rate if the VF/VT detection is stable and quick. This thesis proposes improved VF/VT detection. For our experiments, we use the complete Creighton University Ventricular Tachyarrhythmia Database. Samples are analyzed under the same conditions in intervals of 7 s. Based on this data, we propose a time-delay transform. Then, we extract six shockable features, three known and three new, which are used to construct our Neural Network with Weight Fuzzy Membership Functions model (NEWFM). The result is better than the phase space reconstruction algorithm.
목차
Abstract
1. Introduction
2. The New VT/VF Detection
2.1. Haar Wavelet Transform
2.2. Time-delay Transform
2.3 Feature Extraction
2.4 Feature Selection
3. Experiment and Result
4. Conclusion
References
1. Introduction
2. The New VT/VF Detection
2.1. Haar Wavelet Transform
2.2. Time-delay Transform
2.3 Feature Extraction
2.4 Feature Selection
3. Experiment and Result
4. Conclusion
References
저자정보
참고문헌
자료제공 : 네이버학술정보