tailieunhanh - Báo cáo hóa học: "Research Article Modeling of Electrocardiogram Signals Using Predefined Signature and Envelope Vector Sets"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Modeling of Electrocardiogram Signals Using Predefined Signature and Envelope Vector Sets | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2007 Article ID 12071 12 pages doi 2007 12071 Research Article Modeling of Electrocardiogram Signals Using Predefined Signature and Envelope Vector Sets Hakan Gurkan 1 Umit Guz 1 2 and B. Siddik Yarman3 4 1 Department of Electronics Engineering Engineering Faculty I IK University Kumbaba Mevkii 34980 Sile Istanbul Turkey 2 Speech Technology and Research STAR Laboratory Information and Computing Sciences Division SRI International 333 Ravenswood Avenue Menlo Park CA 94025 USA 3 Department of Electrical-Electronics Engineering College of Engineering Istanbul University 34230 Avcilar Istanbul Turkey 4 Department of Physical Electronics Graduate School of Science and Technology Tokyo Institute of Technology Ookayama Campus 2-12-1 Ookayama Meguro-Ku 152-8552 Tokyo Japan Received 28 April 2006 Accepted 24 November 2006 Recommended by Maurice Cohen A novel method is proposed to model ECG signals by means of predefined signature and envelope vector sets PSEVS . On a frame basis an ECG signal is reconstructed by multiplying three model parameters namely predefined signature vector PSV R predefined envelope vector PEV K and frame-scaling coefficient FSC . All the PSVs and PEVs are labeled and stored in their respective sets to describe the signal in the reconstruction process. In this case an ECG signal frame is modeled by means of the members of these sets labeled with indices R and K and the frame-scaling coefficient in the least mean square sense. The proposed method is assessed through the use of percentage root-mean-square difference PRD and visual inspection measures. Assessment results reveal that the proposed method provides significant data compression ratio CR with low-level PRD values while preserving diagnostic information. This fact significantly reduces the bandwidth of communication in telediagnosis operations. Copyright 2007 Hakan Gurkan et al. This is an open .