ST shape classification in ECG by constructing reference ST set

References 

1. Smrdel A, Jager F. Automated detection of transient ST-segment episodes in 24h electrocardiograms. Medical and Biological Engineering and Computing. 2004;42(3):303–311
2. Papaloukas C, Fotiadis DI, Liavas AP, Likas A, Michalis LK. A knowledge-based technique for automated detection of ischaemic episodes in long duration electrocardiograms. Medical and Biological Engineering and Computing. 2001;39(1):105–112
3. Zimmerman MW, Povinelli RJ. On improving the classification of myocardial ischemia using Holter ECG data. Computers in Cardiology. 2004;377–380
4. Langley P, Bowers EJ, Wild J, Drinnan MJ, Allen J, Brown N. An algorithm to distinguish ischaemic and non-ischaemic ST changes in the Holter ECG. Computers in Cardiology. 2003;30:239–242
5. Andreao RV, Dorizzi B, Boudy J, Mota JCM. ST-segment analysis using hidden Markov Model beat segmentation: application to ischemia detection. Computers in Cardiology. 2004;381–384
6. Author MA. Fast computation and applications to ischemic detection from electrocardiograms of the dilated, discrete Hermite Transform. In: Bioengineering Conference, 2009 IEEE 35th Annual. Boston. 2009;
7. Amit G, Davrath LR, Abboud S, Hod H, Toledo E. Ischemia monitoring by analysis of depolarization change. Computers in Cardiology. 2008;377–380
8. Gudipati P, Rajan PK. Ischemic episode detection in an ECG waveform using discrete cosine transform and artificial neural network. In: 40th Southeastern Symposium on System Theory. 2008;p. 218–221
9. Faganeli J, Jager F. Automatic distinguishing between ischemic and heart-rate related transient ST segment episodes in ambulatory ECG records. Computers in Cardiology. 2008;381–384
10. Papaloukas C, Goletsis Y, Fotiadis DI, Likas A, Michalis LK. HySMID: an ischemia diagnosis system using genetic algorithms and multicriteria decision analysis. Computers in Cardiology. 2003;(September):343–346
11. Smrdel A, Jager F. Advanced detection of ST segment episodes in 24-Hour ambulatory ECG data by automated tracking of transient ST segment reference level. Computers in Cardiology. 2002;29:325–328
12. Dranca L, Goni A, Illarramendi A. Using decision trees for real-time ischemia detection. In: 19th IEEE International Symposium on Computer-Based Medical Systems. June. 2006;p. 719–726
13. Zimmerman MW, Povinelli RJ, Johnson MT, Ropella KM. A reconstructed phase space approach for distinguishing ischemic from non-ischemic ST changes using Holter ECG data. Computers in Cardiology. 2003;(September):243–246
14. Moraru L, Tong S, Malhotra A, Geocadin R, Thakor N, Bezerianos A. Investigation of the effects of ischemic preconditioning on the HRV response to transient global ischemia using linear and nonlinear methods. Medical Engineering and Physics. 2005;27(6):465–473
15. Jeong GY, Yu KH, Kim NG. A polynomial approximation approach for analyzing ST shape change. In: 27th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. 2005;
16. Jeong GY, Yu KH. Morphological classification of ST segment using reference STs set. In: 29th Annual International Conference of the IEEE EMBS. Lyon, France. 2007;p. 636–639
17. Wellens HJJ, Gorgels APM, Doevendans PA. The ECG in Acute Myocardial Inarction and Unstable Angina. Kluwer Academic Publishers; 2004;
18. O’Keefe JH, Hammill SC, Freed MS, Pogwizd SM. The Complete Guide to ECGs. Physicians’ Press; 2002;
19. Phibbs BP. Advanced ECG: Boards and Beyond. Saunders Elsevier; 2006;
20. Taddei A, Biagini A, Distante G, Erndin M, Mazzei MG, Pisani P, et al. The Europena ST-T database: development, distribution and use. Computers in Cardiology. 1990;177–180