000061435 001__ 61435 000061435 005__ 20200910145136.0 000061435 0247_ $$2doi$$a10.1088/0967-3334/37/7/1004 000061435 0248_ $$2sideral$$a94143 000061435 037__ $$aART-2016-94143 000061435 041__ $$aeng 000061435 100__ $$aRomero, Daniel 000061435 245__ $$aIschemia detection from morphological QRS angles changes 000061435 260__ $$c2016 000061435 5060_ $$aAccess copy available to the general public$$fUnrestricted 000061435 5203_ $$aIn this paper, an ischemia detector is presented based on the analysis of QRS-derived angles. The detector has been developed by modeling ischemic effects on the QRS angles as a gradual change with a certain transition time and assuming a Laplacian additive modeling error contaminating the angle series. Both standard and non-standard leads were used for analysis. Non- standard leads were obtained by applying the PCA technique over specific lead subsets to represent different potential locations of the ischemic zone. The performance of the proposed detector was tested over a population of 79 patients undergoing percutaneous coronary intervention in one of the major coronary arteries (LAD (n = 25), RCA (n = 16) and LCX (n = 38)). The best detection performance, obtained for standard ECG leads, was achieved in the LAD group with values of sensitivity and specificity of Se = 90.9%, Sp = 95.4%, followed by the RCA group with Se = 88.9%, Sp = 94.4 and the LCX group with Se = 86.1%, Sp = 94.4%, notably outperforming detection based on the ST series in all cases, with the same detector structure. The timing of the detected ischemic events ranged from 30 s up to 150 s (mean = 66.8 s) following the start of occlusion. We conclude that changes in the QRS angles can be used to detect acute myocardial ischemia 000061435 536__ $$9info:eu-repo/grantAgreement/ES/MINECO/TEC2013-42140-R$$9info:eu-repo/grantAgreement/ES/MINECO/TIN2013-41998-R 000061435 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttp://creativecommons.org/licenses/by/3.0/es/ 000061435 590__ $$a2.058$$b2016 000061435 591__ $$aENGINEERING, BIOMEDICAL$$b37 / 77 = 0.481$$c2016$$dQ2$$eT2 000061435 591__ $$aPHYSIOLOGY$$b50 / 84 = 0.595$$c2016$$dQ3$$eT2 000061435 591__ $$aBIOPHYSICS$$b49 / 73 = 0.671$$c2016$$dQ3$$eT3 000061435 592__ $$a0.688$$b2016 000061435 593__ $$aBiomedical Engineering$$c2016$$dQ2 000061435 593__ $$aBiophysics$$c2016$$dQ2 000061435 593__ $$aPhysiology$$c2016$$dQ3 000061435 593__ $$aPhysiology (medical)$$c2016$$dQ3 000061435 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/acceptedVersion 000061435 700__ $$0(orcid)0000-0002-7503-3339$$aMartínez, Juan Pablo$$uUniversidad de Zaragoza 000061435 700__ $$0(orcid)0000-0003-3434-9254$$aLaguna, Pablo$$uUniversidad de Zaragoza 000061435 700__ $$0(orcid)0000-0002-1960-407X$$aPueyo, Esther$$uUniversidad de Zaragoza 000061435 7102_ $$15008$$2800$$aUniversidad de Zaragoza$$bDpto. Ingeniería Electrón.Com.$$cÁrea Teoría Señal y Comunicac. 000061435 773__ $$g37, 7 (2016), 1004-1023$$pPhysiol. meas.$$tPHYSIOLOGICAL MEASUREMENT$$x0967-3334 000061435 8564_ $$s274656$$uhttps://zaguan.unizar.es/record/61435/files/texto_completo.pdf$$yPostprint 000061435 8564_ $$s79987$$uhttps://zaguan.unizar.es/record/61435/files/texto_completo.jpg?subformat=icon$$xicon$$yPostprint 000061435 909CO $$ooai:zaguan.unizar.es:61435$$particulos$$pdriver 000061435 951__ $$a2020-09-10-14:38:37 000061435 980__ $$aARTICLE