title: Classification of cardiac arrhythmias using competitive networks.
abstract: Information generated by sensors that collect a patient's vital signals are continuous and unlimited data sequences. Traditionally, this information requires special equipment and programs to monitor them. These programs process and react to the continuous entry of data from different origins. Thus, the purpose of this study is to analyze the data produced by these biomedical devices, in this case the electrocardiogram (ECG). Processing uses a neural classifier, Kohonen competitive neural networks, detecting if the ECG shows any cardiac arrhythmia. In fact, it is possible to classify an ECG signal and thereby detect if it is exhibiting or not any alteration, according to normality.
authors.affiliation: Department of Informatics - Universidade do Estado do Rio Grande do Norte (UERN) and Mater Christi Faculty of Science and Tecnology - Mossoró, Brazil Mossoró, Brazil. ciciliamaia@dca.ufm.br
authors.forename: Cicilia R M
authors.initials: CR
authors.lastname: Leite
authors.forename: Daniel L
authors.initials: DL
authors.lastname: Martin
authors.forename: Glaucia R A
authors.initials: GR
authors.lastname: Sizilio
authors.forename: Keylly E A
authors.initials: KE
authors.lastname: Dos Santos
authors.forename: Bruno G
authors.initials: BG
authors.lastname: de Araujo
authors.forename: Ricardo A M
authors.initials: RA
authors.lastname: Valentim
authors.forename: Adriao D D
authors.initials: AD
authors.lastname: Neto
authors.forename: Jorge D
authors.initials: JD
authors.lastname: de Melo
authors.forename: Ana M G
authors.initials: AM
authors.lastname: Guerreiro
mesh_terms: D000465:Algorithms; D001145:Arrhythmias, Cardiac / Q000145:classification / Q000175:diagnosis*; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D006801:Humans; D016571:Neural Networks, Computer; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted