| Revista: | Computación y sistemas |
| Base de datos: | |
| Número de sistema: | 000560137 |
| ISSN: | 1405-5546 |
| Autores: | Torres Cisneros, M1 Guzmán Cabrera, R1 Villalobos, S3 May Arrioja, D.A2 Martell, F2 |
| Instituciones: | 1Universidad de Guanajuato, Applied Physics and Advanced Technologies, Guanajuato. México 2Centro de Investigaciones en Óptica, Aguascalientes. México 3Centro de Investigaciones en Óptica, Guanajuato. México |
| Año: | 2019 |
| Periodo: | Ene-Mar |
| Volumen: | 23 |
| Número: | 1 |
| Paginación: | 95-100 |
| País: | México |
| Idioma: | Inglés |
| Tipo de documento: | Artículo |
| Resumen en inglés | In the aim of automatic detection of cardiac anomalies, in particular arrhythmias, we propose and design two algorithms for arrhythmias detection based on the energy of the ECG signal. Our results have shown that it is possible to obtain a prediction error as small as 0.66% when we use the overlapped windows method. Our algorithms can obtain this error analyzing 30 min signal length just in 12 s of processing time. Our results are faster and competitive if we compare them with those in the literature. |
| Disciplinas: | Ciencias de la computación |
| Palabras clave: | Inteligencia artificial, Inteligencia artificial |
| Keyword: | ECG automatic detection, QRS complex detection, RR segment, Artificial intelligence |
| Texto completo: | Texto completo (Ver HTML) Texto completo (Ver PDF) |
