Prediction of paroxysmal atrial fibrillation based on non-linear analysis and spectrum and bispectrum features of the heart rate variability signal

• Published in: Computer methods and programs in biomedicine Vol. 105; no. 1; pp. 40 - 49
• Main Authors: Mohebbi, Maryam, Ghassemian, Hassan
• Format: Journal Article
• Language: English
• Published: Kidlington Elsevier Ireland Ltd 01.01.2012; Elsevier
• Subjects: Algorithms; Atrial Fibrillation - diagnosis; Biological and medical sciences; Bispectrum; Electrocardiography - methods; Heart Rate - physiology; Heart rate variability; Humans; Internal Medicine; Medical sciences; Non-linear analysis; Other; Paroxysmal atrial fibrillation; Prediction; Radiotherapy. Instrumental treatment. Physiotherapy. Reeducation. Rehabilitation, orthophony, crenotherapy. Diet therapy and various other treatments (general aspects); Spectrum; Support vector machines; Technology. Biomaterials. Equipments. Material. Instrumentation; Support vector machines; Non-linear analysis; Prediction; Bispectrum; Paroxysmal atrial fibrillation; Heart rate variability; Spectrum; Biomedical engineering
• ISSN: 0169-2607; 1872-7565; 1872-7565
• DOI: 10.1016/j.cmpb.2010.07.011

In this paper, an effective paroxysmal atrial fibrillation (PAF) prediction algorithm is presented, which is based on analysis of the heart rate variability (HRV) signal. The proposed method consists of a preprocessing step for QRS detection and HRV signal extraction. In the next step, several featu...