Unsupervised classification of atrial heartbeats using a prematurity index and wave morphology features

Medical and Biological Engineering and Computing

Volumn 47, Issue 7, 2009, Pages 731-741

  Rodríguez Sotelo, José Luis ^a   Cuesta Frau, D ^b   Castellanos Dominguez, G ^a  

^a UNIVERSIDAD NACIONAL DE COLOMBIA   (Colombia)

^b INSTITUTO TECNOLÓGICO DE INFORMÁTICA   (Spain)

Author keywords

Atrial premature beats; Heartbeat classification; J means clustering

Indexed keywords

ATRIAL PREMATURE BEATS; AUTOMATED DIAGNOSIS; CARDIAC ARRHYTHMIA; EXPERIMENTAL DATA; FEATURE VECTORS; HEARTBEAT CLASSIFICATION; J-MEANS CLUSTERING; MAX-MIN; P WAVES; PREMATURE BEATS; QRS COMPLEXES; SENSITIVITY AND SPECIFICITY; SPECIFIC PROBLEMS; UNSUPERVISED CLASSIFICATION;

MORPHOLOGY;

RISK PERCEPTION;

ARTICLE; ARTIFACT REDUCTION; CLASSIFICATION; CONTROLLED STUDY; DIAGNOSTIC ACCURACY; DIAGNOSTIC VALUE; ELECTROCARDIOGRAPHY; HEART ARRHYTHMIA; HEART BEAT; HEART RATE VARIABILITY; MATHEMATICAL COMPUTING; P WAVE; QRS COMPLEX; R WAVE; RELIABILITY; RISK ASSESSMENT; RR INTERVAL; SENSITIVITY AND SPECIFICITY; SIGNAL PROCESSING; STROKE; SUPRAVENTRICULAR PREMATURE BEAT;

ALGORITHMS; ATRIAL PREMATURE COMPLEXES; ELECTROCARDIOGRAPHY; HEART ATRIA; HEART RATE; HUMANS; SIGNAL PROCESSING, COMPUTER-ASSISTED;

EID: 67349271031     PISSN: 01400118     EISSN: None     Source Type: Journal    
DOI: 10.1007/s11517-009-0435-2     Document Type: Article

References (17)

1. Ahlstrom M, Tompkins J (1985) Digital filters for real-time ecg signal processing using microprocessors. IEEE Trans Biomed Eng 32(9):708-713
2. Association AH (2007) Premature beats. http://www.americanheart.org
3. Bahmanyar M, Balachandran W (2005) Beat to beat classification of long electrocardiograms using entropies and hierarchical clustering. In: Proceedings of the 2005 IEEE engineering in medicine and biology 27th annual conference. IEEE, IEEE, Shanghai, China, pp 5579-5581
4. Cuesta-Frau D, Biagetti M, Micó-Tormos RQP, Aboy M (2007) Unsupervised classification of ventricular extrasystoles using bounded clustering algorithms and morphology matching. Med Biol Eng Comput 45(3):229-239
5. Cuesta D, Pérez-Cortés J, Andreu-García G (2003) Clustering of ecg signals in computer-aided holter analysis. Comput Methods Programs Biomed 72:179-196
6. De-Chazal P, O'Dwyer M, Reilly R (2004) Automatic classification of heartbeats using ecg morphology and heartbeat interval features. IEEE Trans Biomed Eng 51(7):1196-1206
7. Engström G, Hedblad B, Juul-Möller S, Tydén P, Janzon L (2000) Cardiac arrhythmias and stroke increased risk in men with high frequency of atrial ectopic beats. Stroke, American Heart Association, London, pp 2925-2929
8. Goodacre S, Irons R (2002) Abc of clinical electrocardiography, atrial arrhythmias. BMG 324:594-597
9. Hansen P, Mladenovic N (2001) J-means: A new local search heuristic for minimum sum of squares clustering. Pattern Recognit 34:405-413
10. Jain A, Murty M, Flynn P (1999) Data clustering: A review. ACM Comput Surv 31(3):265-323
11. Lagerholm M, Peterson C, Braccini G, Edenbrandt L, Sönmo L (2000) Clustering ecg complexes using hermite functions and self-organising maps. IEEE Trans Biomed 48:838-847
12. Mark R, Moody G (1997) Mit-bih arrhythmia database. http://ecg.mit.edu/ dbinfo.html
13. Roddy A (1991) A filter to suppress ecg baseline wander and preserve st-segment accuracy in a real-time environment. J Electrocardiol 24(4):315-323
14. Sahambi JS, Tandon SN, Bhatt RP (1997) Using wavelet transform for ecg charecterization. IEEE Trans Eng Med Biol 16:77-88
15. So H (1998) On adaptive cancellation of multiple interfering sinusoids. Tech. rep., University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong
16. Talman W (2001) Atrial ectopic beats: Another risk factor for stroke. J Watch Neurol 221:1
17. Wallmann D, Tüller D, Wustmann K, Meier P, Isenegger J, Arnold M, Mattle H, Delacrétaz E (2007) Frequent atrial premature beats predict paroxysmal atrial fibrillation in stroke patients: An opportunity for a new diagnostic strategy. STROKE J Am Heart Assoc 38:2292-2294