Wavelet-based event detection in implantable cardiac rhythm management devices.
This paper presents a novel event detector for implantable devices. The algorithm is based on a signal model which describes an event as a linear combination of basis functions. The linear combination involves two fundamental electrogram waveforms represented at different time scales. An efficient, low-complexity detector is developed using the dyadic wavelet transform with integer filter coefficients, and a generalized likelihood ratio test. The results show that reliable detection is obtained at an intermediate signal-to-noise ratio (SNR = 25 dB) for various common noise sources. In terms of probabilities of missed events and false alarms, an over-all performance of 0.7% and 0.1%, respectively, was achieved on electrograms corrupted by the different noise types at an intermediate SNR.
Aström
Magnus
M
Department of Electrical Engineering, Lund University, SE-221 00 Lund, Sweden.
Olmos
Salvador
S
Sörnmo
Leif
L
D000465:Algorithms; D001145:Arrhythmias, Cardiac / Q000175:diagnosis* / Q000628:therapy*; D016477:Artifacts; D002304:Cardiac Pacing, Artificial / Q000379:methods*; D003936:Diagnosis, Computer-Assisted / Q000295:instrumentation / Q000379:methods*; D004562:Electrocardiography / Q000295:instrumentation / Q000379:methods*; D006801:Humans; D010138:Pacemaker, Artificial; D019736:Prostheses and Implants; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted; D013813:Therapy, Computer-Assisted / Q000295:instrumentation / Q000379:methods*