No abstract

No abstract

No abstract

The main goal of this work was development of ECG processing algorithm for the real-time detection and displaying of implanted pacemaker artifacts, if they are present in the signal. In case of traditionally used characteristics of ECG acquisition circuits and analogto-digital conversion pacemaker artifacts are often scarcely distinguished. Wide frequency band of ECG amplifier (0.2-10000 Hz) and high ADC sampling rate (20000 Hz) were used to resolve this problem. All pacemaker spikes detection procedures were realized fully digitally. The developed algorithm testing with the use of the real ECG recordings set showed the following results of pacemaker spikes detection: sensitivity 86.6 % and positive predictivity 99.6 %. The proposed algorithm was included in the ECG processing software of mobile cardiac monitor CardioQVARK based on iPhone series 5, 5S and 6.

Patients with implanted pacemakers (PM) are usually not familiar with their pacing modes and other device settings. Modern bipolar endocardial pacing leads produces such a small pacing artifact that often could not be separated from noise. It becomes a challenge to judge about the underlying rhythm and current pacing mode using single ECG tracing. Good stimuli artifacts visualization and understanding of its interaction with QRS plays crucial role in ECG analysis.