## 1 Introduction
* Software approach--analyzes the digital ECG signal, which should be digitized at high sampling rates that preserve the frequency content of the pacing pulses [7; 8; 9; 10; 11]. They involve:
* band-pass filtering that has been specially designed to distinct the pace pulses from the real ECG components and low-frequency noises [12; 13];
* search for steep edges in a single lead [14; 15] or multi-lead ECG [3];
data transformations such as the first derivative of the ECG, power envelopes in the spectral range of (\(500\div 2200\)) Hz or moving statistical window followed by peak selection based on the statistical properties of the transformed signal [16];
* application of a vectorcardiogram for precise detection of biventricular pacing [17]. Recently, a hybrid approach for pace pulses detection operating at low sampling frequency has been proposed [18]. The method utilizes simple analog processing to extract the pace pulses energy via filters tuned to capture spectral contents outside ECG frequencies of interest, followed by straightforward digital pace pulse detection at a low sampling rate. The requirements of different standards, related to the parameters of the pace pulses that should be detected, are not very strong. ANSI/AAMI EC11 [19] have set the following ranges: (\(0.1\div 2\)) ms for pulses duration; (\(2\div 250\)) mV for amplitude range, up to 100 impulses per minute pacing rate and less than 100 \(\upmu\)s rising edge duration. According to the IEC60601-2-27 standard [20], the lower limit of the pulse duration range is 0.5 ms, while the upper limit of the amplitude range is as high as 700 mV. However, modern pacemakers could generate pace pulses falling below these limits [4]. The different pace pulse morphologies combined with the changes in the paced patient population presenting with a variety of arrhythmias require a significant increase in the complexity of pace pulse detection algorithms [21]. The variety of ECG rhythms combined with pace pulses that differ in amplitude, duration and appearance in the ECG is not the only challenge for the pace pulse detection algorithm. Additional difficulties could be posed by the presence of EMG noise, which overlaps with pace pulses and could prevent their correct detection. On the one hand, low-amplitude pace pulses that could hardly be distinguished from environmental noise reduce the sensitivity (Se) and could lead to erroneous alarms for pacemaker damage. On the other hand, false-positive detections that decrease the positive predictive value (PPV) could lead to inaccurate interpretation of pacemaker rhythms by automated algorithms. In our previous study [22] we reported a drop in the positive predictive value between 10% and 22% when the algorithm described in [14] was applied on ECG signals with EMG artifacts. Recently, a number of methods for EMG suppression in ECG recordings have been proposed, based on locally adaptive, low-pass Myriad filters [23], dynamic procedure for separation of ECG and EMG [24; 25], adaptive periodic segment matrix and singular value decomposition [26], electrocardiogram reconstruction by a Segmented-Beat Modulation method [27], etc. Despite that all these methods address the preservation of QRS complexes and all other components of the diagnostic ECG, a technology that does not influence the steep pace pulses outside of the frequency range of the diagnostic ECG has yet to be announced. In the last decade, Shannon energy and the Stockwell transform (called S-transform, [28]), which analyzes the ECG in the time-frequency domain, were applied separately [29; 30] or in combination [31] for heartbeat detection. The aims of this study are as follows:  
* To assess the potential of the Stockwell transform to highlight pace pulses on the background of intensive EMG artifacts in the time-frequency domain and to involve it in a brand new software approach for pace pulses detection.