In this paper a simple signal segmentation algorithm is introduced. The algorithm determines the epochs of signal components of interest based on signal characteristic such as amplitude, slope, deflection width, or distance between neighboring deflections. The epochs are segmented indirectly by means of a slope trace wave that traces a signal with its average slope and predetermined delay. The algorithm is applied to ECG and electrogram to show its practical applicability and efficiency. It is found that the algorithm can be used to choose particular signal components appropriately without significant signal preprocessing or complexity.
This paper introduces a new approach to process biomedical signals by surgically removing wave deflections in time domain. The method first determines the epochs of high frequency deflections, cuts out them from the signal, and then connects the two disconnected points. To determine the epoch of a deflection to be removed, four slope trace waves are used to isolate the deflection based on signal characteristics of amplitude, slope, duration, and distance from neighboring deflections. The method has been applied to simulated data and MIT-BIH arrhythmia database to show its practical efficacy in the case of baseline wandering removal. It is found that the method has the capability to identify and remove high frequency deflections appropriately, leaving low frequency deflection such as baseline drifting.
Abstract-Single-pass VDD pacemakers have been used as a result of simple implantation procedures and generally reliable atrial tracking. However, there is a controversy over their reliabilities of atrial tracking. As a new sensing method for reliable atrial tracking, a simple automatic pacemaker sensing algorithm was implemented and evaluated to validate its benefits in sensing depolarization waves of single-pass VDD atrial electrograms . The automatic sensing algorithm had a predetermined sensing dynamic range and the sensitivity level was controlled as 50 % of the average of two most recently sensed intrinsic amplitudes. The behavior of the automatic sensing algorithm in the single-pass VDD atrial electrograms was analyzed and characterized. It was observe d that the automatic sensing algorithm was more effective than a conventional fixed threshold method to accurately detect and track p-waves in SVDD electrograms. Keywords -Automatic sensing algorithm, pacemakers, singlepass VDD, electrogram I. INTRODUCTIONSingle-pass VDD (SVDD) pacemaker systems have been used as a result of simple implantation procedures and generally reliable atrial tracking [1][2]. However, since in the single lead electrode the atrial sensing poles are floating, the signal amplitude may vary considerably. An optimal sensitivity level can not be determined using amplitude measurements of acute atrial electrograms because of the significant amplitude variations [3][4]. I ndividual patients may experience serious P -wave undersensing that may require sensing sensitivity reprogramming or may cause asynchronous pacing.There are several studies that suggest a highest sensitivity for P-wave sensing to compensate the amplitude variation, while there are contradictory studies that concern possible oversensing problems by the highest sensitivities [5][6][7].In this study, a sensing method that adapts its sensitivity level to previous intrinsic amplitude variations, an automatic sensing algorithm, is implemented and evaluated to validate its benefits in atrial electrograms from SVDD leads. The automatic sensing algorithm had been developed for sensing of automatic implantable cardioverter defibrillator (AICD or ICD), and has been adopted by pacemakers recently [8][9]. It is expected that the automatic sensing algorithm in pacemakers will improve the sensing performance and remove the human intervention for choosing an optimal sensitivity level.The purpose of this study is to characterize the behavior of an automatic sensing algorithm during SVDD P -wave sensing and compare its sensing performance to that of a conventional fixed sensitivity method. II. METHODOLOGYA simple automatic sensing algorithm was applied to 9 patients SVDD atrial electrograms obtained by Phymos™ 830-s lead (Medico), during several different body postures, deep respiration, and walking. The algorithm had a predetermined sensing dynamic range of 0.25 -2.25 mV and controlled the sensitivity level beat by beat as 50% of the average of two most recently sensed intrinsic amplit ude...
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