Computer analysis of implanted cardiac pacemaker rhythm

Fairweather, Jamie; Johnston, Paul; Luo, Shen; Macfarlane, Peter W.

doi:10.1109/cic.2007.4745454

Cited by 7 publications

(6 citation statements)

References 10 publications

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“…• Dataset 1 -306 ECGs from 51 pacer-patients, including 16 patients with biventricular pacemakers [1]; • Dataset 2 -6 normal ECGs with significant motion artifact; • Dataset 3 -10 normal ECGs incorporating spikes generated by a high energy static gun or clothing static. 49% of Dataset 1 (25 out 51 patients) was used for training and the remainder for testing along with Datasets 2 and 3.…”

Section: Methodsmentioning

confidence: 99%

Performance study of digital pacer spike detection as sampling rate changes

Luo

Johnston

Hong

2008

2008 Computers in Cardiology

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In this study, we first collected ECG data at 32 ksps and 500 sps from 51 patients with an implanted cardiac pacemaker. We also included 16 non paced ECGs with severe motion artifact and static interference. We then annotated the pacer pulses (locations and classifications) using special viewing software and divided the data into training and testing sets. We developed three digital pacemaker stimulus detection algorithms, one for each of three different sampling rates (500 sps, 8 ksps, and 32 ksps) by using similar detection concepts. After tuning them on the training sets at the corresponding sampling rates, we investigated their performances. Results showed that the detection algorithm based on the 12-lead 500-sps data stream has a good performance (Sensitivity or Se=77.51%; Positive Productive Value, or +P=90.32%). The 8-ksps detector has a better performance (Se=95.37; +P=99.77). The digital pacemaker detection algorithm for 32 ksps or higher data provided almost 100% true pacer spike detection (Se=99.51 and +P=100%). In summary, high speed sampling at 32ksps can provide accurate detection of modern pacers and leads to a significant improvement in detection of pacemaker stimuli compared to the reduced sampling rates used previously.

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Section: Methodsmentioning

confidence: 99%

Performance study of digital pacer spike detection as sampling rate changes

Luo

Johnston

Hong

2008

2008 Computers in Cardiology

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“…Sub‐threshold pacing associated with this sensor may be made more prominent when enhanced pacemaker detection features (which alter filtering and processing of ECG signals) are activated in ECG machines . Since the detection algorithms are still imperfect, there may be variability in the number of spikes detected per beat . This could account for variability in the spikes observed on the surface ECG.…”

Section: Case Reportmentioning

confidence: 99%

An uncommon ECG manifestation of normal pacemaker function

Kumar

Morgan

Jordan‐Watt³

et al. 2019

Journal of Arrhythmia

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A presumed abnormal electrocardiogram (ECG) was obtained from an asymptomatic patient with a pacemaker. Systematic evaluation of the ECG revealed that the artifact was due to a physiological sensor in the pacemaker which was displayed when the enhanced pacemaker detection features on the ECG machine was activated. The article discusses the possible causes and an approach to similar artifacts. K E Y W O R D Sartifact, closed loop stimulation, electrocardiogram, electromagnetic interference, pacemaker

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“…6 Set 2 obtained from the University Medical Center of Tucson in 2008, included 41 patents (6 BiV and 35 RV pacing) with a mean age of 73 ±13 years, of whom 56% were male. 10 Set 3, recorded at Glasgow Royal Infirmary in 2009, consisted of 62 patients (33 BiV and 29 RV pacing) with a mean age of 66± 12 years, with 79% being male.…”

Section: Patient Populationmentioning

confidence: 99%

“…6 The analog detector or 8-ksps digital detector of earlier machines was replaced by a 64-ksps digital detection system, also in Burdick E8300 and E8500 devices (Fig. 1C).…”

Section: Introductionmentioning

confidence: 99%