Alignment methods for averaging of high-resolution cardiac signals: a comparative study of performance

Jané, R.; Rix, Hervé; Caminal, P.; Laguna, Pablo

doi:10.1109/10.81582

Cited by 100 publications

(48 citation statements)

References 13 publications

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“…The problem is just as obvious because any individual beat-to-beat interval has the potential of being dramatically different from the mean. Therefore, each heartbeat must be segmented using an adaptive approach (Jane et al, 1991). For the ECG, the process is straightforward because the trace contains a number of high frequency components to match.…”

Section: Heartbeat Alignmentmentioning

confidence: 99%

Heartbeat biometrics: a sensing system perspective

Israel¹,

Irvine²

2012

IJCB

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This paper reviews the emerging research into exploitation of heartbeat data as a biometric for human identification. A variety of methods have been proposed for acquiring heartbeat signatures and a range of processing methods has been examined. We approach the biometric identification and verification problem by characterising the three major factors affecting performance: individual variants, environmental variants, and sensor variants. The ability to collect and process the signal, exploit the data for individual identification or verification, and disseminate the information depends on all three of these factors. Within each component, we have identified the relevant research. Where possible, we have tied these research papers to practical examples using high resolution ECG data. The research indicates that the heartbeat contains rich information about the individual, their level of anxiety, and the cardiac state.Keywords: biometrics; heartbeat; ECG; sensing system; cardiovascular function; human identification. areas of interest include novel biometrics, signal and image processing, quantification and modelling of data quality, and cognitive modeling. He was a Principal Investigator for DARPA's Human Identification at a Distance Program (HumanID). He serves on planning committees for IEEE and SPIE, and has served on several advisory panels for the Department of Defence and the Department of Energy. He has authored over a hundred journal and conference papers and holds a PhD in Mathematical Statistics from Yale University.

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Section: Heartbeat Alignmentmentioning

confidence: 99%

Heartbeat biometrics: a sensing system perspective

Israel¹,

Irvine²

2012

IJCB

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“…The detector is based on an adaptive threshold in the ECG amplitude that has been previously filtered with a band-pass filter (12)(13)(14)(15)(16)(17)(18)(19)(20)(21)(22).…”

Section: R Wave Detectormentioning

confidence: 99%

“…For this reason, a 1-kHz sampling rate is used, reducing the low-pass filter effect due to the presence of alignment errors 12 . This fact affects the remaining QT segment contribution in the r(n) signal, which is not only influenced by the correct alignment of QRS pulses, but also by the selected value for the adaptation constant (μ) in the adaptive algorithm.…”

Section: Qt Pattern Cancellationmentioning

confidence: 99%

P and R Wave Detection in Complete Congenital Atrioventricular Block

et al. 2008

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Complete atrioventricular block (type III AVB) is characterized by an absence of P wave transmission to ventricles. This implies that QRS complexes are generated in an autonomous way and are not coordinated with P waves. This work introduces a new algorithm for the detection of P waves for this type of pathology using non-invasive electrocardiographic surface leads.The proposed algorithm is divided into three stages. In the first stage, the R waves located by a QRS detector are used to generate the RR series and time references for the other stages of the algorithm. In the second stage, the ventricular activity (QT segment) is removed by using an adaptive filter that obtains an averaged pattern of the QT segment. In the third stage, a new P wave detector is applied to the residual signal obtained after QT cancellation in order to detect P wave locations and get the PP time series.Eight Holter records from patients with congenital type III AVB were used to verify the proposed algorithm. Although further improvements should be made to improve the algorithm's performance, the results obtained show high average values of sensitivity (90.52 %) and positive prediction (90.98%). KeywordsComplete congenital atrioventricular block, P and R wave detection, QRS, adaptive impulse correlated filter, SNEO.2 2

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“…The performance of the alignment methods was evaluated by the standard deviation σ of the alignment error, which is inversely related with the cutoff frequency of an equivalent lowpass filter of the averaged signal [8]. The mean value of σ for all morphologies tested is presented in Table 1 and in Figure 5 for a range of noise levels of white and EMG noise for both temporal and wavelet cross-correlation methods.…”

Section: Resultsmentioning

confidence: 99%

“…For this reason, several alignment techniques have been proposed to search for a precise fiducial point in HRECG records [4], [5], [6], [7]. A complete comparative study of the performance of the different alignment methods was presented in [8].…”

Section: Introductionmentioning

confidence: 99%

A new alignment method based on the wavelet multi-scale cross-correlation for noisy high resolution ECG records

Laciar

Jané

Brooks³

2001 Conference Proceedings of the 23rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society

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Abstract-The coherent signal averaging process requires an accurate estimation of the fiducial point in all beats to be averaged. The temporal cross-correlation between the detected beat and a template beat is the typical alignment method used with high-resolution ECG (HRECG) records. However, this technique does not produce a precise fiducial mark in records with high noise levels. In this study, we propose a new alignment method based on the multi-scale cross-correlation between the wavelet transforms of the template and the detected beat, respectively. The wavelet and temporal methods were tested for several simulated records corrupted with white noise and electromyographic (EMG) noise of different RMS levels. The results indicate that wavelet alignment method produces a lower trigger jitter than the temporal method in all tests. We conclude that the proposed alignment method can be used in records with high noise levels, like those found in Holter HRECG systems.

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Alignment methods for averaging of high-resolution cardiac signals: a comparative study of performance

Cited by 100 publications

References 13 publications

Heartbeat biometrics: a sensing system perspective

Heartbeat biometrics: a sensing system perspective

P and R Wave Detection in Complete Congenital Atrioventricular Block

A new alignment method based on the wavelet multi-scale cross-correlation for noisy high resolution ECG records

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