Analysis of cardiac micro-acceleration signals for the estimation of systolic and diastolic time intervals in cardiac resynchronization therapy

Giorgis, L.; Hernández, Alfredo; Amblard, Amel; Senhadji, Lotfi; Cazeau, Serge; Jauvert, Gaël; Donal, Erwan

doi:10.1109/cic.2008.4749061

Cited by 18 publications

(14 citation statements)

References 8 publications

(9 reference statements)

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“…Figure 1 presents an example of a processed average cycle, acquired from a CRT recipient during bi-ventricular pacing and showing the main detection instants, when using an envelogram computed with the absolute value method. Similar envelope estimation methods have been largely applied to the segmentation of PCG signals and it has been shown that their performance strongly depends on the tuning of f c, w, λ and M [4]- [7], [13].…”

Section: A Brief Description Of the Original Methods And Its Parametersmentioning

confidence: 99%

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Optimal Algorithm Switching for the Estimation of Systole Period From Cardiac Microacceleration Signals (SonR)

Giorgis

Frogerais

Amblard³

et al. 2012

IEEE Trans. Biomed. Eng.

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Abstract-Previous studies have shown that cardiac microacceleration signals, recorded either cutaneously, or embedded into the tip of an endocardial pacing lead, provide meaningful information to characterize the cardiac mechanical function. This information may be useful to personalize and optimize the cardiac resynchronization therapy, delivered by a biventricular pacemaker, for patients suffering from chronic heart failure. The present paper focuses on the improvement of a previously proposed method for the estimation of the systole period from a signal acquired with a cardiac micro-accelerometer (SonR sensor, Sorin CRM SAS, France). We propose an optimal algorithm switching approach, to dynamically select the best configuration of the estimation method, as a function of different control variables, such as signal-to-noise ratio or heart rate. This method was evaluated on a database containing recordings from 31 patients suffering from chronic heart failure and implanted with a biventricular pacemaker, for which various cardiac pacing configurations were tested. Ultrasound measurements of the systole period were used as a reference and the improved method was compared with the original estimator. A reduction of 11% on the absolute estimation error was obtained for the systole period with the proposed algorithm switching approach.

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Section: A Brief Description Of the Original Methods And Its Parametersmentioning

confidence: 99%

“…In a previous work, we studied an external version of the SonR signal, and proposed a method to estimate the mitral and aortic valve closure instants [13]. This method was then clinically evaluated in the context of CRT optimization with data from 75 HF patients, under different pacing configurations [14].…”

mentioning

confidence: 99%

Optimal Algorithm Switching for the Estimation of Systole Period From Cardiac Microacceleration Signals (SonR)

Giorgis

Frogerais

Amblard³

et al. 2012

IEEE Trans. Biomed. Eng.

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“…Moreover, these results cannot state if the SonR4 signal comes from the right, the left atrium or both chambers. Different studies on the SonR signal suggest that this type of component is an expression of vibrations of the whole cardiac tissue, regardless of the lead position [2], and that it is rather the expression of events taking place in the left chambers, especially because pressures level are less important in the right atrium.…”

Section: Discussionmentioning

confidence: 99%

“…The SonR signal was recorded by the SonR™ micro accelerometer (Sorin CRM SAS, Clamart, France) placed at the tip of a right atrial lead as previously described [2]. SonR4 templates were retrieved and computed during series of 15 consecutive beats.…”

Section: Sonr Signal Assessmentmentioning

confidence: 99%

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Validation of a Marker of Atrial Contraction in the SonR Signal

Broussous¹,

Kobeissi²,

Dumont³

et al. 2015

WJCD

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Introduction: The main component of the endocardial acceleration signal (SonR) is today used for cardiac resynchronization therapy (CRT) optimization. This prospective, single center pilot study focuses on another signal component, SonR4 that may provide further information on the atrial activity. Methods and Results: SonR signal and ECG tracings were recorded simultaneously during a CRT-D optimization procedure in 15 patients (12 men, 68 ± 9.5 years, ischemic heart disease 53%) indicated for CRT. Correlation between SonR4 signal, recorded using SonR and atrial contraction, identified by Echo Doppler was evaluated by Pearson and Student's t tests under different Atrio-Ventricular (AV) delay programming. From 15 consecutive screened patients, 9 had concomitant analyzable SonR4 and ECG recordings and were included in the study population. The presence of the SonR4 component was systematically correlated to the presence of the A wave. A significant correlation was observed between SonR4 and A wave timings (r = 0.75, p = 0.02) according to different AV delays, with a high reproducibility in SonR4 assessment. Conclusion: A strong correlation between SonR4 and atrial contraction timings was observed, further suggesting that SonR4 is a marker of the atrial contraction. Additional assessments in larger populations are required to confirm these results and build further applications.

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