Optimal algorithm switching for the estimation of systole period from cardiac microacceleration signals (SonR). - Inserm - Institut national de la santé et de la recherche médicale Accéder directement au contenu
Article Dans Une Revue IEEE Transactions on Biomedical Engineering Année : 2012

Optimal algorithm switching for the estimation of systole period from cardiac microacceleration signals (SonR).

Résumé

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 (HF). This paper focuses on the improvement of a previously proposed method for the estimation of the systole period from a signal acquired with a cardiac microaccelerometer (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 the signal-to-noise ratio or heart rate. This method was evaluated on a database containing recordings from 31 patients suffering from chronic HF 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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Dates et versions

inserm-00725533 , version 1 (03-09-2012)

Identifiants

Citer

Lionel Giorgis, Paul Frogerais, Amel Amblard, Erwan Donal, Philippe Mabo, et al.. Optimal algorithm switching for the estimation of systole period from cardiac microacceleration signals (SonR).. IEEE Transactions on Biomedical Engineering, 2012, 59 (11), pp.3009-15. ⟨10.1109/TBME.2012.2212019⟩. ⟨inserm-00725533⟩
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