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Multivariate analysis of follow-up physiological data recorded by cardiac implantable devices

Abstract : New cardiac implantable devices (IDs) allow the acquisition of an increasing amount of data relative to the patient's activity. A quantitative analysis of these data can be of particular interest to optimize the stimulation therapy and to improve patient follow-up. This work presents a method to: i) evaluate the information content of the ID memory data; ii) define synthetic indexes that would summarize these data and ease their interpretation and iii) characterize and compare different patient populations. The proposed approach is based on a coding stage allowing the representation of time-varying data, followed by a multivariate analysis stage, based on principal component analysis (PCA). Results show that the initial 38 variables obtained from the IDs memory contain pertinent information that can be synthesized with a low number of indexes (the first four factorial axes of the PCA represent 70% of the total variance) and that these indexes can be useful to follow the evolution of a given patient's state.
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https://hal.archives-ouvertes.fr/hal-01370980
Contributor : Emmanuel Roux <>
Submitted on : Monday, September 26, 2016 - 2:19:10 PM
Last modification on : Friday, January 15, 2021 - 3:33:22 AM

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Emmanuel Roux, Alfredo Hernandez, Laurence Graindorge, Guy Carrault, Philippe Mabo. Multivariate analysis of follow-up physiological data recorded by cardiac implantable devices. Computers in Cardiology, 2006, Valencia, Spain. ⟨hal-01370980⟩

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