May 1, 2008Physiological MeasurementOpen Access

Model-based Bayesian filtering of cardiac contaminants from biomedical recordings

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Population

Simulated and real biomedical signals containing cardiac contaminants

Design

Other

Authors

RSReza SameniGeorgia Institute of Technology MSMohammad Bagher ShamsollahiSharif University of Technology CJChristian JuttenInstitut polytechnique de Grenoble

Discussion

Member takes

Implication

May enhance signal quality in research recordings; leaves open prospective clinical validation before diagnostic adoption.

Structured PICO

Population

Simulated and real biomedical signals (electroencephalogram, electromyogram, fetal ECG/MCG) containing cardiac contaminants (ECG, MCG, ballistocardiographic artifacts)

Intervention

Model-based Bayesian filtering framework

Outcome

Removal of cardiac contaminants from biomedical recordings

A Bayesian filtering framework can effectively denoise biomedical signals by removing cardiac artifacts.

Cite This Study

Sameni et al. (2008) studied this question.

synapsesocial.com/papers/6a928c31363ee85fa149f834 https://doi.org/10.1088/0967-3334/29/5/006

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Model-based Bayesian filtering of cardiac contaminants from biomedical recordings

Discussion

Member takes

Implication

Structured PICO

Cite This Study

Model-based Bayesian filtering of cardiac contaminants from biomedical recordings

Discussion

Member takes

Implication

Structured PICO

Cite This Study

Also Consider

Also Consider