IEEE transactions on bio-medical engineering
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IEEE Trans Biomed Eng · May 2013
Leakage estimation using Kalman filtering in noninvasive mechanical ventilation.
Noninvasive mechanical ventilation is today often used to assist patient with chronic respiratory failure. One of the main reasons evoked to explain asynchrony events, discomfort, unwillingness to be treated, etc., is the occurrence of nonintentional leaks in the ventilation circuit, which are difficult to account for because they are not measured. This paper describes a solution to the problem of variable leakage estimation based on a Kalman filter driven by airflow and the pressure signals, both of which are available in the ventilation circuit. The filter was validated by showing that based on the attained leakage estimates, practically all the untriggered cycles can be explained.
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IEEE Trans Biomed Eng · May 2013
Blood perfusion values of laser speckle contrast imaging and laser Doppler flowmetry: is a direct comparison possible?
Laser Doppler flowmetry (LDF) and laser speckle contrast imaging (LSCI) allow the monitoring of microvascular blood perfusion. The relationship between the measurements obtained by these two techniques remains unclear. In the present contribution, we demonstrate, experimentally and theoretically, that skin blood flow measurements obtained by LDF and LSCI techniques cannot be compared directly even after "classical" normalization procedure. ⋯ The experiments have been performed on five healthy voluntary subjects (forearm) by using repeated ischemia/reperfusion cycles to induce the necessary skin blood flow changes. LDF and LSCI data were simultaneously acquired on the same region of interest. Considering the importance of this problem from the clinical point of view, it is concluded that the definition of new corrected algorithms for LSCI is probably a mandatory step that must be taken into account if LDF and LSCI blood flow have to be compared.
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IEEE Trans Biomed Eng · May 2013
Fetal ECG extraction by extended state Kalman filtering based on single-channel recordings.
In this paper, we present an extended nonlinear Bayesian filtering framework for extracting electrocardiograms (ECGs) from a single channel as encountered in the fetal ECG extraction from abdominal sensor. The recorded signals are modeled as the summation of several ECGs. ⋯ The parameter sensitivity analysis for different values of noise level, amplitude, and heart rate ratios between fetal and maternal ECGs shows its effectiveness for a large set of values of these parameters. This framework is also validated on the extractions of fetal ECG from actual abdominal recordings, as well as of actual twin magnetocardiograms.