IEEE transactions on bio-medical engineering
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IEEE Trans Biomed Eng · Jan 2008
Statistical modeling of cardiovascular signals and parameter estimation based on the extended Kalman filter.
Cardiovascular signals such as arterial blood pressure (ABP), pulse oximetry (POX), and intracranial pressure (ICP) contain useful information such as heart rate, respiratory rate, and pulse pressure variation (PPV). We present a novel state-space model of cardiovascular signals and describe how it can be used with the extended Kalman filter (EKF) to simultaneously estimate and track many cardiovascular parameters of interest using a unified statistical approach. ⋯ Our results demonstrate the ability of the algorithm to estimate and track several clinically relevant features of cardiovascular signals. We illustrate how the algorithm can be used to elegantly solve several actively researched and clinically significant problems including heart and respiratory rate estimation, artifact removal, pulse morphology characterization, and PPV estimation.
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IEEE Trans Biomed Eng · Dec 2007
Impedance-based ventilation detection during cardiopulmonary resuscitation.
It has been suggested to develop automated external defibrillators with the ability to monitor cardiopulmonary resuscitation (CPR) performance online and give corrective feedback in order to improve the resuscitation quality. Thoracic impedance changes are closely correlated to lung volume changes and can be used to monitor the ventilatory activity. We developed a pattern-recognition-based detection system that uses thoracic impedance to accurately detect ventilation during ongoing CPR. ⋯ The annotated ventilations were detected with an overall positive predictive value of 95.5% for a sensitivity of 90.4%. During chest compressions, the detection system achieved a mean positive predictive value of 94.8% for a sensitivity of 88.7%. The results suggest that accurate ventilation detection during CPR based on the proposed approach is feasible, and that the performance is not significantly degraded in the presence of chest compressions.
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In this paper, a nonlinear Bayesian filtering framework is proposed for the filtering of single channel noisy electrocardiogram (ECG) recordings. The necessary dynamic models of the ECG are based on a modified nonlinear dynamic model, previously suggested for the generation of a highly realistic synthetic ECG. A modified version of this model is used in several Bayesian filters, including the Extended Kalman Filter, Extended Kalman Smoother, and Unscented Kalman Filter. ⋯ The results of the study demonstrate superior results compared with conventional ECG denoising approaches such as bandpass filtering, adaptive filtering, and wavelet denoising, over a wide range of ECG SNRs. The method is also successfully evaluated on real nonstationary muscle artifact. This method may therefore serve as an effective framework for the model-based filtering of noisy ECG recordings.
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IEEE Trans Biomed Eng · Dec 2007
Predicting arterial stiffness from the digital volume pulse waveform.
Cardiovascular disease (CVD) is currently the biggest single cause of mortality in the developed world, hence, the early detection of its onset is vital for effective prevention therapies. Aortic stiffness as measured by aortic pulse wave velocity (PWV) has been shown to be an independent predictor of CVD, however, the measurement of PWV is complex and time consuming. Recent studies have shown that pulse contour characteristics depend on arterial properties such as arterial stiffness. ⋯ Further, the use of support vector regression techniques lead to a direct real-valued estimate of PWV which outperforms previous methods based on multilinear regression. We, therefore, conclude that support vector machine-based classification and regression techniques provide effective prediction of arterial stiffness from the simple measurement of the digital volume pulse. This technique could be usefully employed as a cheap and effective CVD screening technique for use in general practice clinics.
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IEEE Trans Biomed Eng · Nov 2007
The effect of lateral stabilization on walking in young and old adults.
We tested how lateral stability affects gait as a function of age. A simple computational model suggests that walking is laterally unstable and that age-related decreases in motor and sensory function may be treated as noise-like perturbations to the body. Step width variability may be affected by active control of foot placement subject to noise. ⋯ External stabilization resulted in reduced step width variability and 16% decreased energetic cost. Although there was no significant statistical interaction between age group and stabilization, Old and Young subjects walked with similar energetic costs in the stabilized, prescribed step width condition. Age-related changes appear to affect lateral balance, and the resulting compensations explain much of the increased energetic cost of walking in older adults.