Extended Kalman smoother with differential evolution technique for denoising of ECG signal

Electrocardiogram (ECG) signal gives a lot of information on the physiology of heart. In reality, noise from various sources interfere with the ECG signal. To get the correct information on physiology of the heart, noise cancellation of the ECG signal is required. In this paper, the effectiveness of extended Kalman smoother (EKS) with the differential evolution (DE) technique for noise cancellation of the ECG signal is investigated. DE is used as an automatic parameter selection method for the selection of ten optimized components of the ECG signal, and those are used to create the ECG signal according to the real ECG signal. These parameters are used by the EKS for the development of the state equation and also for initialization of the parameters of EKS. EKS framework is used for denoising the ECG signal from the single channel. The effectiveness of proposed noise cancellation technique has been evaluated by adding white, colored Gaussian noise and real muscle artifact noise at different SNR to some visually clean ECG signals from the MIT-BIH arrhythmia database. The proposed noise cancellation technique of ECG signal shows better signal to noise ratio (SNR) improvement, lesser mean square error (MSE) and percent of distortion (PRD) compared to other well-known methods.     

The Importance of Venous Return in Starling‐Like Control of Rotary Ventricular Assist Devices

Rotary ventricular assist devices (VADs) are less sensitive to preload than the healthy heart, resulting in inadequate flow regulation in response to changes in patient cardiac demand. Starling‐like physiological controllers (SLCs) have been developed to automatically regulate VAD flow based on ventricular preload. An SLC consists of a cardiac response curve (CRC) which imposes a nonlinear relationship between VAD flow and ventricular preload, and a venous return line (VRL) which determines the return path of the controller. This study investigates the importance of a physiological VRL in SLC of dual rotary blood pumps for biventricular support. Two experiments were conducted on a physical mock circulation loop (MCL); the first compared an SLC with an angled physiological VRL (SLC‐P) against an SLC with a vertical VRL (SLC‐V). The second experiment quantified the benefit of a dynamic VRL, represented by a series of specific VRLs, which could adapt to different circulatory states including changes in pulmonary (PVR) and systemic (SVR) vascular resistance versus a fixed physiological VRL which was calculated at rest. In both sets of experiments, the transient controller responses were evaluated through reductions in preload caused by the removal of fluid from the MCL. The SLC‐P produced no overshoot or oscillations following step changes in preload, whereas SLC‐V produced 0.4 L/min (12.5%) overshoot for both left and right VADs. Additionally, the SLC‐V had increased settling time and reduced controller stability as evidenced by transient controller oscillations. The transient results comparing the specific and standard VRLs demonstrated that specific VRL rise times were improved by between 1.2 and 4.7 s ( = 3.05 s), while specific VRL settling times were improved by between 2.8 and 16.1 seconds ( = 8.38 s) over the standard VRL. This suggests only a minor improvement in controller response time from a dynamic VRL compared to the fixed VRL. These results indicate that the use of a fixed physiologically representative VRL is adequate over a wide variety of physiological conditions.     

Tanzania IR Initiative: Training the First Generation of Interventional Radiologists

Despite a population of nearly 60 million, there is currently not a single interventional radiologist in Tanzania. Based on an Interventional Radiology (IR) Readiness Assessment, the key obstacles to establishing IR in Tanzania are the lack of training opportunities and limited availability of disposable equipment. An IR training program was designed and initiated, which relies on US-based volunteer teams of IR physicians, nurses, and technologists to locally train radiology residents, nurses, and technologists. Preliminary results support this strategy for addressing the lack of training opportunities and provide a model for introducing IR to other resource-limited settings.