Interbeat control of a ventricular assist device for variable pump performance

Moriya, Aoi; Yoshizawa, Makoto; Shiraishi, Yasuyuki; Yambe, Tomoyuki

doi:10.1109/embc.2013.6610853

Cited by 2 publications

(2 citation statements)

References 7 publications

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“…Although a ''constant speed mode'', which makes the rotational speed of the pump constant, is most commonly used in clinical situations, several studies have reported a benefit of pulsatile control synchronizing with the patient's heartbeat [1][2][3][4], which is the so-called heartbeat synchronization method. For instance, Ando et al revealed in [2] that a ''counter pulse drive mode'', which makes the rotational speed to slow down in the patient's systolic phase, can enhance myocardial perfusion.…”

Section: Introductionmentioning

confidence: 99%

Sensorless cardiac phase detection for synchronized control of ventricular assist devices using nonlinear kernel regression model

et al. 2016

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Recently, driving methods for synchronizing ventricular assist devices (VADs) with heart rhythm of patients suffering from severe heart failure have been receiving attention. Most of the conventional methods require implanting a sensor for measurement of a signal, such as electrocardiogram, to achieve synchronization. In general, implanting sensors into the cardiovascular system of the patients is undesirable in clinical situations. The objective of this study was to extract the heartbeat component without any additional sensors, and to synchronize the rotational speed of the VAD with this component. Although signals from the VAD such as the consumption current and the rotational speed are affected by heartbeat, these raw signals cannot be utilized directly in the heartbeat synchronization control methods because they are changed by not only the effect of heartbeat but also the change in the rotational speed itself. In this study, a nonlinear kernel regression model was adopted to estimate the instantaneous rotational speed from the raw signals. The heartbeat component was extracted by computing the estimation error of the model with parameters determined by using the signals when there was no effect of heartbeat. Validations were conducted on a mock circulatory system, and the heartbeat component was extracted well by the proposed method. Also, heartbeat synchronization control was achieved without any additional sensors in the test environment.

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Section: Introductionmentioning

confidence: 99%

Sensorless cardiac phase detection for synchronized control of ventricular assist devices using nonlinear kernel regression model

et al. 2016

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“…Position of the car in the navigation system and the information of the expressway design. Up & down slope and Right and left curve were shown in the figureAt Tohoku University, various types of medical information detection units are now under development by the Graduate School of Biomedical Engineering, and these sensors can be used for drivers in a non-invasive way(11)(12)(13)(14)(15).…”

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confidence: 99%