Department of Bioengineering, Cardiovascular Innovation Institute, University of Louisville, Louisville, Kentucky 40202, USA.
ASAIO J. 2013 Jul-Aug;59(4):410-9. doi: 10.1097/MAT.0b013e3182976838.
Clinical acceptance of ventricular assist devices (VADs) as long-term heart failure therapy requires safe and effective circulatory support for a minimum of 5 years. Yet, VAD failure beyond 2 years of support is still a concern. Currently, device controllers cannot consistently predict VAD failure modes, and undetected VAD faults may lead to catastrophic device failure. To minimize this risk, a model-based algorithm for reliable VAD fault detection that only requires VAD revolutions per minute (rpm) was developed. The algorithm was tested using computer models of the human cardiovascular system simulating heart failure and axial flow (AF) or centrifugal flow (CF) VADs. Ventricular assist device rpm was monitored after a step down of motor current for normal and simulated fault conditions (>750 faults). The ability to detect fault conditions with 1%, 5%, and 10% rpm measurement noise was evaluated. All failure modes affected the VAD rpm responses to the motor current step down. Fault detection rates were >95% for AF and >89% for CF VADs, even with 10% rpm measurement noise. The VAD rpm responses were significantly altered by blood viscosity (3.5-6.2 cP), which should be accounted for in clinical application. The proposed VAD fault detection algorithm may deliver a convenient and nonintrusive way to minimize catastrophic device failures.
临床接受心室辅助装置(VAD)作为长期心力衰竭治疗需要安全有效的循环支持至少 5 年。然而,超过 2 年的 VAD 支持后仍然存在故障的担忧。目前,设备控制器无法始终如一地预测 VAD 故障模式,未检测到的 VAD 故障可能导致灾难性的设备故障。为了最大限度地降低这种风险,开发了一种基于模型的可靠 VAD 故障检测算法,该算法仅需要每分钟 VAD 转数(rpm)。该算法使用模拟心力衰竭和轴流(AF)或离心流(CF)VAD 的人体心血管系统计算机模型进行了测试。在电机电流下降后监测 VAD rpm,模拟正常和故障条件(>750 个故障)。评估了在 1%、5%和 10% rpm 测量噪声下检测故障条件的能力。所有故障模式都影响了 VAD rpm 对电机电流阶跃的响应。即使在 10%的 rpm 测量噪声下,AF 和 CF VAD 的故障检测率也>95%。血液粘度(3.5-6.2 cP)显著改变了 VAD rpm 响应,这在临床应用中应加以考虑。所提出的 VAD 故障检测算法可能提供一种方便且非侵入性的方法,以最大限度地降低灾难性的设备故障。