Study on sensorless suction detection method based on the intrinsic parameter of rotary left ventricular assist devices_Journal of Biomedical Engineering

Authors：

PENG Jing ¹ ,  WANG Yu ²

1. School of Biomedical Engineering, Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian, Liaoning 116024, P.R.China;
2. School of Optoelectronic Engineering and Instrumentation Science, Dalian University of Technology, Dalian, Liaoning 116024, P.R.China;

Corresponding author：

WANG Yu, Email: yuwang0410@dlut.edu.cn

Keywords：

left ventricular assist device; suction detection; intrinsic blood pump parameter

DOI：

10.7507/1001-5515.201803077

Video：

Export PDF Favorites Scan Get Citation

Abstract Full text Figures/Tables Video References Cited by

The rotary left ventricular assist device (LVAD) has been an effective option for end-stage heart failure. However, while clinically using the LVAD, patients are often at significant risk for ventricular collapse, called suction, mainly due to higher LVAD speeds required for adequate cardiac output. Some proposed suction detection algorithms required the external implantation of sensors, which were not reliable in long-term use due to baseline drift and short lifespan. Therefore, this study presents a new suction detection system only using the LVAD intrinsic blood pump parameter (pump speed) without using any external sensor. Three feature indices are derived from the pump speed and considered as the inputs to four different classifiers to classify the pumping states as no suction or suction. The in-silico results using a combined human circulatory system and LVAD model show that the proposed method can detect ventricular suction effectively, demonstrating that it has high classification accuracy, stability, and robustness. The proposed suction detection system could be an important part in the LVAD for detecting and avoiding suction, while at the same time making the LVAD meet the cardiac output demand for the patients. It could also provide theoretical basis and technology support for designing and optimizing the control system of the LVAD.

Citation： PENG Jing, WANG Yu. Study on sensorless suction detection method based on the intrinsic parameter of rotary left ventricular assist devices. Journal of Biomedical Engineering, 2019, 36(3): 478-485. doi: 10.7507/1001-5515.201803077 Copy

1.	Mozaffarian D, Benjamin E J, Go A S, et al. Heart disease and stroke statistics--2015 update: a report from the American Heart Association. Circulation, 2015, 131(4): e29-322.
2.	刘维永, 金振晓. 终末期心力衰竭外科治疗的进展与思考. 中华胸心血管外科杂志, 2012, 28(6): 377-380.
3.	Rose E A, Gelijns A C, Moskowita A J, et al. Long-term use of a left ventricular assist device for end-stage heart failure. N Engl J Med, 2001, 345(20): 1435-1443.
4.	Slaughter M S, Bartoli C R, Sobieski M A, et al. Intraoperative evaluation of the HeartMate II flow estimator. J Heart Lung Transplant, 2009, 28(1): 39-43.
5.	Slaughter M S, Rogers J G, Milano C A, et al. Advanced heart failure treated with continuous-flow left ventricular assist device. N Engl J Med, 2009, 361(23): 2241-2251.
6.	Vollkron M, Schima H, Huber L, et al. Development of a suction detection system for axial blood pumps. Artif Organs, 2004, 28(8): 709-716.
7.	Vollkron M, Schima H, Huber L, et al. Advanced suction detection for an axial flow pump. Artif Organs, 2006, 30(9): 665-670.
8.	Vollkron M, Voitl P, Ta J, et al. Suction events during left ventricular support and ventricular arrhythmias. J Heart Lung Transplant, 2007, 26(8): 819-825.
9.	Simaan M A, Ferreira A, Chen S, et al. A dynamical state space representation and performance analysis of a feedback-controlled rotary left ventricular assist device. IEEE Trans Contr Syst Technol, 2009, 17(1): 15-28.
10.	Kitamura T, Matsushima Y, Tokuyama T, et al. Physical model-based indirect measurements of blood pressure and flow using a centrifugal pump. Artif Organs, 2000, 24(8): 589-593.
11.	Giridharan G A, Skliar M. Physiological control of blood pumps using intrinsic pump parameters: a computer simulation study. Artif Organs, 2006, 30(4): 301-307.
12.	Karantonis D M, Lovell N H, Ayre P J, et al. Identification and classification of physiologically significant pumping states in an implantable rotary blood pump. Artif Organs, 2006, 30(9): 671-679.
13.	Ferreira A, CHEN S, Simaan M A, et al. A discriminant-analysis-based suction detection system for rotary blood pumps//Proceedings of the 28th IEEE EMBS Annual International Conference. New York City, USA: IEEE, 2006: 5382-5385.
14.	Karantonis D M, Cloherty S L, Lovell N H, et al. Noninvasive detection of suction in an implantable rotary blood pump using neural networks. Int J Comput Intell Appl, 2008, 7(3): 237-247.
15.	Wang Yu, Simaan M A. A suction detection system for rotary blood pumps based on the Lagrangian support vector machine algorithm. IEEE J Biomed Health Inform, 2013, 17(3): 654-663.
16.	Tzallas A T, Katertsidis N S, Karvounis E C, et al. Modeling and simulation of speed selection on left ventricular assist devices. Comput Biol Med, 2014, 51(1): 128-139.
17.	Faragallah G, Wang Y, Divo E, et al. A new current-based control model of the combined cardiovascular and rotary left ventricular assist device//Proceedings of 2011 American Control Conference. San Francisco, USA: IEEE, 2011: 4775-4780.
18.	Ferreira A, Simaan M A, Boston J R, et al. Frequency and time-frequency based indices for suction detection in rotary blood pumps//Proceedings of IEEE International Conference on Acoustics Speech and Signal Processing. Toulouse, France: IEEE, 2006: 1064-1067.
19.	Viswajith V S, Wang Yu, Simaan M A. Aortic valve dynamics and blood flow control in continuous flow left ventricular assist devices//Proceedings of 2017 American Control Conference. Seattle, USA: IEEE, 2017: 1456-1461.

1. Mozaffarian D, Benjamin E J, Go A S, et al. Heart disease and stroke statistics--2015 update: a report from the American Heart Association. Circulation, 2015, 131(4): e29-322.
2. 刘维永, 金振晓. 终末期心力衰竭外科治疗的进展与思考. 中华胸心血管外科杂志, 2012, 28(6): 377-380.
3. Rose E A, Gelijns A C, Moskowita A J, et al. Long-term use of a left ventricular assist device for end-stage heart failure. N Engl J Med, 2001, 345(20): 1435-1443.
4. Slaughter M S, Bartoli C R, Sobieski M A, et al. Intraoperative evaluation of the HeartMate II flow estimator. J Heart Lung Transplant, 2009, 28(1): 39-43.
5. Slaughter M S, Rogers J G, Milano C A, et al. Advanced heart failure treated with continuous-flow left ventricular assist device. N Engl J Med, 2009, 361(23): 2241-2251.
6. Vollkron M, Schima H, Huber L, et al. Development of a suction detection system for axial blood pumps. Artif Organs, 2004, 28(8): 709-716.
7. Vollkron M, Schima H, Huber L, et al. Advanced suction detection for an axial flow pump. Artif Organs, 2006, 30(9): 665-670.
8. Vollkron M, Voitl P, Ta J, et al. Suction events during left ventricular support and ventricular arrhythmias. J Heart Lung Transplant, 2007, 26(8): 819-825.
9. Simaan M A, Ferreira A, Chen S, et al. A dynamical state space representation and performance analysis of a feedback-controlled rotary left ventricular assist device. IEEE Trans Contr Syst Technol, 2009, 17(1): 15-28.
10. Kitamura T, Matsushima Y, Tokuyama T, et al. Physical model-based indirect measurements of blood pressure and flow using a centrifugal pump. Artif Organs, 2000, 24(8): 589-593.
11. Giridharan G A, Skliar M. Physiological control of blood pumps using intrinsic pump parameters: a computer simulation study. Artif Organs, 2006, 30(4): 301-307.
12. Karantonis D M, Lovell N H, Ayre P J, et al. Identification and classification of physiologically significant pumping states in an implantable rotary blood pump. Artif Organs, 2006, 30(9): 671-679.
13. Ferreira A, CHEN S, Simaan M A, et al. A discriminant-analysis-based suction detection system for rotary blood pumps//Proceedings of the 28th IEEE EMBS Annual International Conference. New York City, USA: IEEE, 2006: 5382-5385.
14. Karantonis D M, Cloherty S L, Lovell N H, et al. Noninvasive detection of suction in an implantable rotary blood pump using neural networks. Int J Comput Intell Appl, 2008, 7(3): 237-247.
15. Wang Yu, Simaan M A. A suction detection system for rotary blood pumps based on the Lagrangian support vector machine algorithm. IEEE J Biomed Health Inform, 2013, 17(3): 654-663.
16. Tzallas A T, Katertsidis N S, Karvounis E C, et al. Modeling and simulation of speed selection on left ventricular assist devices. Comput Biol Med, 2014, 51(1): 128-139.
17. Faragallah G, Wang Y, Divo E, et al. A new current-based control model of the combined cardiovascular and rotary left ventricular assist device//Proceedings of 2011 American Control Conference. San Francisco, USA: IEEE, 2011: 4775-4780.
18. Ferreira A, Simaan M A, Boston J R, et al. Frequency and time-frequency based indices for suction detection in rotary blood pumps//Proceedings of IEEE International Conference on Acoustics Speech and Signal Processing. Toulouse, France: IEEE, 2006: 1064-1067.
19. Viswajith V S, Wang Yu, Simaan M A. Aortic valve dynamics and blood flow control in continuous flow left ventricular assist devices//Proceedings of 2017 American Control Conference. Seattle, USA: IEEE, 2017: 1456-1461.

Journal of Biomedical Engineering

Study on sensorless suction detection method based on the intrinsic parameter of rotary left ventricular assist devices

Abstract Full text Figures/Tables Video References Cited by

Previous Article

Next Article

Format

Content