A Physiological Control System for Pulsatile Ventricular Assist Device Using an Energy-Efficient Deep Reinforcement Learning Method-Reference-Cited by-同舟云学术

A Physiological Control System for Pulsatile Ventricular Assist Device Using an Energy-Efficient Deep Reinforcement Learning Method

Published:2023 Issue: Volume:72 Page:1-10
ISSN:0018-9456
Container-title:IEEE Transactions on Instrumentation and Measurement
language:
Short-container-title:IEEE Trans. Instrum. Meas.

Author:

Li Te¹^ORCID,Cui Wenbo¹^ORCID,Liu Xingjian¹^ORCID,Li Xu¹^ORCID,Xie Nan¹^ORCID,Wang Yongqing¹^ORCID

Affiliation:

1. State Key Laboratory of High-performance Precision Manufacturing and the School of Mechanical Engineering, Dalian University of Technology, Dalian, China

Funder

National Key Research and Development Project

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Foundation of State Key Laboratory of Digital Manufacturing Equipment and Technology

Young Elite Scientists Sponsorship Program by CAST

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/19/10012124/10130059.pdf?arnumber=10130059

Reference37 articles.

1. Supervised Adaptive Fuzzy Control of LVAD with Pulsatility Ratio Modulation

2. Kernel based progressive distillation for adder neural networks;xu;Proc Adv Neural Inf Process Syst,2020

3. Controller Design for Left Ventricular Assist Devices in Patients with Heart Failure

4. AdderNet and its minimalist hardware design for energy-efficient artificial intelligence;wang;arXiv 2101 10015,2021

5. A physiological control system for ECG-synchronized pulsatile pediatric ventricular assist devices

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