Your browser doesn't support javascript.
loading
Suction detection and suction suppression of centrifugal blood pump based on the FFT-GAPSO-LSTM model and speed modulation.
Liu, Xin; Qu, Hongyi; Huang, Chuangxin; Meng, Lingwei; Chen, Qi; Wang, Qiuliang.
Afiliação
  • Liu X; Ganjiang Innovation Academy, Chinese Academy of Sciences, Ganzhou, Jiangxi Province, 341000, China.
  • Qu H; Department of Automation, University of Science and Technology of China, Hefei 230026, China.
  • Huang C; Ganjiang Innovation Academy, Chinese Academy of Sciences, Ganzhou, Jiangxi Province, 341000, China.
  • Meng L; Institute of Electrical Engineering, Chinese Academy of Sciences, Beijing, 100190, China.
  • Chen Q; Ganjiang Innovation Academy, Chinese Academy of Sciences, Ganzhou, Jiangxi Province, 341000, China.
  • Wang Q; Department of Automation, University of Science and Technology of China, Hefei 230026, China.
Heliyon ; 10(4): e25992, 2024 Feb 29.
Article em En | MEDLINE | ID: mdl-38370170
ABSTRACT
Centrifugal blood pumps are important devices used to treat heart failure. However, they are prone to high-risk suction events that pose a threat to human health when operating at high speeds. To address these issues, a normal suction detection method and a suction suppression method based on the FFT-GAPSO-LSTM model and speed modulation were proposed. The innovation of this suction detection method lies in the application of the genetic particle swarm optimisation (GAPSO) and the fast Fourier transform (FFT) feature extraction method to the long-term and short-term memory (LSTM) model, thereby improving the accuracy of suction detection. After detecting signs of suction, the suction suppression method designed in this study based on variable-speed modulation immediately takes effect, enabling the centrifugal blood pump to quickly return to its normal state by controlling the speed. The suction detection method was divided into four steps. First, a mathematical model of the coupling of the cardiovascular system and the centrifugal blood pump was established, and a real-time blood flow curve was obtained through model simulation. Second, the signal was preprocessed by adding Gaussian white noise and low-pass filtering to make the blood flow signal close to actual working conditions while retaining the original characteristics. Subsequently, through fast Fourier transform (FFT) analysis of the processed curve, the spectral characteristics that can characterise the working state of the centrifugal blood pump were extracted. Finally, the parameters of the LSTM model were optimised using the GAPSO, and the improved LSTM model was used to train and test the blood flow spectrum feature set. The results show that the suction detection method of the FFT-GAPSO-LSTM model can effectively detect whether centrifugal blood pump suction occurs and has certain advantages over other methods. In addition, the simulation results of the suction suppression were excellent and could effectively suppress the occurrence of suction. These results provide a reference for the design of centrifugal blood pump control systems.
Palavras-chave

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article