WANG Yongyan 1,2,3 , MA Songhua 1,2,3 , HU Tianliang 1,2,3 , MA Dedong 4,5 , LIAN Xianhui 1,2,3 , WANG Shuai 1,2,3 , ZHANG Jiguo 1,2,3
  • 1. School of Mechanical Engineering, Shandong University, Jinan 250061, P. R. China;
  • 2. Key Laboratory of High Efficiency and Clean Mechanical Manufacture at Shandong University, Ministry of Education, Jinan 250061, P. R. China;
  • 3. National Demonstration Center for Experimental Mechanical Engineering Education, Jinan 250061, P. R. China;
  • 4. Qilu Hospital of Shandong University, Jinan 250012, P. R. China;
  • 5. Key Laboratory of Otolaryngology, Shandong University, Jinan 250012, P. R. China;
MA Songhua, Email: msh_1216@sdu.edu.cn; MA Dedong, Email: ma@qiluhuxi.com
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The setting and adjustment of ventilator parameters need to rely on a large amount of clinical data and rich experience. This paper explored the problem of difficult decision-making of ventilator parameters due to the time-varying and sudden changes of clinical patient’s state, and proposed an expert knowledge-based strategies for ventilator parameter setting and stepless adaptive adjustment based on fuzzy control rule and neural network. Based on the method and the real-time physiological state of clinical patients, we generated a mechanical ventilation decision-making solution set with continuity and smoothness, and automatically provided explicit parameter adjustment suggestions to medical personnel. This method can solve the problems of low control precision and poor dynamic quality of the ventilator’s stepwise adjustment, handle multi-input control decision problems more rationally, and improve ventilation comfort for patients.

Citation: WANG Yongyan, MA Songhua, HU Tianliang, MA Dedong, LIAN Xianhui, WANG Shuai, ZHANG Jiguo. Expert knowledge-based strategies for ventilator parameter setting and stepless adaptive adjustment. Journal of Biomedical Engineering, 2023, 40(5): 945-952. doi: 10.7507/1001-5515.202209015 Copy

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