A Novel Method to Evaluate Patient-Ventilator Synchrony during Mechanical Ventilation
Liming Hao,
Shuai Ren,
Yan Shi,
Na Wang,
Yixuan Wang,
Zujin Luo,
Fei Xie,
Meng Xu,
Jian Zhang,
Maolin Cai
Affiliations
Liming Hao
School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China
Shuai Ren
School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China
Yan Shi
School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China
Na Wang
School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China
Yixuan Wang
School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China
Zujin Luo
Department of Respiratory and Critical Care Medicine, Beijing Engineering Research Center of Respiratory and Critical Care Medicine, Beijing Institute of Respiratory Medicine, Beijing Chao-Yang Hospital, Capital Medical University, Beijing 100043, China
Fei Xie
Department of Pulmonary and Critical Care Medicine, Chinese PLA General Hospital, Beijing 100039, China
Meng Xu
Department of Orthopedics, Chinese PLA General Hospital, Beijing 100039, China
Jian Zhang
School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China
Maolin Cai
School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China
The synchrony of patient-ventilator interaction affects the process of mechanical ventilation which is clinically applied for respiratory support. The occurrence of patient-ventilator asynchrony (PVA) not only increases the risk of ventilator complications but also affects the comfort of patients. To solve the problem of uncertain patient-ventilator interaction in the mechanical ventilation system, a novel method to evaluate patient-ventilator synchrony is proposed in this article. Firstly, a pneumatic model is established to simulate the mechanical ventilation system, which is verified to be accurate by the experiments. Then, the PVA phenomena are classified and detected based on the analysis of the ventilator waveforms. On this basis, a novel synchrony index SIhao is established to evaluate the patient-ventilator synchrony. It not only solves the defects of previous evaluation indexes but also can be used as the response parameter in the future research of ventilator control algorithms. The accurate evaluation of patient-ventilator synchrony can be applied to the adjustment of clinical strategies and the pathological analyses of patients. This research can also reduce the burden on clinicians and help to realize the adaptive control of the mechanical ventilation and weaning process in the future.