Expert knowledge-based strategies for ventilator parameter setting and stepless adaptive adjustment / 生物医学工程学杂志
Journal of Biomedical Engineering
; (6): 945-952, 2023.
Article
en Zh
| WPRIM
| ID: wpr-1008920
Biblioteca responsable:
WPRO
ABSTRACT
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.
Palabras clave
Texto completo:
1
Base de datos:
WPRIM
Asunto principal:
Respiración Artificial
/
Ventiladores Mecánicos
/
Redes Neurales de la Computación
Límite:
Humans
Idioma:
Zh
Revista:
Journal of Biomedical Engineering
Año:
2023
Tipo del documento:
Article
Pais de publicación:
CHINA
/
CN
/
REPUBLIC OF CHINA