Annu Int Conf IEEE Eng Med Biol Soc. 2022 Jul;2022:962-965. doi: 10.1109/EMBC48229.2022.9871166.
Supervision of mechanical ventilation is currently still performed by clinical staff. With the increasing level of automation in the intensive care unit, automatic supervision is becoming necessary. We present a fuzzy-based expert supervision system applicable to automatic feedback control of oxygenation. An adaptive fuzzy limit checking and trend detection algorithm was implemented. A knowledge-based fuzzy logic system combines these outputs into a final score, which subsequently triggers alarms if a critical event is registered. The system was evaluated against annotated experimental data. An accuracy of 83 percent and a precision of 95 percent were achieved. The automatic detection of critical events during feedback control of oxygenation provides an additional layer of safety and assists in alerting clinicians in the case of abnormal behavior of the system. Clinical relevance - Automatic supervision is a necessary feature of physiological feedback systems to make them safer and more reliable in the future.
目前，机械通气的监护仍由临床医护人员来执行。随着重症监护病房自动化程度的不断提高，自动监护变得非常必要。我们提出了一种基于模糊逻辑的专家监护系统，适用于氧合的自动反馈控制。实现了自适应模糊限检查和趋势检测算法。基于知识的模糊逻辑系统将这些输出组合成一个最终分数，如果检测到关键事件，则会触发警报。该系统是根据标注的实验数据进行评估的。在氧合的反馈控制过程中，关键事件的自动检测为安全性提供了额外的保障，并在系统出现异常行为时协助临床医生发出警报。临床意义——自动监护是生理反馈系统的必要特征，以使它们在未来更安全、更可靠。
