The invention discloses an
intelligent control method for an analgesia pump based on
deep learning. The
intelligent control method comprises the following steps: S1, acquiring multi-
modal original signals of a postoperative patient and synchronously normalizing the multi-
modal original signals; s2, removing artifacts and
noise in the synchronous data, and performing interpolation compensation on
missing data; s3, carrying out
modal reliability
weight distribution on the sensing sequence based on a Hemma optimization
algorithm; s4, inputting the node set into a PainNet relation statistical network to generate a dynamic graph topological structure; s5, predicting the pain
score of the patient in the future, and generating a low-
dose high-frequency micro-pulse administration instruction; s6, according to the
circadian rhythm of the patient, dynamically adjusting the edge weight and the administration interval of the PainNet network; and S7, when the pain
score fluctuation exceeds the limit, triggering an emergency mode, quickly converging to the most conservative parameter combination, and outputting a safety locking instruction. According to the invention, the control accuracy and safety of postoperative analgesia are improved.