The invention belongs to the technical field of
medical care monitoring, and particularly relates to a urinary
surgery nursing monitoring method combining
the Internet of Things and image recognition. Acquiring multi-source
monitoring data related to urinary
surgery patient
nursing; carrying out preprocessing and region segmentation on the acquired image data; calculating the real-time
urine volume by adopting piecewise linear mapping; constructing a
urine volume
time sequence, predicting a future
urine volume trend by adopting an LSTM model, and performing anomaly identification through prediction errors; a state area of the
catheter is identified by adopting a
convolutional neural network identification model, leakage detection is carried out, the color of urine is analyzed, and a leakage
risk index is calculated; and multi-
modal input is constructed, and a comprehensive
risk index is output. According to the method,
the Internet of Things technology and the image recognition technology are combined to be used for urinary
surgery nursing monitoring, and intelligent monitoring and automatic early warning of the urine bag liquid level,
catheter bending, leakage
diffusion, urine color change, the
urine volume trend and the patient
body movement risk are achieved.