The invention relates to the technical field of
image analysis, in particular to an
anesthesia post-operation
pain assessment method in combination with facial expressions of a patient. An
optical flow method is adopted to analyze pixel motion of a facial image,
optical flow vectors and information points are obtained, and
facial expression changes are quantitatively captured. In view of information point validity differences, facial feature points are screened to reduce
data redundancy. And in consideration of the facial structure difference of the patient, the traction characteristics of the
optical flow vector are analyzed, and the traction direction of the image block is determined. Pain expressions such as eye
eyebrow closeness and the like can be represented by the traction direction. By analyzing the distribution
confusion degree and difference in the traction direction, the facial pain index is determined, and accurate reference is provided for
pain assessment. And finally, screening a
data set based on the facial images of multiple patients and pain indexes, training a neural network, and establishing a mapping relation between facial expressions and pain degrees. According to the method, the
pain assessment accuracy is improved, the assessment efficiency is also remarkably improved, and automatic pain assessment of the facial image of the patient to be tested is realized.