Newborn pain expression recognition method based on dual-channel feature deep learning

Abstract

The invention discloses a newborn pain expression recognition method based on dual-channel feature deep learning. This method first grayscales the facial image of the newborn and extracts the local binary pattern (Local Binary Pattern, LBP) feature map; then uses a two-channel convolutional neural network to process the grayscale image and The features of the two channels of the LBP feature map are used for deep learning; finally, a softmax-based classifier is used to classify the fusion features of the two channels for expression classification, which is divided into four types of expressions: calm, crying, mild pain, and severe pain. Combining the feature information of the two channels of the gray image and its LBP feature map, this method can effectively identify calm, crying, mild pain, severe pain and other expressions, and has a certain effect on the lighting, noise and occlusion problems of newborn facial images. It has good robustness and provides a new method and approach for developing a pain expression recognition system for newborns.

Description

technical field [0001] The invention relates to a newborn pain expression recognition method based on dual-channel feature deep learning, which belongs to the field of image processing and emotion recognition. Background technique [0002] Pain is a common uncomfortable symptom of the human body. It not only makes people suffer, but also brings a series of physiological and psychological adverse effects. Studies have shown that newborns have the ability to feel pain after birth, and can transmit, perceive, respond to and even remember harmful stimuli. Various examinations and treatments received from birth will bring pain and stimulation to newborns. Painful stimuli can cause systemic reactions in the body, such as changes in breathing and immunity, and instability of cardiovascular function; this pain may also lead to long-term effects such as developmental delay in newborns, permanent damage to the central nervous system, and emotional disorders. Early repeated operant p...

AI Technical Summary

Problems solved by technology

[0005] To meet the needs of developing an automatic assessment system for neonatal pain, the present invention provides a newborn pain expression recognition method based on dual-channel feature deep learning, which solves the problem of insufficient feature extraction of neonatal facial expression images by traditional methods, and can not obtain more accurate recognition The results of the problem, open up a new way to provide objective and accurate pain automatic assessment tools for clinical

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