The application discloses a
cognitive impairment recognition method based on natural behavior analysis, comprising the following steps: S1, video acquisition and individual separation, real-time acquisition of activity scene video
stream, detection of the boundary box of all human bodies, and cross-frame tracking of the detected
human body target; S2, natural behavior
feature extraction, posture
estimation, expression recognition, social interaction analysis and task participation analysis are carried out, and after all the features are normalized, the fixed-length feature vectors are packaged and uploaded to the cloud; S3, mapping of behavior features to cognitive dimensions, the cloud receives the
time sequence feature flow of each
human body target, calls the pre-trained multi-
level mapping model to perform
time sequence coding, attention fusion, cognitive dimension decoding,
risk identification and suggestion generation; S4, result storage and display, the
risk identification result and the suggestion of each time are stored into a
time sequence database, and a personal
cognitive health atlas is constructed. The application can realize high ecological validity, low cost, high acceptance and fine early screening.