Abstract:
OBJECTIVE To analyze the differences in gait features between patients with cardiovascular and cerebrovascular diseases and normal people, and to explore new objective features of traditional Chinese medicine (TCM) whole-body inspection.
METHODS A monocular camera was used to collect frontal walking videos of subjects, and the diagnosis results of TCM practitioners were used as disease annotation data; a deep learning model was used to estimate the three-dimensional coordinates of key points; the gait features were defined and calculated based on the three-dimensional coordinates of key points of the lower limbs; differences in gait features among people with cardiovascular and cerebrovascular diseases were collected and verified.
RESULTS The three-dimensional coordinates of key points of the lower limbs were automatically extracted and 8 types of TCM gait features were calculated: step width, stride length, foot lift height, limb angle, left and right hip joint angles, and left and right knee joint angles. It was found that there were significant differences in the features between people with cardiovascular and cerebrovascular diseases and healthy people (P < 0.05).
CONCLUSION The TCM inspection gait extracted by this study can effectively distinguish patients with cardiovascular and cerebrovascular diseases from healthy people, expands the research scope of TCM whole-body inspection, and provides new ideas for the early detection and prevention of cardiovascular and cerebrovascular diseases.
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