The invention discloses an intelligent artificial limb movement intention recognition method based on multi-
modal information and a D-S evidence theory, and belongs to the technical field of
artificial intelligence, mode recognition and intelligent artificial limb control. According to the method, firstly, electromyographic signals and
kinematics signals of user limbs and three-dimensional
point cloud information of the
terrain where the user limbs are located are synchronously collected; filtering, segmenting and
time domain /
frequency domain feature extraction are carried out on the physiological signals, rotation correction and dimension reduction are carried out on the environment
point cloud, and a
binary image is generated; using a
deep learning model to identify a preliminary
motion mode from the physiological features and identify a
terrain category from the environment image; and finally, inputting the two recognition results as evidence bodies into an improved D-S evidence
theory model for decision-
level fusion, and outputting a final comprehensive motion intention recognition result. According to the method, the human physiological
signal and the external environment information are fused, so that the
ambiguity and uncertainty of single information source identification are effectively solved, and the intention identification accuracy and adaptability of the intelligent artificial limb in different complex scenes are remarkably improved.