Lower limb gait prediction method based on attitude sensor and motion capture template data

Abstract

The invention relates to the field of mode recognition, in particular to a lower limb gait prediction method based on an attitude sensor and motion capture template data. The method comprises the following steps: firstly, collecting Euler angle data of the thigh, the shank and the foot on the right side of a human body in a walking process, and taking a corresponding relationship of the Euler angle data in a gait period as motion capture template data; obtaining the Euler angle of the thigh on the right side in real time through the attitude sensor; based on the Euler angle of the thigh on the right side and the motion capture template data, obtaining Euler angles, corresponding to the current right thigh angle, of the shank and the foot on the right side, and storing the Euler angles as right real-time motion capture template data; obtaining Euler angles of the thigh, the shank and the foot on the left side according to the right real-time motion capture template data based on the phase corresponding relation of the left and right legs; and predicting motion of lower limbs in real time through the Euler angle data of the thighs, the shanks and the feet on the left side and the right side. According to the method, the position information of the main parts of the lower limbs is obtained through one attitude sensor, the whole gait process is predicted, and the mode recognition cost is reduced.

Description

technical field [0001] The invention relates to the field of pattern recognition, in particular to a lower limb gait prediction method based on posture sensors and motion capture template data, which can be used to reasonably predict the postures of other parts of the lower limbs when a single posture sensor is used. Background technique [0002] The control of various human assistive devices such as exoskeletons, rehabilitation equipment, and smart prosthetics requires lower limb-based motion. Recognizing the movements of the lower limbs based on the data of a variety of sensors is of great significance to the control of various peripheral devices of the human body and the evaluation of the movement of the human body. [0003] Plantar pressure sensors are inexpensive and can be easily integrated into the soles of shoes. The detection of heel strike and toe-off using plantar pressure can effectively divide the gait cycle. The posture sensor integrated with the inertial mea...

AI Technical Summary

Problems solved by technology

Too many attitude sensors will increase the complexity of wearing the recognition system and greatly increase its cost

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