A motion intention recognition and device method for lower extremity exoskeleton

Abstract

A movement intention recognition and device method for lower limb exoskeleton, belonging to the field of lower limb exoskeleton robot sensing technology. The movement intention recognition device includes a lower limb electromyographic signal acquisition module, a plantar pressure acquisition module, a lower limb inertial information measurement module, a data acquisition and transmission module and a central controller. The method uses one-to-one SVM multi-classification to obtain an offline database gait trajectory based on plantar pressure signals, uses a CNN online joint angle estimation model to obtain a real-time prediction trajectory of joint angles based on myoelectric signals, and combines the two types of gait trajectories based on the degree of muscle fatigue. The trajectory is fused with variable gain information to provide an accurate desired motion trajectory for the lower limb joint drive of the exoskeleton robot. The invention effectively combines the advance of the electromyographic signal and the stability of the plantar pressure signal, greatly improves the accuracy and real-time performance of movement intention recognition, and provides sufficient guarantee for the safety and power-assisted efficiency of the exoskeleton robot. ensure.

Description

technical field [0001] The invention belongs to the technical field of lower limb exoskeleton robot perception, and in particular relates to a device and method for recognizing motion intentions of a lower limb exoskeleton robot. Background technique [0002] With the rapid development of modern science and technology, the level of weapons and equipment has increasingly become an important guarantee for the victory of modern warfare, and the status of individual combat exoskeletons in military struggles has gradually increased. At the same time, the problem of aging in modern society is becoming more and more serious. Inconvenience in legs and feet is one of the serious problems in the lives of the elderly. Light-weight walking exoskeletons are of great significance to improving the quality of life of the elderly. [0003] As a typical human-machine collaborative robot, exoskeleton robots can accurately and quickly recognize human motion intentions. Figure 1 has been a majo...

AI Technical Summary

Problems solved by technology

At present, there are three main methods of motion intention recognition applied to lower extremity exoskeleton robots: 1. Gait phase recognition based on plantar pressure. The use of compliant control algorithms cannot recognize different road conditions and different sports actions; 2. Sports intention recognition based on surface electromyography signals (sEMG). There is too much motion information inside, and the current technology mainly focuses on muscle activation, and the recognition model is relatively complicated; 3. Human motion intention recognition based on force sensors, which detect the interaction force between the human body and the exoskeleton through the force sensor, and compare the interaction force according to the magnitude of the interaction force The recognition effect of human motion intention is better, but the multi-dimensional force sensor is expensive and bulky, so it needs to be fixed on the exoskeleton robot, which increases the cost

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