Lower limb exoskeleton system with actively adjustable leg rod length and control method of lower limb exoskeleton system with actively adjustable leg rod length

Abstract

The invention relates to a lower limb exoskeleton system with actively adjustable leg rod length and a control method of the lower limb exoskeleton system with the actively adjustable leg rod length,and belongs to the technical field of wearable robots. The control method comprises the steps that according to parameter detection data representing that the lower limb exoskeleton system is in an action state, a thigh rod unit and a shank rod unit are controlled to adjust the leg rod lengths of the thigh rod unit and the shank rod unit until the position deviation between the joint rotation center position of the lower limb exoskeleton system and the lower limb joint rotation center position of a wearer is compensated. According to the control method of the lower limb exoskeleton system withthe actively adjustable leg rod length, the use safety is improved while the wearing comfort can be effectively improved, and the control method of the lower limb exoskeleton system with the activelyadjustable leg rod length can be widely applied to rehabilitation training of patients with lower limb weakness or hemiplegia or walking assistance of old people.

Description

technical field [0001] The invention relates to wearable robots and the field thereof, in particular to a lower extremity exoskeleton system with an actively adjustable leg rod length and a control method thereof. Background technique [0002] With the aging of the population, the number of stroke patients continues to increase; in addition, spinal cord injuries caused by traffic accidents, sports injuries and other injury factors are on the rise. Therefore, early rehabilitation training for patients is becoming more and more important. The more attention it receives, the mainstream is to use the plasticity of the central nervous system to make the affected side respond accordingly through exercise training, improve muscle tension, and establish a new combination of the nervous system. However, relying on the experience of physical therapists to perform manual rehabilitation training on patients is not only inefficient, but also unsatisfactory. The use of the lower extremit...

AI Technical Summary

Problems solved by technology

[0005] By arranging the thigh bar and the calf bar in an adjustable length structure, the adaptation range of the lower extremity exoskeleton to the wearer's height can be effectively improved, and the cost can be effectively reduced; It is generally approximated as a hinge joint, and most exoskeleton designs approximate the flexion / extension of the hip joint and knee joint as a single-degree-of-freedom fixed-axis rotation hinge joint. The difference in the movement mechanism of the exoskeleton joints causes the relative movement between the human leg and the exoskeleton leg bar, and in the process of walking, there is a problem that the center position of the joint does not match. The positional deviation between them can reach the order of 10 mm. Because it is relatively small, it is ignored in the design of the existing exoskeleton because of the softness of human skin tissue. The binding between human legs is tight, and the small displacement difference will bring greater interference force. Long-term reciprocation will cause damage to the soft tissue of the lower limb joints, especially the limb sensory ability of patients with paralysis of the lower limbs. It is difficult to feel these negative effects, and there are large negative effects

[0006] In addition, when the exoskeleton system assists the wearer to move, the timing of driving the thigh bar to swing is judged based on the detection data of the pose detection sensor fixed on the thigh bar. Misjudgment of the impact of noise, resulting in uncoordinated movement between the walker and the human body

[0007] Aiming at the above-mentioned uncoordinated movement problem, the current solution is to collect the human muscle electrical signal and combine the adaptive oscillator algorithm to predict the quasi-periodic gait trajectory, so as to realize the precise assistance of the robot to the human hip joint; although this method can predict Eliminate the power-assist delay, but there are certain requirements for the periodicity of walking. When the wearer frequently changes the walking rhythm, the timing of the power-assist is disordered and affects coordination due to the inability to accurately predict it.

Or the phase angle oscillator can be used to accurately identify the corresponding gait phase of the human body in each walking cycle, so as to achieve accurate power-assisted control of the corresponding gait phase, but it can only be calculated in the current state after the joint angle is detected by the attitude sensor. The power assist value does not have a predictive function, and the power assist is still affected by the delay and there is a sense of lag

Images