Exoskeleton nursing robot is a typical human-machine co-drive system. To full play the subjective control and action orientation of human, it is necessary to comprehensively analyze exoskeleton wearer's surface electromyography (EMG) in the process of moving patients, especially identifying the spatial distribution and internal relationship of the EMG information. Aiming at the location of electrodes and internal relation between EMG channels, the complex muscle system at the upper limb was abstracted as a muscle functional network. Firstly, the correlation characteristics were analyzed among EMG channels of the upper limb using the mutual information method, so that the muscle function network was established. Secondly, by calculating the characteristic index of network node, the features of muscle function network were analyzed for different movements. Finally, the node contraction method was applied to determine the key muscle group that reflected the intention of wearer's movement, and the characteristics of muscle function network were analyzed in each stage of moving patients. Experimental results showed that the location of the myoelectric collection could be determined quickly and efficiently, and also various stages of the moving process could effectively be distinguished using the muscle functional network with the key muscle groups. This study provides new ideas and methods to decode the relationship between neural controls of upper limb and physical motion.
Electromyography ; Exoskeleton Device ; Humans ; Muscle, Skeletal ; physiology ; Robotics ; Upper Extremity

The purpose of this paper was to investigate the effects of wearable lower limb exoskeletons on the kinematics and kinetic parameters of the lower extremity joints and muscles during normal walking, aiming to provide scientific basis for optimizing its structural design and improving its system performance. We collected the walking data of subjects without lower limb exoskeleton and selected the joint angles in sagittal plane of human lower limbs as driving data for lower limb exoskeleton simulation analysis. Anybody (the human biomechanical analysis software) was used to establish the human body model (the human body model without lower limb exoskeleton) and the man-machine system model (the lower limb exoskeleton model). The kinematics parameters (joint force and joint moment) and muscle parameters (muscle strength, muscle activation, muscle contraction velocity and muscle length) under two situations were compared. The experimental result shows that walking gait after wearing the lower limb exoskeleton meets the normal gait, but there would be an occasional and sudden increase in muscle strength. The max activation level of main lower limb muscles were all not exceeding 1, in another word the muscles did not appear fatigue and injury. The highest increase activation level occurred in rectus femoris (0.456), and the lowest increase activation level occurred in semitendinosus (0.013), which means the lower limb exoskeletons could lead to the fatigue and injury of semitendinosus. The results of this study illustrate that to avoid the phenomenon of sudden increase of individual muscle force, the consistency between the length of body segment and the length of exoskeleton rod should be considered in the design of lower limb exoskeleton extremity.
Biomechanical Phenomena ; Exoskeleton Device ; Gait ; Humans ; Lower Extremity ; physiology

In order to improve the motion fluency and coordination of lower extremity exoskeleton robots and wearers, a pace recognition method of exoskeleton wearer is proposed base on inertial sensors. Firstly, the triaxial acceleration and triaxial angular velocity signals at the thigh and calf were collected by inertial sensors. Then the signal segment of 0.5 seconds before the current time was extracted by the time window method. And the Fourier transform coefficients in the frequency domain signal were used as eigenvalues. Then the support vector machine (SVM) and hidden Markov model (HMM) were combined as a classification model, which was trained and tested for pace recognition. Finally, the pace change rule and the human-machine interaction force were combined in this model and the current pace was predicted by the model. The experimental results showed that the pace intention of the lower extremity exoskeleton wearer could be effectively identified by the method proposed in this article. And the recognition rate of the seven pace patterns could reach 92.14%. It provides a new way for the smooth control of the exoskeleton.
Algorithms ; Exoskeleton Device ; Humans ; Lower Extremity ; Motion ; Support Vector Machine

At present, most of the research on hip exoskeleton robots adopts the method of decoupling analysis of hip joint motion, decoupling the ball pair motion of hip joint into rotational motion on sagittal plane, coronal plane and cross section, and designing it into series mechanism. Aiming at the problems of error accumulation and man-machine coupling in series mechanism, a parallel hip rehabilitation exoskeleton structure is proposed based on the bionic analysis of human hip joint. The structure model is established and the kinematics analysis is carried out. Through the OpenSim software, the curve of hip flexion and extension, adduction and abduction angle in a gait cycle is obtained. The inverse solution of the structure is obtained by the D-H coordinate system method. The gait data points are selected and compared with the inverse solution obtained by ADAMS software simulation. The results show that the inverse solution expression is correct. The parallel hip exoskeleton structure can meet the requirements of the rotation angle of the hip joint of the human body, and can basically achieve the movement of the hip joint, which is helpful to improve the human-computer interaction performance of the exoskeleton.
Humans ; Exoskeleton Device ; Hip Joint ; Gait ; Biomechanical Phenomena ; Computer Simulation

Aiming at the human-computer interaction problem during the movement of the rehabilitation exoskeleton robot, this paper proposes an adaptive human-computer interaction control method based on real-time monitoring of human muscle state. Considering the efficiency of patient health monitoring and rehabilitation training, a new fatigue assessment algorithm was proposed. The method fully combined the human neuromuscular model, and used the relationship between the model parameter changes and the muscle state to achieve the classification of muscle fatigue state on the premise of ensuring the accuracy of the fatigue trend. In order to ensure the safety of human-computer interaction, a variable impedance control algorithm with this algorithm as the supervision link was proposed. On the basis of not adding redundant sensors, the evaluation algorithm was used as the perceptual decision-making link of the control system to monitor the muscle state in real time and carry out the robot control of fault-tolerant mechanism decision-making, so as to achieve the purpose of improving wearing comfort and improving the efficiency of rehabilitation training. Experiments show that the proposed human-computer interaction control method is effective and universal, and has broad application prospects.
Humans ; Exoskeleton Device ; Muscle Fatigue ; Muscles ; Algorithms ; Electric Impedance

In order to improve the wearing comfort and bearing effectiveness of the exoskeleton, based on the prototype and working mechanism analysis of a relaxation wearable system for knee exoskeleton robot, the static optimization synthesis and its method are studied. Firstly, based on the construction of the virtual prototype model of the system, a comprehensive wearable comfort evaluation index considering the factors such as stress, deformation and the proportion of stress nodes was constructed. Secondly, based on the static simulation and evaluation index of system virtual prototype, multi-objective genetic optimization and local optimization synthesis of armor layer topology were carried out. Finally, the model reconstruction simulation data confirmed that the system had good wearing comfort. Our study provides a theoretical basis for the bearing performance and prototype construction of the subsequent wearable system.
Humans ; Exoskeleton Device ; Computer Simulation ; Emotions ; Knee Joint

Based on the structure and motion bionic principle of the normal adult fingers, biological characteristics of human hands were analyzed, and a wearable exoskeleton hand function training device for the rehabilitation of stroke patients or patients with hand trauma was designed. This device includes the exoskeleton mechanical structure and the electromyography (EMG) control system. With adjustable mechanism, the device was capable to fit different finger lengths, and by capturing the EMG of the users' contralateral limb, the motion state of the exoskeleton hand was controlled. Then driven by the device, the user's fingers conducting adduction/abduction rehabilitation training was carried out. Finally, the mechanical properties and training effect of the exoskeleton hand were verified through mechanism simulation and the experiments on the experimental prototype of the wearable exoskeleton hand function training device.
Bionics ; instrumentation ; Electromyography ; Exoskeleton Device ; Fingers ; Hand ; Humans ; Motion ; Stroke Rehabilitation

Based on the biomechanical mechanism of human upper limb, the disadvantages of traditional rehabilitation training and the current status of upper limb rehabilitation robot, a six degree of freedom, flexible adjustment, wearable upper limb rehabilitation exoskeleton design scheme is proposed. Firstly, the mechanics of each joint of the upper limb is analyzed, and the virtual prototype design of the whole mechanical structure of the upper limb rehabilitation wearable exoskeleton is carried out by using CATIA three-dimensional software. The tooth transmission of the forearm and the upper arm single row four point contact ball bearing with internal/external rotation and the shoulder flexible passive adjustment mechanism (viscoelastic damper) are innovatively designed. Then, the joints of the upper limb rehabilitation exoskeleton are analyzed, theoretical analysis and calculation of the driving torque, the selection of the motor and gearbox of each driving joint are carried out. Finally, the whole finite element analysis of the upper limb exoskeleton is carried out. The research and experimental results showed that the design scheme of the upper limb exoskeleton assist structure is highly feasible, which can help the patients with upper limb paralysis and motor dysfunction self-rehabilitation.
Biomechanical Phenomena ; Exoskeleton Device ; Humans ; Robotics ; Stroke Rehabilitation ; Torque ; Upper Extremity ; Wearable Electronic Devices

Based on the biomechanical simulation curve of OpenSim, an open source software of biomechanical model, a spherical exoskeleton parallel mechanism with two degrees of freedom for hip joint is proposed in this paper for the rehabilitation therapy of patients with impaired leg motor function or elderly people with walking dysfunction. Firstly, the parallel mechanism is modeled and the position inverse solution of the parallel mechanism is obtained using inverse kinematics analysis. The velocity analysis expression of the mechanism is derived by deriving the inverse kinematics solution. The model is imported into the mechanical system dynamics analysis software ADAMS and matrix processing analysis software MATLAB to carry out simulation experiments. The correctness of the velocity analysis is verified by comparing the velocity simulation results of the two methods. Then, three singular types of the mechanism are analyzed according to the obtained Jacobian matrix. According to the inverse solution of the mechanism, the reachable workspace of the mechanism is obtained by programming in MATLAB with given mechanism parameters and restriction conditions. Finally, the prototype platform is built. The experimental results show that the exoskeleton hip joint using this parallel mechanism can satisfy the requirement of rotation angle of human hip joint movement, but also can be good to assist patients with leg flexion-extension movement and adduction-abduction movement, and it is helpful to carry out corresponding rehabilitation training. It also has theoretical significance and application value for the research work of human hip exoskeleton parallel mechanism.
Biomechanical Phenomena ; Exoskeleton Device ; Hip Joint ; physiology ; Humans ; Models, Theoretical ; Movement ; Rehabilitation ; instrumentation ; Rotation ; Walking

In response to the problem that the traditional lower limb rehabilitation scale assessment method is time-consuming and difficult to use in exoskeleton rehabilitation training, this paper proposes a quantitative assessment method for lower limb walking ability based on lower limb exoskeleton robot training with multimodal synergistic information fusion. The method significantly improves the efficiency and reliability of the rehabilitation assessment process by introducing quantitative synergistic indicators fusing electrophysiological and kinematic level information. First, electromyographic and kinematic data of the lower extremity were collected from subjects trained to walk wearing an exoskeleton. Then, based on muscle synergy theory, a synergistic quantification algorithm was used to construct synergistic index features of electromyography and kinematics. Finally, the electrophysiological and kinematic level information was fused to build a modal feature fusion model and output the lower limb motor function score. The experimental results showed that the correlation coefficients of the constructed synergistic features of electromyography and kinematics with the clinical scale were 0.799 and 0.825, respectively. The results of the fused synergistic features in the K-nearest neighbor (KNN) model yielded higher correlation coefficients ( r = 0.921, P < 0.01). This method can modify the rehabilitation training mode of the exoskeleton robot according to the assessment results, which provides a basis for the synchronized assessment-training mode of "human in the loop" and provides a potential method for remote rehabilitation training and assessment of the lower extremity.
Humans ; Exoskeleton Device ; Reproducibility of Results ; Walking/physiology* ; Lower Extremity ; Algorithms ; Stroke Rehabilitation/methods*