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.
In order to help the patients with upper-limb disfunction go on rehabilitation training, this paper proposed an upper-limb exoskeleton rehabilitation robot with four degrees of freedom (DOF), and realized two control schemes, i.e., voice control and electromyography control. The hardware and software design of the voice control system was completed based on RSC-4128 chips, which realized the speech recognition technology of a specific person. Besides, this study adapted self-made surface eletromyogram (sEMG) signal extraction electrodes to collect sEMG signals and realized pattern recognition by conducting sEMG signals processing, extracting time domain features and fixed threshold algorithm. In addition, the pulse-width modulation(PWM)algorithm was used to realize the speed adjustment of the system. Voice control and electromyography control experiments were then carried out, and the results showed that the mean recognition rate of the voice control and electromyography control reached 93.1% and 90.9%, respectively. The results proved the feasibility of the control system. This study is expected to lay a theoretical foundation for the further improvement of the control system of the upper-limb rehabilitation robot.
This paper presents a wearable exoskeleton robot system to realize walking assist function, which oriented toward the patients or the elderly with the mild impairment of leg movement function, due to illness or natural aging. It reduces the loads of hip, knee, ankle and leg muscles during walking by way of weight support. In consideration of the characteristics of the psychological demands and the disease, unlike the weight loss system in the fixed or followed rehabilitation robot, the structure of the proposed exoskeleton robot is artistic, lightweight and portable. The exoskeleton system analyzes the user's gait real-timely by the plantar pressure sensors to divide gait phases, and present different control strategies for each gait phase. The pressure sensors in the seat of the exoskeleton system provide real-time monitoring of the support efforts. And the drive control uses proportion-integral-derivative (PID) control technology for torque control. The total weight of the robot system is about 12.5 kg. The average of the auxiliary support is about 10 kg during standing, and it is about 3 kg during walking. The system showed, in the experiments, a certain effect of weight support, and reduction of the pressure on the lower limbs to walk and stand.
The lower extremity exoskeleton robot is a wearable device designed to help people suffering from a walking disorder to regain the power of the legs and joints to achieve standing and walking functions. Compared with traditional robots that include rigid mechanisms, lower extremity exoskeleton robots with compliant characteristics can store and release energy in passive elastic elements while minimizing the reaction force due to impact, so it can improve the safety of human-robot interaction. This paper reviews the compliant characteristics of lower extremity exoskeleton robots from the aspects of compliant drive and compliant joint, and introduces the augmentation, assistive, rehabilitation lower extremity exoskeleton robots. It also prospect the future development trend of lower extremity exoskeleton robots.
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.
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.
In order to reduce the impact caused by the contact between the foot and the ground when wearing the lower extremity exoskeleton under the condition of high load, this paper proposed an exoskeleton foot mechanism for improving the foot comfort, and optimized the key index of its influence on the comfort. Firstly, the physical model of foot mechanism was established based on the characteristics of foot stress in gait period, and then the mathematical model of vibration was abstracted. The correctness of the model was verified by the finite element analysis software ANSYS. Then, this paper analyzed the influence of vibration parameters on absolute transmissibility based on vibration mathematical model, and optimized vibration parameters with MATLAB genetic algorithm toolbox. Finally, this paper took white noise to simulate the road elevation as the vibration input, and used the visual simulation tool Simulink in MATLAB and the vibration equation to construct the acceleration simulation model, and then calculated the vibration weighted root mean square acceleration value of the foot. The results of this study show that this foot comfort mechanism can meet the comfort indexes of vibration absorption and plantar pressure, and this paper provides a relatively complete method for the design of exoskeleton foot mechanism, which has reference significance for the design of other exoskeleton foot and ankle joint rehabilitation mechanism.
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.
Lower limb ankle exoskeletons have been used to improve walking efficiency and assist the elderly and patients with motor dysfunction in daily activities or rehabilitation training, while the assistance patterns may influence the wearer’s lower limb muscle activities and coordination patterns. In this paper, we aim to evaluate the effects of different ankle exoskeleton assistance patterns on wearer’s lower limb muscle activities and coordination patterns. A tethered ankle exoskeleton with nine assistance patterns that combined with differenet actuation timing values and torque magnitude levels was used to assist human walking. Lower limb muscle surface electromyography signals were collected from 7 participants walking on a treadmill at a speed of 1.25 m/s. Results showed that the soleus muscle activities were significantly reduced during assisted walking. In one assistance pattern with peak time in 49% of stride and peak torque at 0.7 N·m/kg, the soleus muscle activity was decreased by (38.5 ± 10.8)%. Compared with actuation timing, the assistance torque magnitude had a more significant influence on soleus muscle activity. In all assistance patterns, the eight lower limb muscle activities could be decomposed to five basic muscle synergies. The muscle synergies changed little under assistance with appropriate actuation timing and torque magnitude. Besides, co-contraction indexs of soleus and tibialis anterior, rectus femoris and semitendinosus under exoskeleton assistance were higher than normal walking. Our results are expected to help to understand how healthy wearers adjust their neuromuscular control mechanisms to adapt to different exoskeleton assistance patterns, and provide reference to select appropriate assistance to improve walking efficiency.
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.