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.
Aiming at the status of muscle and joint damage caused on surgeons keeping surgical posture for a long time, this paper designs a medical multi-position auxiliary support exoskeleton with multi-joint mechanism by analyzing the surgical postures and conducting conformational studies on different joints respectively. Then by establishing a human-machine static model, this study obtains the joint torque and joint force before and after the human body wears the exoskeleton, and calibrates the strength of the exoskeleton with finite element analysis software. The results show that the maximum stress of the exoskeleton is less than the material strength requirements, the overall deformation is small, and the structural strength of the exoskeleton meets the use requirements. Finally, in this study, subjects were selected to participate in the plantar pressure test and biomechanical simulation with the man-machine static model, and the results were analyzed in terms of plantar pressure, joint torque and joint force, muscle force and overall muscle metabolism to assess the exoskeleton support performance. The results show that the exoskeleton has better support for the whole body and can reduce the musculoskeletal burden. The exoskeleton mechanism in this study better matches the actual working needs of surgeons and provides a new paradigm for the design of medical support exoskeleton mechanism.
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.
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.
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.
Objective To explore the effect of smart powered hip exoskeleton-assisted gait training on lower limb motor function in stroke patients. Methods Stroke patients hospitalized at the China Rehabilitation Research Center (Beijing Bo’ai Hospital) between December 2023 and March 2025 were enrolled. The patients were randomly assigned to either the exoskeleton group or the conventional gait training group (control group). All patients received conventional rehabilitation therapy, including occupational therapy and physiotherapy. Additionally, the exoskeleton group underwent gait training with a smart hip-powered exoskeleton. The control group received conventional gait training using traditional rehabilitation methods. Functional assessments were conducted before treatment, after 2 weeks and 4 weeks of treatment using the following scales: Fugl-Meyer Assessment Scale for Lower Extremity (FMA-LE), Fugl-Meyer Balance Assessment Scale (FMA-B), Modified Ashworth Scale (MAS), 6-Minute Walk Test, Modified Barthel Index (MBI). Patients in the exoskeleton group underwent subjective satisfaction assessment after 4 weeks of treatment. Results A total of 29 patients were included. Among them, there were 15 cases in the exoskeleton group and 14 cases in the control group. There was no statistically significant difference in gender, age, stroke type, disease duration, and hemiplegic side between the two groups (P>0.05). There was no statistically significant difference in motor function indicators between the two groups before and after treatment (P>0.05). After 4 weeks of treatment, FMA-LE, FMA-B, and MBI scores in both groups were higher than before treatment (P<0.05). After 2 weeks of treatment, the FMA-LE score in the foreign group showed an improvement (P<0.05), while the control group showed an improvement until 4 weeks later (P<0.05). After 2 weeks of treatment, there was a statistically significant difference in the improvement rate of FMA-LE between the two groups (Z=?2.076, P=0.041). After 4 weeks of treatment, the subjective satisfaction of patients in the exoskeleton group was relatively high, with an average score of 33.07±4.96. Conclusions Smart powered hip exoskeleton-assisted gait training combined with conventional rehabilitation can improve lower limb motor function, balance, activities of daily living, and walking capacity in post-stroke patients. The exoskeleton demonstrated superior efficacy in enhancing lower limb function compared to conventional training. Patients demonstrated high acceptance of the exoskeleton-assisted gait training in terms of safety and comfort.
With the breakthroughs of digitization, artificial intelligence and other technologies and the gradual expansion of application fields, more and more studies have been conducted on the application of digital intelligence technologies such as exoskeleton robots, brain-computer interface, and spinal cord neuromodulation to improve or compensate physical function after spinal cord injury (SCI) and improve self-care ability and quality of life of patients with SCI. The development of digital intelligent rehabilitation technology provides a new application platform for the functional reconstruction after SCI, and the digital and intelligentized rehabilitation technology has broad application prospects in the clinical rehabilitation treatment after SCI. This article elaborates on the current status of exoskeleton robots, brain-computer interface technology, and spinal cord neuromodulation technology for functional recovery after SCI.
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.
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.
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.
