The motor nervous system transmits motion control information through nervous oscillations, which causes the synchronous oscillatory activity of the corresponding muscle to reflect the motion response information and give the cerebral cortex feedback, so that it can sense the state of the limbs. This synchronous oscillatory activity can reflect connectivity information of electroencephalography-electromyography (EEG-EMG) functional coupling. The strength of the coupling is determined by various factors including the strength of muscle contraction, attention, motion intention etc. It is very significant to study motor functional evaluation and control methods to analyze the changes of EEG-EMG synchronous coupling caused by different factors. This article mainly introduces and compares coherence and Granger causality of linear methods, the mutual information and transfer entropy of nonlinear methods in EEG-EMG synchronous coupling, and summarizes the application of each method, so that researchers in related fields can understand the current research progress on analysis methods of EEG-EMG synchronous systematically.
At present, the upper limb function of stroke patients is often assessed clinically using a scale method, but this method has problems such as time-consuming, poor consistency of assessment results, and high participation of rehabilitation physicians. To overcome the shortcomings of the scale method, intelligent upper limb function assessment systems combining sensors and machine learning algorithms have become one of the hot research topics in recent years. Firstly, the commonly used clinical upper limb functional assessment methods are analyzed and summarized. Then the researches on intelligent assessment systems in recent years are reviewed, focusing on the technologies used in the data acquisition and data processing parts of intelligent assessment systems and their advantages and disadvantages. Lastly, the current challenges and future development directions of intelligent assessment systems are discussed. This review is hoped to provide valuable reference information for researchers in related fields.
Lower limb exoskeleton rehabilitation robots are used to improve or restore the walking and movement ability of people with lower limb movement disorders. However, the required functions for patients differ based on various diseases. For example, patients with weak muscle strength require power assistance, patients with spinal cord injuries require motion compensation, patients with gait abnormalities require gait correction, and patients with strokes require neural rehabilitation. To design a more targeted lower limb exoskeleton rehabilitation robot for different diseases, this article summarised and compared existing lower limb exoskeleton rehabilitation robots according to their main functions and the characteristics and rehabilitation needs of various lower limb movement disorders. The correlations between the functions of existing devices and diseases were summarised to provide certain references for the development of new lower limb exoskeleton rehabilitation robots.
Rapid and accurate recognition of human action and road condition is a foundation and precondition of implementing self-control of intelligent prosthesis. In this paper, a Gaussian mixture model and hidden Markov model are used to recognize the road condition and human motion modes based on the inertial sensor in artificial limb (lower limb). Firstly, the inertial sensor is used to collect the acceleration, angle and angular velocity signals in the direction of x, y and z axes of lower limbs. Then we intercept the signal segment with the time window and eliminate the noise by wavelet packet transform, and the fast Fourier transform is used to extract the features of motion. Then the principal component analysis (PCA) is carried out to remove redundant information of the features. Finally, Gaussian mixture model and hidden Markov model are used to identify the human motion modes and road condition. The experimental results show that the recognition rate of routine movement (walking, running, riding, uphill, downhill, up stairs and down stairs) is 96.25%, 92.5%, 96.25%, 91.25%, 93.75%, 88.75% and 90% respectively. Compared with the support vector machine (SVM) method, the results show that the recognition rate of our proposed method is obviously higher, and it can provide a new way for the monitoring and control of the intelligent prosthesis in the future.
The performance of intelligent prosthetic knee has an important effect on the realization of physiological gait of transfemoral amputees. A new type of single axis hydraulic damping knee prosthesis was designed based on the analysis of physiological gait. The training methods of the stance and swing phase were proposed. Knee prosthesis test was done through simulation and measurement device. The control target of peak flexion angle during swing of knee prosthesis is chosen to be 60–70°. When the damper valve closure was 0%, maximum swing-phase knee flexion angle of knee prosthesis were (86±2)°, (91±3)° and (97±3)° with the speed of 0.8 m/s, 1.2 m/s and 1.8 m/s, respectively. Once the valve closure was changed, maximum swing-phase knee flexion angle with different speeds could be adjusted between 60° and 70° and the required valve closure percentage were separately 25%, 40% and 70%. The damping adjustment law of intelligent knee prosthesis to achieve physiological gait was revealed.
A software and hardware platform for gait simulation and system evaluation for lower limb intelligent prosthesis is proposed and designed, in order that the wearable symmetry effect of the intelligent knee prosthesis can be quantitatively analyzed by machine test instead of human wear test. The whole-body three-dimensional gait and motion analysis system instrument, a device to collect gait data such as joint angle and stride of adults, was used for extracting simulated gait characteristic curve. Then, the gait curve was fitted based on the corresponding joint to verify the feasibility of the test platform in the experiment. Finally, the developed artificial knee prosthesis was worn on the prosthetic evaluation system to quantitatively analyze the gait symmetry effect. The results showed that there was no significant difference in gait symmetry between the developed knee joints at different speeds, which could reach more than 88%. The simulation and evaluation of the prosthetic gait have good effects on the functional simulation and evaluation of the lower limb intelligent prosthesis.
The rotation center of traditional hip disarticulation prosthesis is often placed in the front and lower part of the socket, which is asymmetric with the rotation center of the healthy hip joint, resulting in poor symmetry between the prosthesis movement and the healthy lower limb movement. Besides, most of the prosthesis are passive joints, which need to rely on the amputee’s compensatory hip lifting movement to realize the prosthesis movement, and the same walking movement needs to consume 2–3 times of energy compared with normal people. This paper presents a dynamic hip disarticulation prosthesis (HDPs) based on remote center of mechanism (RCM). Using the double parallelogram design method, taking the minimum size of the mechanism as the objective, the genetic algorithm was used to optimize the size, and the rotation center of the prosthesis was symmetrical with the rotation center of the healthy lower limb. By analyzing the relationship between the torque and angle of hip joint in the process of human walking, the control system mirrored the motion parameters of the lower on the healthy side, and used the parallel drive system to provide assistance for the prosthesis. Based on the established virtual prototype simulation platform of solid works and Adams, the motion simulation of hip disarticulation prosthesis was carried out and the change curve was obtained. Through quantitative comparison with healthy lower limb and traditional prosthesis, the scientificity of the design scheme was analyzed. The results show that the design can achieve the desired effect, and the design scheme is feasible.
The body weight support rehabilitation training system has now become an important treatment method for the rehabilitation of lower limb motor dysfunction. In this paper, a pelvic brace body weight support rehabilitation system is proposed, which follows the center of mass height (CoMH) of the human body. It aims to address the problems that the existing pelvic brace body weight support rehabilitation system with constant impedance provides a fixed motion trajectory for the pelvic mechanism during the rehabilitation training and that the patients have low participation in rehabilitation training. The system collectes human lower limb motion information through inertial measurement unit and predicts CoMH through artificial neural network to realize the tracking control of pelvic brace height. The proposed CoMH model was tested through rehabilitation training of hemiplegic patients. The results showed that the range of motion of the hip and knee joints on the affected side of the patient was improved by 25.0% and 31.4%, respectively, and the ratio of swing phase to support phase on the affected side was closer to that of the gait phase on the healthy side, as opposed to the traditional body weight support rehabilitation training model with fixed motion trajectory of pelvic brace. The motion trajectory of the pelvic brace in CoMH mode depends on the current state of the trainer so as to realize the walking training guided by active movement on the healthy side of hemiplegia patients. The strategy of dynamically adjustment of body weight support is more helpful to improve the efficiency of walking rehabilitation training.
With the aging of the society, the number of stroke patients has been increasing year by year. Compared with the traditional rehabilitation therapy, the application of upper limb rehabilitation robot has higher efficiency and better rehabilitation effect, and has become an important development direction in the field of rehabilitation. In view of the current development status and the deficiency of upper limb rehabilitation robot system, combined with the development trend of all kinds of products of the upper limb rehabilitation robot, this paper designed a center-driven upper limb rehabilitation training robot for cable transmission which can help the patients complete 6 degrees of freedom (3 are driven, 3 are underactuated) training. Combined the structure of robot with more joints rehabilitation training, the paper choosed a cubic polynomial trajectory planning method in the joint space planning to design two trajectories of eating and lifting arm. According to the trajectory equation, the movement trajectory of each joint of the robot was drawn in MATLAB. It laid a foundation for scientific and effective rehabilitation training. Finally, the experimental prototype is built, and the mechanical structure and design trajectories are verified.
Rehabilitation engineering is an important branch of rehabilitation medicine. Relying on combination of medical and engineering research projects to carry out the cultivation of rehabilitation medicine-engineering interdisciplinary postgraduates of medical engineering is an important way to train high-quality composite innovative talents. This article introduces the medicine-engineering interdisciplinary innovative training model of rehabilitation engineering medical workers piloted by the Department of Rehabilitation Medicine of Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine and the Research Institute of Rehabilitation Engineering and Technology of University of Shanghai for Science and Technology. By clarifying the objectives of medicine-engineering interdisciplinary postgraduates training, strengthening the construction of mentor teams, establishing multi-disciplinary postgraduates courses, improving teaching arrangements and apprenticeship plans, and encouraging the exchange of postgraduates with different research backgrounds, this training mode cultivates postgraduates to be guided by clinical problems in rehabilitation medicine to expand scientific research and research ideas, pomotes the transformation of research achievements and their application in clinical practice, and cultivates compound-type rehabilitation engineering research talents with post competence. The purpose is to provide a reference for the training of future composite rehabilitation engineering research talents.