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In order to make the designed ankle robotic system simpler, practical, and clinically oriented, we developed a novel $\underline{R}-2\underline{U}PS/RR$ ankle rehabilitation robot with a variety of training functions covering all the required ranges of motion of the ankle joint complex (AJC), where $U$ , $P$ , $S$ , and $R$ denote universal, prismatic, spherical, and revolute joints, respectively, and the underlined letter denotes the actuated joint. The robot was designed with three degrees of freedom (DOFs), with a series $R$ mechanism and a $2\underline{U}PS/RR$ parallel mechanism. The main advantage is that the height of the robot is very low, which is convenient for clinical use by patients. At first, the mechanism design and inverse solution of positions were introduced in detail. Then, the patient-passive exercise based on the predefined trajectory tracking and patient-active exercise based on the spring model were developed to satisfy different rehabilitation stages. Finally, experiments with healthy subjects were conducted to verify the effectiveness of the developed patient-passive and patient-active exercises of the developed ankle rehabilitation robot, with results compared with the existing ankle robotic system showing good trajectory tracking performance and interactive performance.

In this paper, the problem of a fully actuated hexarotor performing a physical interaction with the environment through a rigidly attached tool is considered. A nonlinear model predictive impedance control (NMPIC) method is proposed to achieve the goal in which the controller is able to simultaneously handle the constraints and maintain the compliant behavior. The design of NMPIC is the combination of a nonlinear model predictive control and impedance control based on the dynamics of the system. A disturbance observer is exploited to estimate the external wrench and then provide compensation for the model which was employed in the controller. Moreover, a weight adaptive strategy is proposed to perform the online tuning of the weighting matrix of the cost function within the optimal problem of NMPIC to improve the performance and stability. The effectiveness and advantages of the proposed method are validated by several simulations in different scenarios compared with the general impedance controller. The results also indicate that the proposed method opens a novel way for interaction force regulation.

Patients with hemiplegia are usually restricted to performing general bilateral activities of daily life (gbADLs). Bilateral training has been verified to contribute to the rehabilitation of physical functions. Although robotic systems are gradually being employed in the field of rehabilitation, few studies have performed simulations with regards to gbADLs for training. Therefore, a novel end-effector bilateral rehabilitation robotic system (EBReCS) for the upper limb is developed in this article for the task rendering of gbADLs, in which the gbADL-corresponding workspace is obtained via modularly designed bilateral parallelogram mechanisms, and interaction rendering of multiple bimanual modes (uncoupled, trans-soft-coupled, trans-semi-coupled, and rotation-coupled) is achieved by implementing the admittance model, the inner force field between robotic end-effectors, and the outer force field distributed around. Experiments of the proposed four rehabilitation training modes were carried out on the healthy subject, with the results showing a feasible method of the EBReCS in the simulation of multiple bimanual coordinated rehabilitation training tasks. In the future, the constructed EBReCS is expected to be clinically tested and exploited for home rehabilitation as a coordinated training device.

Patients with hemiplegia are usually restricted to performing general bilateral activities of daily life (gbADLs). Bilateral training has been verified to contribute to the rehabilitation of physical functions. Although robotic systems are gradually being employed in the field of rehabilitation, few studies have performed simulations with regards to gbADLs for training. Therefore, a novel end-effector bilateral rehabilitation robotic system (EBReCS) for the upper limb is developed in this article for the task rendering of gbADLs, in which the gbADL-corresponding workspace is obtained via modularly designed bilateral parallelogram mechanisms, and interaction rendering of multiple bimanual modes (uncoupled, trans-soft-coupled, trans-semi-coupled, and rotation-coupled) is achieved by implementing the admittance model, the inner force field between robotic end-effectors, and the outer force field distributed around. Experiments of the proposed four rehabilitation training modes were carried out on the healthy subject, with the results showing a feasible method of the EBReCS in the simulation of multiple bimanual coordinated rehabilitation training tasks. In the future, the constructed EBReCS is expected to be clinically tested and exploited for home rehabilitation as a coordinated training device.

When the under-actuated hand pinches the object on the worktable, the trajectory of the end of the finger is not a straight line, which makes it difficult for the hand to grasp the object from its both sides. In order to overcome this shortcoming, this paper proposes a new configuration of the linear-parallel and self-adaptive under-actuated hand which uses the four-link and sliding base mechanism to compensate for the vertical displacement of the end of the finger. Based on this new configuration, the mechanical structure of the under-actuated hand is designed, which has five degrees of freedom (DOFs), and is mainly composed of two fingers, a sliding base, four link compensation mechanisms and an outer base. These two fingers have exactly the same structure and size, where each finger uses only one motor to control two joints of the finger which realizes the under-actuated function. Through the cooperation of the four-link and sliding base mechanism, the under-actuated hand can realize the linear-parallel and self-adaptive hybrid grasping mode. Kinematics analysis and contact force analysis of the under-actuated hand are discussed, and the prototype of the under-actuated hand is developed to carry out the grasping experiments. The results of the simulation and experiment all show that the under-actuated hand has good motion performance and grasping stability and can be used as an end effector for intelligent robots.

Ran Jiao,1 Shuai Peng,2 Lulu Wang,3 Man Feng,4 Youqin Li,3 Jing Sun,3 Dongyi Liu,5 Jia Fu,5 Chang Feng5 1Hospital of Shandong University, Jinan, 250100, People’s Republic of China; 2Department of Nursing, Yankuang New Journey General Hospital, Zoucheng, 273500, People’s Republic of China; 3Cheeloo College of Medicine, Shandong University, Jinan, 250102, People’s Republic of China; 4Department of Pathology, Affiliated Hospital of Shandong Academy of Medical Sciences, the Third Affiliated of Shandong First Medical University, Jinan, 250000, People’s Republic of China; 5Department of Anaesthesiology, the Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, 250033, People’s Republic of ChinaCorrespondence: Chang Feng, Department of Anaesthesiology, the Second Hospital, Cheeloo College of Medicine, Shandong University, 247 Bei Yuan Street, Jinan, 250033, People’s Republic of China, Tel +86-17660085521, Email fengc2016@126.comPurpose: To investigate, in patients with gastric carcinoma undergoing laparoscopic radical gastrectomy, the effects of ultrasound-guided quadratus lumborum block (UG-QLB) combined with general anaesthesia (GA) on the postoperative recovery compared with GA alone.Patients and Methods: The retrospective study enrolled 231 patients with gastric carcinoma undergoing laparoscopic radical gastrectomy, including 119 patients who received UG-QLB combined with GA (Group QG), and 112 patients undergoing GA alone (Group GA). The primary endpoint was the postoperative 3-year recurrence-free survival (RFS). The secondary endpoints were the average visual analogue scale (VAS) scores within 48 h after surgery, the first time of postoperative ambulation, the first time of flatus, postoperative hospitalization, perioperative opioid requirement and adverse effects after surgery.Results: UG-QLB combined with GA did not affect the 3-year RFS in patients undergoing laparoscopic radical gastrectomy (HR 0.659, 95% CI 0.342– 1.269, P=0.212). However, the VAS ranking analysis implicated that it could significantly alleviate the postoperative pain in laparoscopic radical gastrectomy patients (P< 0.01). In addition, it dramatically facilitated the early recovery of postoperative ambulation and flatus, while shortening the duration of postoperative hospitalization (P< 0.01). The most important was it could remarkably reduce the opioid consumption (P< 0.01), which in the meanwhile, reduced the incidence of postoperative nausea and vomiting (PONV) (P=0.01).Conclusion: Although UG-QLB combined with GA did not improve the 3-year RFS for patients with gastric carcinoma undergoing laparoscopic radical gastrectomy, it could provide satisfactory postoperative pain relief, reduce opioid consumption and adverse effects, which subsequently facilitates postoperative early rehabilitation.Keywords: gastric adenocarcinoma, prognosis, postoperative early recovery, laparoscopic radical gastrectomy, quadratus lumborum block, ultrasound guidance

During the flight of quadrotor unmanned aerial vehicle manipulator, external wind and model uncertainties will significantly affect the accuracy and stability of the controller. This study investigates the problem of high-precision attitude control for the quadrotor manipulator that is equipped with a 2-DOF robotic arm in presence of several disturbances based on a new sliding mode observer and a corresponding sliding mode controller. As for the proposed sliding mode observer, to reduce its estimation chattering phenomenon, a sigmoid function is exploited to replace the discontinuous signum function. Moreover, to adapt to the estimation of disturbances with different upper bounds of the first derivative, a fuzzy logic system algorithm is used to adaptively update the observer gains and slope parameters of the sigmoid function. Furthermore, a generalized super-twisting algorithm is incorporated into the proposed sliding mode observer. Similarly, the sliding mode controller is constructed by using the generalized super-twisting algorithm and a sigmoid function in addition to the sliding mode observer-based feedforward disturbance compensation. In addition, to further relieve the influence of system sensor noise, a tracking differentiator is exploited to incorporate with both proposed sliding mode observer and sliding mode controller. Finally, to demonstrate the effectiveness of the proposed method, several simulations and experiments on the quadrotor unmanned aerial vehicle manipulator system are conducted under varying external disturbances.

Panacis Quinquefolii Radix is the dry root of Panax quinquefolium, which is a perennial plant of Araliaceae. The plant has a long growth cycle and serious growth barrier problem, which leads to the use of pesticides. As a result, the pesticide residues in Panacis Quinquefolii Radix are arousing great concern. This paper reviews the research findings on the investigation, detection methods, content analysis and risk assessment of pesticide residues in Panacis Quinquefolii Radix since 1993, and compares the pesticide residue limit standards of different countries and regions. The pesticide residues in Panacis Quinquefolii Radix have been changing from organochlorines with high toxicity to triazines and triazoles with low toxicity. The pesticide residues are generally low, while the pollution of pentachloronitrobenzene and other pesticides still exist. The detection method has evolved from chromatography to chromatography-mass spectrometry. There are no reports of health risks caused by pesticide residues of Panacis Quinquefolii Radix. Pesticide residue is a major factor restricting the sound development of Panacis Quinquefolii Radix industry in China. Therefore, we suggest to improve the registration of pesticides applied to the plant, popularize mature ecological planting mode and supporting technology, and strengthen the research on the risk assessment and limit standard of pesticide residue in Panacis Quinquefolii Radix.

Aerial physical interaction is a promising field for unmanned aerial vehicles in future applications. This paper presents a novel paradigm for automatic aerial contact-based sliding interaction (inspection/cleaning) tasks in aerial robotics allowing a 3D force with a constant norm to be applied on generic surfaces with unknown geometry. The interaction task is achieved by a fully-actuated hexarotor equipped with a rigidly attached end-effector under a passivity-based geometric impedance controller and a new sliding-mode extended state observer to estimate the interaction wrench. In order to increase the observer performance and reduce the estimation chattering phenomenon, the observer is innovatively incorporated with a super-twisting algorithm and a sigmoid function with a switching gain being adaptively updated by a fuzzy logic system. A detailed stability analysis for the observer is presented based on the Lyapunov stability theory. The proposed control approach is validated in several simulations in which we try to accomplish the aerial physical sliding interaction task with different types of objects under various sliding speeds.

With the widespread application of rehabilitation robots, surface electromyography (sEMG), as a non-invasive way, has become an effective tool to judge the activation state of the related muscles. The traditional muscle activation model is not accurate enough for the reason that the sEMG signals contain wealth of unknown information. To estimate the muscle activation state and to evaluate the effect of ankle rehabilitation training, the activation mean sample entropy is proposed in this paper which is modified by the sample entropy of the complexity of the expression sequence based on the traditional muscle activation model. The degree of muscle activation in the process of ankle rehabilitation training was evaluated by using a parallel ankle robotic system, and the accuracy of the index was verified by conducting experiments with a healthy subject.

Because of low efficiency and accuracy in the domain in the’ oposed an evaluation model based on the method of deep learning and designed a optimal RBM training algorithm. The comparative experimental model in this paper mainly adopts naive Bayesian model algorithm, restricted Boltzmann machine model algorithm and perceptron model algorithm, respectively based on the training data of the algorithm model in this paper. The algorithm proposed in this paper can obtain high calculation accuracy under the condition of given training sample data, and also has good calculation accuracy in terms of running time. In the process of model training, the model proposed in this paper can obtain high accuracy in less training time, and the model has the least calculation time. The results have a good capacity of extracting features and can reflect the essential features by comparing the result with other different modern optimization algorithms.

In this work, we approach high-precision attitude control problem of UAV manipulators in presence of external disturbances. A disturbance observer is exploited to estimate the disturbance, meanwhile we used the estimated result as a feed-forward compensation. A backstepping controller is employed to stabilize the UAV attitude by feedback. The mathematical model of UAV manipulator is constructed by combining the UAV base and the equipped robotic arm together. Furthermore, to relieve the influence of sensor noise, we fused a tracking differentiator into the whole system. The constructed method is validated in realistic simulations, where we executed UAV manipulator hovering flight with varying external disturbances.