ABSTRACT
Most lower limb rehabilitation robots are limited to specific training postures to adapt to stroke patients in multiple stages of recovery. In addition, there is a lack of attention to the switching functions of the training side, including left, right, and bilateral, which enables patients with hemiplegia to rehabilitate with a single device. This article presents an exoskeleton robot named the multistage hemiplegic lower-limb rehabilitation robot, which has been designed to do rehabilitation in multiple training postures and training sides. The mechanism consisting of the thigh, calf, and foot is introduced. Additionally, the design of the multi-mode limit of the hip, knee, and ankle joints supports delivering therapy in any posture and training sides to aid patients with hemiplegia in all stages of recovery. The gait trajectory is planned by extracting the gait motion trajectory model collected by the motion capture device. In addition, a control system for the training module based on adaptive iterative learning has been simulated, and its high-precision tracking performance has been verified. The gait trajectory experiment is carried out, and the results verify that the trajectory tracking performance of the robot has good performance.
Subject(s)
Hemiplegia , Robotics , Humans , Lower Extremity , Foot , GaitABSTRACT
Rehabilitation robots are used to promote structural and functional recovery of the nervous system with repetitive, task-oriented training and have been gradually applied to clinical rehabilitation training. This paper proposes an upper limb exoskeleton rehabilitation robot system that could realize shoulder-elbow-wrist joint rehabilitation training. Firstly, a motion equivalent model was established based on the upper limb movement mechanism, the robot mechanism configuration was designed, and the optimization algorithm and spatial mechanism theory were used to optimize and analyze the structural parameters and human-machine compatibility of the robot, which will guide the design of the robot's model. Then, the robot kinematics were solved, and its maximum motion range, dexterity distribution, and daily motion trajectory were simulated. Finally, a system prototype was built to test the maximum range of robot-assisted human upper limb training by laser tracker, while the pressure of human-machine interaction during training was captured and analyzed by flexible sensors. The results show that the proposed rehabilitation robot could nearly completely cover the range of motion of upper limb joints and meet the needs of trajectory training, and the linear velocity dexterity and angular velocity dexterity in the motion space are maximum 0.55 and 0.89, and the human-machine interaction pressures during the training process are all less than 10 kPa. Besides, this paper also conducted a system evaluation based on the fuzzy comprehensive evaluation model, and the evaluation result was 0.39, with an excellent evaluation grade, it indirectly indicates that the robot's overall performance was good.
Subject(s)
Exoskeleton Device , Robotics , Shoulder Joint , Humans , Robotics/methods , Upper Extremity/physiology , Movement/physiologyABSTRACT
BACKGROUND: Remote-controlled robotic vascular interventional surgery can reduce radiation exposure to interventional physicians and improve safety. However, inconvenient operation and lack of force feedback limit its application. MATERIALS AND METHODS: A new wearable robotic system for vascular interventional surgery is designed, which is more flexible in operation. It ensures the safety of surgery through haptic force feedback. The system was evaluated by human vascular models and animal experiments. RESULTS: The average static error of the system is 0.048 mm when the axial motion is 250 mm and 1.259° when the rotational motion is 400°. The average error of the force feedback is 0.021 N. The results of vascular model experiments and animal experiments demonstrate the feasibility and safety of the system. CONCLUSIONS: The proposed robotic system can assist physicians in remotely delivering standard catheters or guidewires. The system is more flexible and uses haptic force feedback to ensure surgical safety.
ABSTRACT
At present, most vascular intervention robots cannot cope with the more common coronary complex lesions in the clinic. Moreover, the lack of effective force feedback increases the risk of surgery. In this paper, a vascular interventional robot that can collaboratively deliver multiple interventional instruments has been developed to assist doctors in the operation of complex lesions. Based on the doctor's skills and the delivery principle of interventional instruments, the main and slave manipulators of the robot system are designed. Haptic force feedback is generated through resistance measuring mechanism and active drag system. In addition, a force feedback control strategy based on force-velocity mapping is proposed to realize the continuous change of force and avoid vibration. The proposed robot system was evaluated through a series of experiments. The experimental results show that the system can accurately measure the delivery resistance of interventional instruments, and provide haptic force feedback to doctors. The capability of the system to collaboratively deliver multiple interventional instruments is effective. Therefore, it can be considered that the robot system is feasible and effective.
Subject(s)
Robotic Surgical Procedures , Robotics , Coronary Vessels , Equipment Design , Mechanical Phenomena , FeedbackABSTRACT
Aiming at the shortcomings of most existing control strategies for lower limb rehabilitation robots that are difficult to guarantee trajectory tracking effect and active participation of the patient, this paper proposes a force/position-based velocity control (FPVC) strategy for the hybrid end-effector lower limb rehabilitation robot (HE-LRR) during active training. The configuration of HE-LRR is described and the inverse Jacobian analysis is carried out. Then, the FPVC strategy design is introduced in detail, including normal velocity planning and tangential velocity planning. The experimental platform for the HE-LRR system is presented. A series of experiments are conducted to validate the FPVC strategy's performance, including trajectory measurement experiments, force and velocity measurement experiments, and active participation experiments. Experimental studies show that the end effector possesses good following performance with the reference trajectory and the desired velocity, and the active participation of subjects can be adjusted by the control strategy parameters. The experiments have verified the rationality of the FPVC strategy, which can meet the requirements of trajectory tracking effect and active participation, indicating its good application prospects in the patient's robot-assisted active training.
ABSTRACT
A stroke is a common disease that can easily lead to lower limb motor dysfunction in the elderly. Stroke survivors can effectively train muscle strength through leg flexion and extension training. However, available lower limb rehabilitation robots ignore the knee soft tissue protection of the elderly in training. This paper proposes a human-robot cooperative lower limb active strength training based on a robust admittance control strategy. The stiffness change law of the admittance model is designed based on the biomechanics of knee joints, and it can guide the user to make force correctly and reduce the stress on the joint soft tissue. The controller will adjust the model stiffness in real-time according to the knee joint angle and then indirectly control the exertion force of users. This control strategy not only can avoid excessive compressive force on the joint soft tissue but also can enhance the stimulation of quadriceps femoris muscles. Moreover, a dual input robust control is proposed to improve the tracking performance under the disturbance caused by model uncertainty, interaction force and external noise. Experiments about the controller performance and the training feasibility were conducted with eight stroke survivors. Results show that the designed controller can effectively influence the interaction force; it can reduce the possibility of joint soft tissue injury. The robot also has a good tracking performance under disturbances. This control strategy also can enhance the stimulation of quadriceps femoris muscles, which is proved by measuring the muscle electrical signal and interaction force. Human-robot cooperative strength training is a feasible method for training lower limb muscles with the knee soft tissue protection mechanism.
Subject(s)
Resistance Training , Robotics , Stroke , Humans , Aged , Robotics/methods , Range of Motion, Articular , Quadriceps MuscleABSTRACT
The lower limb rehabilitation robot is a typical man-machine coupling system. Aiming at the problems of insufficient physiological information and unsatisfactory safety performance in the compliance control strategy for the lower limb rehabilitation robot during passive training, this study developed a surface electromyography-based gain-tuned compliance control (EGCC) strategy for the lower limb rehabilitation robot. First, the mapping function relationship between the normalized surface electromyography (sEMG) signal and the gain parameter was established and an overall EGCC strategy proposed. Next, the EGCC strategy without sEMG information was simulated and analyzed. The effects of the impedance control parameters on the position correction amount were studied, and the change rules of the robot end trajectory, man-machine contact force, and position correction amount analyzed in different training modes. Then, the sEMG signal acquisition and feature analysis of target muscle groups under different training modes were carried out. Finally, based on the lower limb rehabilitation robot control system, the influence of normalized sEMG threshold on the robot end trajectory and gain parameters under different training modes was experimentally studied. The simulation and experimental results show that the adoption of the EGCC strategy can significantly enhance the compliance of the robot end-effector by detecting the sEMG signal and improve the safety of the robot in different training modes, indicating the EGCC strategy has good application prospects in the rehabilitation robot field.
Subject(s)
Robotics , Humans , Electromyography/methods , Lower Extremity/physiology , Electric ImpedanceABSTRACT
To provide stroke patients with good rehabilitation training, the rehabilitation robot should ensure that each joint of the limb of the patient does not exceed its joint range of motion. Based on the machine vision combined with an RGB-Depth (RGB-D) camera, a convenient and quick human-machine interaction method to measure the lower limb joint range of motion of the stroke patient is proposed. By analyzing the principle of the RGB-D camera, the transformation relationship between the camera coordinate system and the pixel coordinate system in the image is established. Through the markers on the human body and chair on the rehabilitation robot, an RGB-D camera is used to obtain their image data with relative position. The threshold segmentation method is used to process the image. Through the analysis of the image data with the least square method and the vector product method, the range of motion of the hip joint, knee joint in the sagittal plane, and hip joint in the coronal plane could be obtained. Finally, to verify the effectiveness of the proposed method for measuring the lower limb joint range of motion of human, the mechanical leg joint range of motion from a lower limb rehabilitation robot, which will be measured by the angular transducers and the RGB-D camera, was used as the control group and experiment group for comparison. The angle difference in the sagittal plane measured by the proposed detection method and angle sensor is relatively conservative, and the maximum measurement error is not more than 2.2 degrees. The angle difference in the coronal plane between the angle at the peak obtained by the designed detection system and the angle sensor is not more than 2.65 degrees. This paper provides an important and valuable reference for the future rehabilitation robot to set each joint range of motion limited in the safe workspace of the patient.
ABSTRACT
In the process of rehabilitation, the objectivity and the accuracy of rehabilitation assessment have an obvious impact on the follow-up training. To improve this problem, using a multi-sensor source, this paper attempts to establish a comprehensive assessment method of the finger rehabilitation effect, including three indicators of finger muscle strength, muscle fatigue degree, and range of motion. Firstly, on the basis of the fingertip pressure sensor of the End-Effector Finger Rehabilitation Robot, a mathematical model of finger muscle strength estimation was established, and the estimated muscle strength was scored using the entropy weight method. Secondly, using an sEMG signal sensor, a fatigue monitoring system was designed in the training process, and the fatigue degree was determined on the basis of the change trend of the eigenvalues of MAV and RMS. Lastly, a human-machine motion coupling model was established, and the joint range of motion acquisition and scoring model were obtained on the basis of the motor encoder. According to the above three indicators, using the AHP assessment method to establish a comprehensive rehabilitation assessment method, the effectiveness of the method was verified by experiments. This paper provides a potential new idea and method for objective, accurate, and convenient assessment of finger function rehabilitation, which is of positive significance for alleviating the burden on rehabilitation doctors and improving rehabilitation efficiency.
ABSTRACT
Patient transfer has always been a difficult problem, usually requiring multiple caregivers to work together, which is time consuming and can easily cause secondary injuries to the patient. In addition, with the crisis of COVID-19, the issue of patient transfer is even more critical, as caregivers are at a high risk of infection, causing significant damage to healthcare resources. In this paper, a patient transfer assist system named E-pat-plus (Easy Patient Transfer plus) has been proposed; it can assist caregivers in transferring patients, reduce direct contact between them, and avoid secondary injuries. In the mechanical structure of this apparatus, a novel five-gear assembly module and a synchronous belt pulley set are proposed; they are the key points to the basic functional realization of the device and can reduce the cost of the prototype. Furthermore, a fuzzy (proportion-integration-differentiation) PID-based cross-coupling control strategy is applied to the apparatus to ensure the stability and safety of the operation. Finally, some preliminary experiments, including current experiments and error experiments, are carried out to verify the reliability of the device and lay the foundation for clinical tests.
Subject(s)
Caregivers , Equipment Design , Patient Transfer/methods , COVID-19/epidemiology , COVID-19/prevention & control , COVID-19/transmission , Female , Health Personnel , Humans , Male , Reproducibility of ResultsABSTRACT
By analyzing the physiological structure and motion characteristics of human ankle joint, a four degree of freedom generalized spherical parallel mechanism is proposed to meet the needs of ankle rehabilitation. Using the spiral theory to analyze the motion characteristics of the mechanism and based on the method of describing the position with spherical coordinates and the posture with Euler Angle, the inverse solution of the closed vector equation of mechanism position is established. The workspace of mechanism is analyzed according to the constraint conditions of inverse solution. The workspace of the moving spherical center of the mechanism is used to match the movement space of the tibiotalar joint, and the workspace of the dynamic platform is used to match the movement space of subtalar joint. Genetic algorithm is used to optimize the key scale parameters of the mechanism. The results show that the workspace of the generalized spherical parallel mechanism can satisfy the actual movement space of human ankle joint rehabilitation. The results of this paper can provide theoretical basis and experimental reference for the design of ankle joint rehabilitation robot with high matching degree.