Traditional joint space admittance controller for N-DOF robotic systems is complexity and easily leads to incongruous movement among all joints. Our study introduces a central pattern generator (CPG) network into one-dimension joint space admittance control for the custom-made lower limb robotic exoskeleton with four DOFs, to guarantee the coordinated movement and security of users. The predefined trajectories for four joints are produced by CPG. Unilateral knee joint torque of subjects is detected based on corresponding muscle EMG signals. The torque is transformed into an additional set of state variables for CPG based on the one-dimension admittance controller. CPG harmonically adjusts the predefined trajectories by the additional state variables. Finally, the robotic exoskeleton completes the predefined trajectories with a classical PID controller.

A generalized framework to achieve coordinated admittance control for multi-joint lower limb robotic exoskeleton

The force analysis of a pelvic support walking robot with joint compliance is discussed in this paper. During gait training, pelvic motions of hemiplegic patients may be excessively large or out of control; however, restriction of pelvic motions is not likely to facilitate successful rehabilitation. A robot-assisted pelvic balance trainer (RAPBT) is proposed to help patients control the range of motion via force field, and force analysis is necessary for the control of the compliant joints. Thus, kinematic model and static model are developed to derive the Jacobian and the relation between the interaction forces and the pelvic movements, respectively. Since the joint compliance is realized through a nontorsional spring, a conventional (linear) Jacobian method and a piecewise linear method are derived to relate the interaction forces with the pelvis movements. Three preliminary experiments are carried out to evaluate the effectiveness of the proposed methods and the feasibility of the RAPBT. The experiment results indicate that the piecewise linear method is effective in the calculation of the interaction forces. Gait with pelvic brace strongly resembles free overground walking and partly decreases motion range via force field. The findings of this research demonstrate that the pelvic brace with joint compliance may provide effective interventions.

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Force Analysis and Evaluation of a Pelvic Support Walking Robot with Joint Compliance.

Nerve injury after stroke leads to disorders of locomotion and a declining balance function, which increases the risk of falling. Restriction of pelvic motions can hinder successful rehabilitation, hence a robotic-assisted rehabilitation trainer (RART) is proposed to assist patients in controlling the pelvic motions via force field. The mechanical design, kinetic framework, and the intention-based controller of the RART are introduced in this paper. Based on an intention-based control strategy, the robot generates force field that affects the pelvic motions (vertical and lateral motion, rotation, and obliquity) via a compliant pelvic brace while the patient is walking on ground. A control experiment with 16 hemiplegic patients is carried out to examine the effects on recovery of the balance function. Clinical evaluations and gait analysis are performed before and after the treatment. The experimental results show that the proposed control method is effective in motion recognition, and significant improvements of the balance function, gait speed, stride, stride frequency, Fugl-Meyer assessment, peak knee, and hip flexion angle during swing phase for their affected side are observed in the comparisons within the RART group. These preliminary results demonstrate that the proposed robot with force field and visual feedback may be effective in improving the balance function.

Robotic-Assisted Rehabilitation Trainer Improves Balance Function in Stroke Survivors

BACKGROUND Most stroke survivors are suffering from physical motor impairments and confronting with the risk of falls, and well trunk stability is essential for balance during daily functional activities. OBJECTIVES Current fall prevention devices have various limits to the efficient recovery of balance function of the trunk. To provide hemiplegic patients after stroke with the retraining of trunk position sense and a safety environment, a novel fall prevention device is proposed. METHODS Firstly, the structure of the device is introduced and this work is a first effort towards restoring trunk balance function through retraining of trunk position sense. Secondly, the kinematic and static model of the device are developed. Lastly, kinematic and static analysis are carried out to study the motion characteristics, and a contrast experiment was derived to show the effectiveness of robot. RESULTS No obvious difference in balance ability between two groups prior treatment (P> 0.05). Fugl-Meyer assessment in all the cases were improved in different extent (P< 0.05). The robot group had significantly higher Fugl-Meyer scores after treatment than the control group (P< 0.05). CONCLUSIONS The results show that the fall prevention device has good kinematic dexterity within the prescribed workspace and markedly improves balance function.

Design and analysis of a novel fall prevention device for lower limbs rehabilitation robot.

Nerve injury after stroke usually weakens the trunk muscle strength (TMS) and balance function, which increases the risk of falling and affects the Activities of Daily Living (ADL). Thus a novel fall prevention device is proposed to reinforce the TMS and retrain the sense of trunk position. Firstly, the structure of the fall prevention device for protection is introduced, the forward and inverse kinematic models, and the location and velocity of the mass center and angular velocity are calculated. Then, the kinetic equation of the system based on the Lagrange function and the feedback force misalignment equation used for structural parameters optimization are derived out, the structural parameters incorporated into the structural dynamic model include those related to the feedback force in a given motion trajectory of trunk. Lastly, the numerical simulation using the MATLAB is carried out to study the influence of those parameters. It is found that both the length of link and the stiffness of spring have strong influence on the feedback force during gait training. Global optimization of these structural parameters is carried out to demonstrate the practical application of the proposed method for the forming of force field of the system.

Dynamic Modeling and Optimization of a Fall Prevention Device Using Genetic Algorithm

After analyzing the rehabilitation needs of stroke patients and the previous studies on lower limb rehabilitation robot, our lower limb rehabilitation robot is designed for stroke patients' gait and balance training. The robot consists of the mobile chassis, the support column and the pelvis mechanism and it is described in detail. As the pelvis mechanism allows most of the patient's motion degrees of freedom (DOFs), the kinematics model of the mechanism is set up, and kinematics simulation is carried out to study the motion characteristics of the mechanism. After analyzing the calculation and simulation results, the pelvis mechanism is proven to measure up to the movement needs of the paralytic's waist and pelvis in walking rehabilitation process.

Jing Wang

Papers

Lower limb rehabilitation robot for gait training