Stroke is one of the primary causes of motor disorders, which can seriously affect the patient’s quality of life. However, the assessment of the upper limb affected by stroke is commonly based on scales, and the characteristics of brain reorganization induced by limb movement are not clear. Thus, this study aimed to investigate stroke-related cortical reorganization based on functional near infrared spectroscopy (fNIRS) during upper limb multi-joint linkage movement with reference to the Fugl–Meyer Assessment of the upper extremities (FMA-UE). In total, 15 stroke patients and 15 healthy subjects participated in this study. The functional connectivity (FC) between channels and the regions of interest (ROI) was calculated by Pearson’s correlation coefficient. The results showed that compared with the control group, the FC between the prefrontal cortex and the motor cortex was significantly increased in the resting state and the affected upper limb’s multi-joint linkage movements, while the FC between the motor cortex was significantly decreased during the unaffected upper limb’s multi-joint linkage movements. Moreover, the significantly increased ROI FC in the resting state showed a significantly positive correlation with FMA-UE in stroke patients (p < 0.05). This study highlights a new biomarker for evaluating the function of movement in stroke patients and provides guidance for rehabilitation training.

Background: Pneumatic muscle actuator (PMA) actuated multisection continuum arms are widely applied in various fields with high flexibility and bionic properties. Nonetheless, their kinematic modeling and control strategy proves to be extremely challenging tasks. Methods: The relationship expression between the deformation parameters and the length of PMA with the geometric method is obtained under the assumption of piecewise constant curvature. Then, the kinematic model is established based on the improved D-H method. Considering the limitation of PMA telescopic length, an impedance iterative learning backstepping control strategy is investigated. For one thing, the impedance control is utilized to ensure that the ideal static balance force is maintained constant in the Cartesian space. For another, the iterative learning backstepping control is applied to guarantee that the desired trajectory of each PMA can be accurately tracked with the output-constrained requirement. Moreover, iterative learning control (ILC) is implemented to dynamically estimate the unknown model parameters and the precondition of zero initial error in ILC is released by the trajectory reconstruction. To further ensure the constraint requirement of the PMA tracking error, a log-type barrier Lyapunov function is employed in the backstepping control, whose convergence is demonstrated by the composite energy function. Results: The tracking error of PMA converges to 0.004 m and does not exceed the time-varying constraint function through cosimulation. Conclusion: From the cosimulation results, the superiority and validity of the proposed theory are verified.

The 6-PUS (P: prismatic joint; U: universal joint; S: spherical joint) parallel mechanism study in this paper is the core mechanism used in the rehabilitation robot for children with cerebral palsy, which has a dynamic platform that acts on the pelvis of the child with cerebral palsy to provide support for the child. The complexity of the parallel mechanism leads to complex dynamics analysis and modeling errors, and the design of the controller must consider singularities, unknown external disturbances, stability, and so on. In response to the above considerations, this paper analyses the dynamics of a 6-PUS parallel mechanism and designs a non-singular fast terminal sliding mode control based on adaptive disturbance estimation to address the modeling errors and unknown external disturbance to which the system is subjected in practical applications. Feed-forward compensation of the controller is achieved by estimating the external disturbance and modeling errors to which the system is subjected with an adaptive disturbance estimation strategy. The non-singular fast terminal sliding mode controller is used to suppress the inherent jitter phenomenon of sliding mode control while ensuring the error between the actual trajectory and the desired trajectory converges quickly. Finally, the simulation results demonstrate that the designed controller can achieve highly accurate trajectory tracking despite the presence of modeling errors and external disturbances.