In response to the problems of mismatched human-robot motion and poor human-robot coupling (HRC) performance in ankle rehabilitation robots, this study proposes a cable-driven flexible ankle rehabilitation robot (FARR) based on biomimetic design and analyzes its HRC performance. Firstly, based on the motion characteristics and physiological structure of the ankle joint, an equivalent model of the ankle joint is proposed to solve the workspace of the ankle joint. Secondly, a design configuration of a cable-driven FARR with a flexible equivalent axis is proposed, and the structure of the FARR is designed. The robot's kinematics and dynamics are analyzed to solve the robot's workspace. By comparing the workspace of the ankle joint with the robot's workspace, the completeness of the robot's motion function is verified. Furthermore, the HRC dynamic theory model and the HRC dynamic simulation model are established to solve the HRC joint torque during the HRC system motion. The results show that the HRC joint torque is small in magnitude and stable in variation, indicating that the burden on the joint during robot motion is minimal. Finally, a prototype of the FARR is built, and motion function experiments of the HRC system are conducted to verify the matching between actual human motion and FARR motion under the HRC system.

Ankle injury and dysfunction are always accompanied by abnormal peripheral tissues. In order to achieve a more comprehensive rehabilitation training, this article firstly studies the movement characteristics of the surrounding muscles of the ankle-foot. The human musculoskeletal model in OpenSim is used for human exercise experiment. And the relationship between different muscles around the ankle-foot and the direction of the ankle-foot movement are measured respectively, so as to formulate ankle-foot static/dynamic rehabilitation strategies related to the auxiliary training of the ankle-foot muscle. In order to implement the established rehabilitation exercise strategy and to reduce the control difficulty of rehabilitation robot, a new type of decoupling series-parallel mechanism with three rotations and one movement is proposed. After analyzing the degree of freedom and the positive kinematics solution, it is proved that it is completely decoupled in kinematics, can realize the independence of motion control, and there is no singular space. Then, under the premise of meeting the space required for the implementation of the rehabilitation strategy, the proposed new ankle-foot rehabilitation robot is optimized in terms of structure and component size, which improves its space utilization and optimizes the overall mechanical performance. Finally, the dynamic simulation experiment is carried out with the dynamic rehabilitation strategy as the goal, which proves that the robot can realize the normal gait simulation movement in sitting posture, and the motion control of the robot is independent of each other and shows good dynamic performance. Through investigation, the ankle-foot rehabilitation robot designed in this article is cost-effective.

In this letter, a human–machine compatible ankle rehabilitation robot (HMCARR) is proposed to help stroke patients with motion dysfunction recover their motor function. The HMCARR can make the human ankle center-of-rotation (H-CoR) and the ankle rehabilitation robot center-of-rotation (R-CoR) coincide in real-time. The overall idea is to analyze from the “human” perspective to the “human–machine” perspective, and then to the “machine” perspective. Firstly, from the “human” perspective: a spherical-pair-with-clearance equivalent human ankle model and a H-CoR estimation model are proposed, and the motion range of the H-CoR is analyzed. Secondly, from the “ human–machine” perspective: to obtain the mechanical design principles of the HMCARR, degree-of-freedom (DOF) and kinematic analyses of the human–machine closed chain model are conducted. Finally, from the “machine” perspective: DOF, kinematics, singularity, sensitivity, and workspace analysis are performed for the HMCARR based on a 3-RRCRR parallel mechanism, where R and C represent a revolute pair and a cylindrical pair, respectively. This study indicates that the mechanical design principles of the HMCARR include three requirements for the DOFs, kinematic independence, and position workspace. The results suggest that the HMCARR based on the 3-RRCRR parallel mechanism can achieve coincidence between H-CoR and R-CoR in real-time.

When applying continuous motion estimation (CME) model based on sEMG to human-robot system, it is inevitable to encounter scenarios in which the motions performed by the user are different from the motions in the training stage of the model. It has been demonstrated that the prediction accuracy of the currently effective approaches on untrained motions will be significantly reduced. Therefore, we proposed a novel CME method by introducing muscle synergy as feature to achieve better prediction accuracy on untrained motion tasks. Specifically, deep non-smooth NMF (Deep-nsNMF) was firstly introduced on synergy extraction to improve the efficiency of synergy decomposition. After obtaining the activation primitives from various training motions, we proposed a redundancy classification algorithm (RC) to identify shared and task-specific synergies, optimizing the original redundancy segmentation algorithm (RS). NARX neural network was set as the regression model for training. Finally, the model was tested on prediction tasks of eight untrained motions. The prediction accuracy of the proposed method was found to perform better than using time-domain feature as input of the network. Through Deep-nsNMF with RS, the highest accuracy reached 99.7%. Deep-nsNMF with RC performed similarly well and its stability was relatively higher among different motions and subjects. Limitation of the approach is that the problem of positive correlation between the prediction error and the absolute value of real angle remains to be further addressed. Generally, this research demonstrates the potential for CME models to perform well in complex scenarios, providing the feasibility of dedicating CME to real-world applications.

To clarify the utility of colleges and universities to help the development of sports industry, and to evaluate the degree of utility in promoting the sports industry in colleges and universities, is the effective way to further promote the development of sports industry in colleges and...